Bok:978 3 319 42448 4
Bok:978 3 319 42448 4
Bok:978 3 319 42448 4
PaoloTasca
TomasoAste
LorianaPelizzon
NicolasPerony Editors
Banking
Beyond Banks
and Money
A Guide to Banking Services in the
Twenty-First Century
Banking Beyond Banks and Money
New Economic Windows
Series editors
MARISA FAGGINI, MAURO GALLEGATI, ALAN P. KIRMAN, THOMAS LUX
Editors
123
Editors
Paolo Tasca Loriana Pelizzon
Centre for Blockchain Technologies SAFE
University College London Goethe University Frankfurt
London Frankfurt am Main
UK Germany
ECUREX Research
Zurich
Switzerland
Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
Paolo Tasca, Tomaso Aste, Loriana Pelizzon and Nicolas Perony
Classication of Crowdfunding in the Financial System . . . . . . . . . . . . . 5
Loriana Pelizzon, Max Riedel and Paolo Tasca
Crowdfunding and Bank Stress . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
Daniel Blaseg and Michael Koetter
How Peer to Peer Lending and Crowdfunding Drive the FinTech
Revolution in the UK . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55
Susanne Chishti
FinTech in China: From Shadow Banking to P2P Lending. . . . . . . . . . . 69
Jnos Barberis and Douglas W. Arner
Features or Bugs: The Seven Sins of Current Bitcoin . . . . . . . . . . . . . . . 97
Nicolas T. Courtois
Decentralized Banking: Monetary Technocracy in the Digital Age . . . . . 121
Adam Hayes
Trustless ComputingThe What Not the How . . . . . . . . . . . . . . . . . . . . 133
Gavin Wood and Jutta Steiner
Reinventing Money and Lending for the Digital Age . . . . . . . . . . . . . . . . 145
Richard D. Porter and Wade Rousse
How Non-Banks are Boosting Financial Inclusion and Remittance . . . . . 181
Diana C. Biggs
Scalability and Egalitarianism in Peer-to-Peer Networks . . . . . . . . . . . . . 197
Fabio Caccioli, Giacomo Livan and Tomaso Aste
v
vi Contents
Keywords Crowdfunding
Distributed Ledger Technologies Blockchain
P2P nance - Peer to Peer nance
e-nance
Fintech
P. Tasca ()
Centre for Blockchain Technologies, University College London, London, UK
e-mail: p.tasca@ucl.ac.uk
T. Aste
Computer Science Department, University College London, London, UK
e-mail: t.aste@ucl.ac.uk
T. Aste
Systemic Risk Centre, London School of Economics, London, UK
L. Pelizzon
SAFE, Goethe University Frankfurt, Frankfurt am Main, DE
e-mail: pelizzon@safe.uni-frankfurt.de
L. Pelizzon
Department of Economics, Ca Foscari University of Venice, Venice, IT
N. Perony
ETH Zurich, Zurich, CH
e-mail: perony@ecurex.com
N. Perony
ECUREX Research, Zurich, CH
This book collects the voices of leading scholars, entrepreneurs, policy makers and
consultants who, through their expertise and keen analytical skills, are best posi-
tioned to picture from various angles the unfolding technological revolution in
banking and nance.
We stand on the brink of a fourth industrial revolution, which will fundamentally
alter the way we live, work, and relate to one another. New technologies are
dramatically transforming our economic systems, and our society in general, into
something very different from what we were used to think about over the last few
decades. The possibilities unlocked by billions of people collectively connected by
mobile devices, with unprecedented processing power, storage capacity, and access
to knowledge, are vast. The introduction of distributed ledger technologies makes
possible to initiate a new economy that is blurring the lines between consumers and
producers, this technology shift is enabling a rapid transition towards what is
known as the economy of collaborative commons: a digital space where providers
and users share goods and services at a marginal cost rapidly approaching nil
(Rifkin 2014). These innovations will be further multiplied by emerging techno-
logical breakthroughs in elds such as machine learning, robotics, the Internet of
Things, nanotechnology, biotechnology, materials science, energy storage and
quantum computing.
In this context, traditional nancial instruments, institutions and markets are
rapidly becoming obsolete and inadequate to serve an increasingly globally inter-
connected online marketplace with an accelerating number of high-frequency
transactions.
As technology progressed, the advent of the Internet era at the end of the last
century opened the road to new nancial services and markets. In Allen et. al 2002,
the word e-nance was coined by Allen et al (2002). to include mobile and digital
nancial services such as online banking, Internet transactions and online trading.
If, during that phase, the traditional brick-and-mortar banking model was somehow
still able to keep its dominant role within the nancial systems, now this position is
challenged by new technology advances. The evolution, and combined use of,
information communication technologies, cryptography, open source computing
methods, time-stamped ledgers, and peer-to-peer distributed networks now afford
end users direct, anonymous, disintermediated and secure access to assets, pay-
ments and nancial services without the need to rely upon banks.
In recent years, we have started to move from e-nance to peer-to-peer (P2P)
nance, dened by Tasca (2015) as: the provision of nancial services and markets
directly by end users to end users using technology-enabled platforms supported by
computer-based and network-based information and communication technologies.
The term P2P nance encompasses cryptocurrencies and blockchain-based nancial
applications, decentralised markets for lending, crowdfunding and other nancial
services, digital assets and wallets.
These technologies are fragmenting and dismantling some of the major banking
services: Lending, deposits, security, advisory services, investments, payments and
Introduction 3
currencies. These nancial services, that were traditionally procured under one roof
with a single point of control, can now be offered by decentralised platforms with
limited or absent human interactionone of the prerequisites and founding pillars
of the brick-and-mortar banking model.
P2P nance is a new form of banking beyond banks and money, emerging as a
consequence of the ongoing FinTech revolution characterized by a nance-focused
trend of technology start-ups and corporations primarily focused on peripheral
industries but increasingly interested in nance. A legion of technology companies
in San Francisco, New York City, London, and elsewhere seized the opportunity
offered by the dissatisfaction of banking customers and are now creating nancial
products and services that are beyond the capacity of banks to replicate. This new
contingent of FinTech companies are not only capturing revenues that were tra-
ditionally banking prots (e.g., in payments or lending), but also experimenting
with new data-led revenue streams for banking.
At the same time, although banks nd it difcult to innovate mostly due of the
burden of their legacy infrastructures, the traditional banking industry benets from
many years of experience with a large number of detailed regulations and opera-
tional procedures, providing the means to operate safely. No such framework
currently exists for P2P nance which is a bottom-up phenomenon, based on
fast-evolving technological advances. P2P nance is shifting the power from the
traditional stakeholders to the end users, and the citizens in general, and creating
new opportunities for entrepreneurs; in doing so it also introduces new risks and
challenges for legal systems and risk management practices.
Similarly, in the twenty-rst century we need the same banking services of the
twentieth century, but the way we expect them to be delivered to us has dramati-
cally changed, as we now leave in the digital age global communication and
information sharing. In the rst decade of the twenty-rst century only, people
connected to the Internet worldwide increased from 350 million to over 2.5 billion.
The use of mobile phones increased from 750 million to over 6 billion. By 2025, if
the current pace of technological innovation is maintained, most of the projected 8
billion people on Earth will be online (Schmidt and Cohen 2013). As long as the
connectivity will continue to increase and become more affordable, by extending
the online experience to places where people today dont even have landline
phones, we envision a landscape where P2P nance will continue to invade and
disrupt the nancial mainstream. New forms of nancial (dis)intermediations, new
ubiquitous accesses to services and decentralised markets will emerge, which will
ll gaps, create value and progressively substitute the traditional banking system.
This book constitutes a unique perspective on this technological and social
revolution, as it is written by the people who are driving it. By presenting an
overview of the new banking and money transfer models and, at the same time,
addressing their challenges and threats, this collection of essays is meant to offer a
guideline for the providers and the consumers of banking services in the twenty-rst
century.
4 P. Tasca et al.
References
Allen, F., Andrews, J.M., Strahan, P.: E-nance: an introduction. J. Financ. Serv. Res. 22(12),
527 (2002)
Rifkin, J.: The Zero Marginal Cost Society: The Internet of Things, the Collaborative Commons,
and the Eclipse of Capitalism. Macmillan (2014)
Schmidt, E., Cohen, J.: The New Digital Age: Reshaping the Future of People, Nations and
Business. Hachette, UK (2013)
Tasca, P.: Digital Currencies: Principles, Trends, Opportunities, and Risks. ECUREX
Research WP, 7 Sept 2015
Classication of Crowdfunding
in the Financial System
Digital technology has become a prerequisite for, and a constant companion of, new
developments in our daily life and business activity. Internet, information communi-
cations technologies, data-driven technologies, modern analytical methods and virtual
infrastructures penetrate into the daily life of every single household by changing
consumer and investment behavior worldwide. Nowadays, anyone with access to the
Internet can participate interactively in digital spaces. Flexible and varied relationships
are formed between people and their diverse identities, both in the online and offline
worlds. We are already living in the so-called economy of Collaborative Commons
characterized by the prevalence of sharing over ownership. This major structural
L. Pelizzon M. Riedel ()
Research Center SAFE, Johann Wolfgang Goethe-University, House of Finance,
Theodor-W.-Adorno Platz 3, 60323 Frankfurt am Main, Germany
e-mail: riedel@safe.uni-frankfurt.de
L. Pelizzon
e-mail: pelizzon@safe.uni-frankfurt.de
P. Tasca
Centre for Blockchain Technologies, University College London, London, UK
e-mail: p.tasca@ucl.ac.uk
change mainly applies to products and services that can be easily standardized and
automated, similar to the broad spectrum of services offered by traditional banks.
The rapid development from the early days of the Internet in the 90s to its current
advancement towards the Internet of Things1 is partly attributable to the emergence of
the so-called Web 2.0. The term Web 2.0 was coined soon after the launch of the
worldwide rst crowdfunding platform ArtistShare in the US in 2003 and about one
year before the pioneering peer-to-peer (P2P) lending platform Zopa was founded in
the United Kingdom in 2005. The year 2004 became a turning point for Internet users.
Being largely consumers of content in the old Web, users transformed into content
creators. User interactivity, collaboration and the resulting content creation were the
main characteristics of Web 2.0. As documented by Schwienbacher and Larralde
(2010), Web 2.0 especially broadened the capabilities of small rms by allowing
users content to inflow and create value for the company. This technological
advancement enabled the rst P2P platforms to utilize the emerging momentum and
popularity of various online social networks, while especially lending platforms took
the simplicity and efciency of credit scores to their advantage and managed to deal
with loan applications at a speed that is close to real time.
The novel nancing segment for consumers and small businesses grew from a
niche to a sizeable market not until the 2008 Financial crisis. Many households, hit
by huge nancial pain, lost trust and condence in the traditional banking sector
(Gritten 2011) and withdrew from nancial markets while looking for alternative
sources to obtaining funds. Banks reduced their lending activity and capital stopped
flowing from those who had it to those who were able to use it to grow businesses
and create jobs, thus, prolonging the Great Recession. At the dawn of the emer-
gency program loans and public bail outs, the reputation of the bankers was already
signicantly undermined in most of the western countries and their traditional role
as credit providers has been criticized and put under spotlight of the public opinion,
(Rose 2010; Stiglitz 2010). The post-crisis period was characterized by a low-yield
environment such that investors became creative in identifying alternative invest-
ments and allocating their funds in new nancial products.
Under this general context, the focus of both capital holders and capital seekers
turned to alternative market infrastructures that were able to provide direct, disin-
termediated credit-lending relationships for households and businesses without the
need of a single point of control (or failure).
1
The Internet of Things describes the a concept where physical devices are connected to the
Internet and are able to identify themselves and exchange data.
Classication of Crowdfunding in the Financial System 7
any resource (services, creative content, funds, etc.) from a large group that is
typically online. The term crowdfunding was rst coined in 2006 by Michael
Sullivan on Fundavlog, his video blogging project.
The actors associated with crowdfunding fall into three main roles: (i) the
borrower or project initiator who presents her credit request or idea/project to be
funded; (ii) individuals or groups (i.e., the crowd) who support the funding request;
and (iii) a moderating organization (i.e., the platform) that brings the parties
together to launch the idea or support the borrowing request.
The literature distinguishes between (i) lending-based crowdfunding, which
consists of loans which are repaid with interest, (ii) equity-based crowdfunding in
which investors receive shares of the startup company, (iii) reward-based crowd-
funding that involves rewarding funders with a product that has actual monetary
value, often an early version of the product or service being funded, and (iv) do-
nation-based crowdfunding in which backers donate funds because they believe in
the cause (Cholakova and Clarysse 2015).
As pointed out by Everett (2008), lending-based crowdfunding is a
technology-enabled form of social lending. Indeed, the advent of modern social
lending is attributed to the English Friendly Societies of the 18th and 19th century
that arose spontaneously during the Industrial Revolution as clubs that helped their
members pool resources and risk. The Friendly Societies allowed members to make
deposits and receive loans, and also assisted family members in the case of negative
shocks such as illness. What was a locally bounded phenomenon in the past has
become nowadays a spatially unbounded opportunity to connect with socially
inclined or prot oriented, mostly anonymous, individuals. Besides, one of the
biggest challenges, accurate risk assessment, was facilitated with technological
advances. Friendly Societies had little experience in risk management and about
one third of them had failed in the 19th century (Covello and Mumpower 1986). An
online platform, on the other hand, is not exposed to idiosyncratic risk of its
borrowers per se but it provides the necessary tools to investors for controlling their
risk exposure by (a) collecting, scoring, and disseminating credit qualications for a
pool of prospective borrowers, (b) the real-time reporting supply of lending bids,
allowing investors to diversify across loans and spreading borrower risk across
investors, and (c) the online servicing, monitoring, and credit history reporting of
loan performance.
The equity-based model is a valuable alternative source of funding for entre-
preneurs as the crowd takes the role of traditional investors in startups, such as
business angels and venture capitalists. The project initiatives involve equity shares,
revenue, or prot sharing with the funders.
In contrast to lending- and equity-based crowdfunding, the donation- and
reward-based models do not guarantee a payoff to funders. Projects of this kind tend
to raise smaller amounts of capital than those with equity participation. Still, both
models experienced high popularity among backers. This might seem unreasonable
since nancial reward is practically non-existent and one might assume that project
initiators depend solely on the goodwill of potential backers. This is not necessarily
true as pointed out by Schwartz (2015). Funders can be incentivised to donate by
8 L. Pelizzon et al.
experiencing a non-nancial value while doing so. Their intrinsic motivation might
be driven by factors such as personal entertainment, political expression, arts
patronage, altruism, being part of a community, or having a feeling of being a
creator.
Despite the growing popularity of the latter two models, it is mostly P2P lending
and equity-based crowdfunding that pose a potential threat to the business models
of traditional nancial institutions. Consequently, the focus of this survey lies
especially on these two models.
2
Source: Crowdsourcing.org; Massolution.
3
Source: Morgan Stanley Research.
4
Source: Fitch Ratings. https://www.tchratings.com/gws/en/tchwire/tchwirearticle/P2P-
Lending's-Success?pr_id=851174.
Classication of Crowdfunding in the Financial System 9
Theoretical and empirical results show that traditional banks have little incentive
for screening small borrowers and practically they invest little effort in doing this.
Iyer et al. (2010) nd that the screening process in P2P markets incorporates soft,
i.e. non-standard, information. They point out that lenders are able to infer one-third
of the information regarding borrowers credit score by utilizing such information
beneting in particular small borrowers. Since traditional lenders use only hard,
standard information on estimating creditworthiness, they argue that Prosper, a
lending platform in the US, acts like a complementary lending institution that
improves small borrowers overall credit access. On the negative side, not all
lenders have nancial and screening expertise giving a comparative advantage to
institutional investors over individual investors in selecting protable loans. Butler
et al. (2010) reports that borrowers with relatively better access to traditional bank
nancing are willing to borrow at a lower rate at Prosper. This suggests that P2P
markets add to overall credit supply efciency.
Morse (2015) points out that the main driver of the crowdfunding disrupting
force is the increasing role of big data. Data analysis has become a crucial part in
business relations and an integral component of social network businesses. Despite
the fact that big data brings forth also all sorts of uncertainties such as privacy,
monopoly power, or discrimination, P2P platforms might be able to offer pricing
and access benets to potential borrowers if they manage to unearth soft infor-
mation not accessed or used by intermediated nance.
By considering all the above elements, if asked whether crowdfunding has the
possibility to positively disrupt consumer nance, it seems that this is potentially
the case. Due to the complexity of some businesses (e.g., collateralized loans
requiring repossessions and foreclosures, and long maturity lending without forcing
mechanisms), this will probably be not the case across all markets.
less likely to get a loan as opposed to white. They conclude that the way borrowers
present themselves affects the likelihood of getting a loan and more favorable loan
terms. Overall, beauty seems to be related to taste-based discrimination while
blacks are subjected to statistical discrimination.
Successful loan funding also appears to be related to various signals of trust-
worthiness. Duarte et al. (2012) nds that borrowers who appear to be more
trustworthy have a higher likelihood of getting loan and being charged a relatively
lower interest rate. However, trustworthy-looking borrowers, in fact, default at a
lower rate and have a relatively better credit rating. Freedman and Jin (2014)
observe that also having a social network is benecial for borrowers as it increases
the probability of being funded and lowers the interest rate on the loan. According
to Hildebrand et al. (2010), group leaders, who are rewarded for successful loan
listings, have an incentive to signal borrower quality to lenders. This alleviates
information asymmetries that can be mitigated if group leaders invest a substantial
amount in the loans themselves.
Studies show that some investors do not process all available information
optimally. Gelman (2013) nds that small investors, in particular, ignore valuable
borrower information that is conveyed in a borrowers loan verication status on
Lending Club. Thus, such investors show risk seeking behavior while professional
investors act more rationally and in a more risk averse manner. Furthermore,
Freedman and Jin (2014) nd that lenders on Prosper do not understand the relation
between social ties and unobserved borrower quality. Some borrowers use their
social network to their advantage of getting the best deal. Lenders learn about such
gaming behavior from their investment mistakes only gradually over time and
adjust slowly. Contrary to this nding, Lin et al. (2009) observes that friendships of
borrowers signal credit quality to lenders.
Mach et al. (2014) show that small business applications are more than twice as
likely to be funded than other loans. Berger and Gleisner (2014) observe that
market participants who were paid to act as intermediaries on Prosper and screen
loan listings had a positive impact on lowering borrowers credit spreads by
reducing information asymmetries.
There is also presence of herding behavior among lenders. Zhang and Liu
(2012), Herzenstein et al. (2011) and Ceyhan et al. (2011) observe that bids for a
single loan do not occur uniformly over time. In particular, bids are concentrated at
the end of a listings lifetime and tend to be more concentrated for listings that are
close to being fully funded.
From a more theoretical perspective, Paravisini et al. (2009) estimate investors
risk preference parameters and their elasticity to wealth. They nd that wealthier
investors exhibit lower absolute risk aversion and higher relative risk aversion and
that for a given investor, the relative risk aversion increases after experiencing a
negative wealth shock.
To sum up, despite some inefciencies observed by researchers, P2P lending
markets overall positively affect credit supply to individuals.
Classication of Crowdfunding in the Financial System 11
5
Financial Conduct Authority (2016, April 6). The FCAs regulatory approach to crowdfunding
over the internet, and the promotion of non-readily realisable securities by other media. Retrieved
from http://www.fca.org.uk/static/documents/policy-statements/ps14-04.pdf.
12 L. Pelizzon et al.
Funding From the funding side there are many factors that could influence the
performance of equity crowdfunding. Compared to venture capital funding, which
is lead by professional experts, the influential factors of equity crowdfunding could
be detrimental when funding decisions are taken by small investors without a strong
nancial background. An empirical examination in this eld is applied by Ahlers
et al. (2015). After having investigated 104 equity crowdfunding offerings pub-
lished on ASSOB (one of the largest equity-based crowdfunding platform), the
authors present several key factors that could lead to an investment bias. Namely,
factors that are not necessarily linked to performance but that are instead perceived
as such by the investors: the quantity of the board members, the levels of members,
education, their professional network, the clarication for the exit scenario (IPO, or
trade sale) and the time that the rm has been in the business (experience).
Investment As for as investment is concerned, the valuation of a startup is the great
challenge, especially when it comes to small investors. In donation-based crowd-
funding, the pricing problem does not exist at all, as the motivation for donation is
not based on nancial return. For lending-based crowdfunding, investors could
receive their interest periodically, thus the pricing model could at least refer to
Discounted Cash Flow techniques. But when it comes to equity crowdfunding,
there does not exist an unassailable text-book model. Usually, the valuation could
be either based on the asset value, on the expected cash flow (or return) or a mix of
both. In terms of asset valuation, for startups in early-stage, the most important asset
is probably the intellectual property, which is intangible and therefore subjected to
an arbitrary valuation. On the other hand, the forthcoming expected return could
also be of great uncertainty. Indeed, it is very common to happen that no cash flow
is generated in the rst 57 years for a seed or early-stage company. If any, it would
anyway be reinvested into the business again. So, investors generally do not have a
sufcient set of track-records to use in order to extrapolate future cash flows or
returns on investment (Wilson and Testoni 2014). And due to information asym-
metries, entrepreneurs and investors probably have a different view on equity
pricing because they have a different information set. In fact, the information
asymmetry problem is hardly avoided especially for startups still in their seed stage.
There exists a tension in equity crowdfunding (but not only) as entrepreneurs have
to bear the risk to disclose more business details to the crowd but at the same time
they need to protect their ideas and business strategies that could be copied easily
by other companies. In this eld Innovestment, a German crowdfunding platform,
provides an innovative solution. In Innovestment, pricing of equity is based on
auction. Investors bid for the equity of a startup according to their own internal
valuation and entrepreneurs can at the end decide whether to accept or refuse the
funding amount.
Regulations Investment in seed-stage companies is essentially a high-risk activity
because, as presented above, it deserves some level of competence. Indeed,
according to Zhang et al. (2014), the majority of investors are professionals or
high-net-worth individuals. Thus, governments tend to be very cautious with regard
to regulation of retail equity crowdfunding. Although still in evolution, in the
Classication of Crowdfunding in the Financial System 13
following, we briefly present the status of the legislation for some of the biggest
crowdfunding markets. In the US, for a long time equity-based crowdfunding has
only been opened to accredited investors. According to the Security and Exchange
Commission an accredited investor, in the context of a natural person, includes
anyone who earned income in excess of USD 200,000 in each of the prior two
years, or has a net worth over USD 1 million. This restriction is expected to be
lifted up soon. However, in October 2015, the SEC approved the Title III of the
JOBS Act, which will allow non-accredited investors to invest in equity-based
crowdfunding. When the rules will come into effect, the US equity crowdfunding
market will be open to all citizens. Also in UK, equity crowdfunding is considered a
risky investment. It is fully monitored and regulated by the Financial Conduct
Authority which considers any share in equity-based crowdfunding as a non-readily
realizable security. In general, the market is only open to some qualied investors
whose wealth or income has surpassed a certain pre-dened standard. According to
a rule approved in 2014, retail investors and normal citizens must explicitly conrm
that they will not invest more than 10 % of their net investable assets in equity
crowdfunding products. In other EU countries, the investment environment is rel-
atively loose. In July 2013, Italy, became the rst country in Europe to implement a
complete retail equity crowdfunding regulation. After few months, in reviewing
existing rules, Italy enlarged the category of suitable crowdfunding target compa-
nies. Now, it is no longer limited only to startups but it is extended and applied to a
broader denition, provided that crowdfunding companies are innovating and
launching new products. In Germany equity crowdfunding has been legal for years
but only limited to silent partnership, which means investors could only share the
prot but have no voting rights. In France, equity crowdfunding is also allowed but
the regulation places some constraints. For example, crowdfunding platforms need
to maintain a minimum capital requirement of EUR 730,000.
Looking at the past, it becomes clear that regulators are willing to facilitate the
flow of capital between market participants. However, most countries are still in the
ongoing process of dening an appropriate legal framework for the crowdfunding
segment.
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Author Biographies
1 Introduction
Akerlofs (1970) seminal lemons problem epitomizes the key challenge faced by
any investor: how to select projects from a pool of opaque applicants. Traditionally,
banks help resolve the information asymmetry between savers and investors by
developing screening competences and acting as delegated monitors (Diamond
1984). But dramatically reduced transaction and information acquisition costs,
together with historically low interest rates, impede banks incentives to engage in
D. Blaseg
Goethe-University Frankfurt, Theodor-W.-Adorno-Platz 4, 60323 Frankfurt, Germany
e-mail: blaseg@wiwi.uni-frankfurt.de
M. Koetter ()
Frankfurt School of Finance and Management, Deutsche Bundesbank,
and IWH, Sonnemannstr. 9-11, 60314 Frankfurt, Germany
e-mail: m.koetter@fs.de
costly information generation, which can lead to the contraction of credit (Puri et al.
2011; Jimnez et al. 2012) or misallocated funding to too risky projects
(DellAriccia and Marquez 2004; Jimnez et al. 2014). Against this backdrop,
recent studies by Belleflamme et al. (2013) and Mollick (2014) hypothesize that
crowdfunding may rival bank nance and connect even small savers with risky new
ventures that face traditionally tighter nancing constraints (e.g., Cassar 2004;
Robb and Robinson 2014).
We test whether the wisdom-of-the-(investor)crowd becomes a more likely
substitute for bank credit as a major source of funding for new ventures if young
ventures banks are shocked. We construct a novel, hand-collected data set of
ventures uses of equity crowdfunding in Germany, their relationships with banks,
and various venture traits since 2011. By observing venture-bank relationships, we
can identify if ventures connected to shocked banks are more likely to use
crowdfunding in an attempt to substitute for contracting bank credit supply. In so
doing, we move beyond the important descriptive evidence in this nascent strand of
literature, which does not permit inferences about the causal effects of the deter-
minants of crowdfunding.1
We also control for observable management and venture traits to determine if
more opaque ventures with greater information asymmetries are more likely to use
crowdfunding as an alternative source of nancing. Greater information asymmetries
increase capital costs, which implies a well-known pecking order of capital structure:
Internal funds are preferred over debt, and equity is a last resort of funding (Jensen
and Meckling 1976; Myers and Majluf 1984). To mitigate information asymmetries
and facilitate the efcient allocation of nancial resources, from savers to productive
investors, nancial intermediaries can generate private information by establishing
close and long-term relationships (Rajan 1992; Uchida et al. 2012). But relationship
lending is costly, so banks may turn down funding requests by promising, yet
hard-to-assess projects such as new ventures if they cannot condently cover the
costs associated with producing necessary private information (Rajan 1992; Petersen
and Rajan 1994, 2002). In this setting, we investigate if ventures tied to banks that
struggle to cover the costs of private information generation are more likely to tap a
potentially less-than-wise crowd as a funding source.
The nancial crisis of 2008 amplied the generally prevalent challenges that young
and small ventures confront when trying to raise external nance. In the aftermath of
the great nancial crisis, the number and volume of equity nancing rounds from
venture capital sources declined signicantly (Block et al. 2010), credit supply
tightened in the Eurozone (Hempell and Kok 2010), and in Germany, even local
lenders reduced their loans (Puri et al. 2011). Gorman and Sahlman (1989) and Cassar
(2004) caution that credit supply shocks are especially important for new ventures.
However, most existing empirical evidence is geared toward venture capitalist
1
Recent policy (e.g., De Buysere et al. 2014), and academic (e.g., Mollick 2014; Schwienbacher
2013; Hornuf and Schwienbacher 2014), light on the potential role of crowdfunding and vividly
illustrate the broadening interest in this new form of nancing ventures. We instead seek to provide
empirical evidence about the causal effects of bank credit crunches.
Crowdfunding and Bank Stress 19
Fig. 1 Sample of new ventures that apply for crowdfunding or not. Notes This gure shows the
sample of ventures that applied successfully to one of the six largest equity crowdfunding
platforms in Germany for funds between 2011 and 2014. Out of 157 applicants, 133 ventures
successfully completed their funding request by obtaining the requested minimum amount, 24
applying ventures were not successfully in terms of raising the the requested minimum amount,
and 200 ventures did not apply at all. Some ventures applied multiple times for funding. The data
on non-applicants is obtained from the German Federal Association of Startups. The data about
crowdfunding applicants were collected from observing applicant data directly in the online
platforms maintained by Bankless24, Berfuerst, Companisto, Fundsters, Innovestment, Mashup
Finance, Seedmatch, and others
funding (for an overview, see Gompers and Lerner 2001). The ability of crowdfunding
to substitute for bank credit or other sources of external nance, due to its signicantly
lower transaction costs in the Internet age, in particular remains unclear.
This research gap exists primarily because of the absence of data. We
hand-collected a sample of all the ventures that applied for funds on major German
equity crowdfunding platforms since 2011. That is, among 357 new ventures for
which we have data, 157 applied for equity crowdfunding at one of the six major
German online platforms between November 2011 and June 2014, which cover
95 % of the total market in terms of offerings and 99 % in terms of volume.
Figure 1 illustrates the structure of the sample and the main specications that
explain the odds that a venture apply for external funding on a crowdfunding
platform conditional on its bank relationship and venture and management traits.
We manually gathered the data for the crowdfunding ventures from each plat-
form webpage and database. For the 200 ventures that did not use crowdfunding,
we obtained the venture and management variables from the membership database
of the Federal Association of Startups. Thus, in contrast with previous research into
20 D. Blaseg and M. Koetter
crowdfunding (e.g., Belleflamme et al. 2013; Mollick 2014), we can estimate the
probability of tapping the wisdom of the crowdTrust and Reputation, conditional
on venture and managerial traits, relative to a relevant comparison group of com-
parable young ventures that face similar nancing constraints.
Another challenge that plagues empirical literature pertaining to the role of
crowdfunding is the notorious unobservability of the arguably most important
competing source of external nance: bank credit. Because we collect information
about each ventures bank relationship, we can exploit the heterogeneity in bank
distress in the aftermath of the nancial crisis and identify credit supply shocks to
ventures, according to the health of their main external nancier. To our knowl-
edge, this article is the rst to seek to identify the effect of bank stress on alternative
forms of external nance directly.
In total, we identify 82 banks connected to the new ventures in our sample and
specify ve alternative indicators of stressed relationship lenders. The main indi-
cator is whether a bank received capital support from the German Special Fund for
Financial Market Stabilization (SoFFin), which came into effect as of 2008. With
an alternative approach, we also classify banks as stressed if they report an existing
restructuring plan, according to the comprehensive assessment conducted by the
European Banking Authority (EBA) in November 2014, and whether a regional
savings bank belongs to a stressed Landesbank in 2008 (see Puri et al. 2011).
The main results show that ties to a bank bailed out by the SoFFin increase the
probability that the venture taps a crowdfunding platforms by 18 %. The probability
of successfully completing a crowdfunding request increases by 22 % tough, so the
successful completion of a crowdfunding request (the left branch in Fig. 1) does not
appear to depend on the indicators of bank distress. That is, credit supply shocks
determine the choice to seek alternative funding forms, but they do not necessarily
discriminate between projects that can or cannot convince the crowd. The positive
effect of crunched banks the use of crowdfunding remains statistically and eco-
nomically signicant, even when we control directly for bank nancial proles.
Alternative indicators of bank distress, and especially the existence of restructuring
plans shared with the EBA, yield qualitatively similar results, though with weaker
statistical signicance. Regarding other venture and management traits, we nd that
the likelihood of using crowdfunding is signicantly larger for ventures that exhibit
lower ratings, are smaller, and have fewer tangible assets. This result may indicate
that ventures with greater information asymmetry suffer the most from a credit
supply shock, and therefore seek crowdfunding as an alternative. Whether these
projects are more likely to be lemons or gems that have been neglected by banks is
an important question for further research.
The remainder of this article is organized as follows: Sect. 2 relates our study to
prior literature and provides an institutional background of equity crowdfunding in
Germany. In Sect. 3, we present and discuss crowdfunding data, as well as our
identication strategy for bank-venture relationships. We discuss the empirical
ndings in Sect. 4 and conclude in Sect. 5.
Crowdfunding and Bank Stress 21
Banks are vital to resolve information asymmetries, especially those that plague
small and medium enterprises (e.g., Petersen and Rajan 1994, 2002; Berger and
Udell 1998). The quality of opaque new ventures is difcult for investors to evaluate
and information asymmetries always exist during external, early stage nancing (see
Jensen and Meckling 1976; Stiglitz and Weiss 1981; de Meza and Webb 1987).
Information asymmetries between ventures and possible investors result in the
well-known pecking order of capital (Myers and Majluf 1984), such that ventures
prefer to nance new projects with retained earnings or other internal cash flows,
because external funds are more expensive. External debt nancing is favored over
equity, because the latter dilutes the ownership of the entrepreneur. Robb and
Robinson (2014) use the Kauffman Firm Surveys to document the important role of
debt at the beginning of a ventures life and suggest that the largest part of total
capital comes from outside debt, followed by owners equity, then insider debt,
outside equity, and nally owner debt. Brown et al. (2012) also note the important
role for bank debt as a source of funding for new ventures in Germany.
The nancial crisis aggravated the nancing challenges faced by young ventures
during and after 2008 (e.g., Popov and Udell 2012; Jimnez et al. 2012). Puri et al.
(2011) document a credit supply crunch among German local lenders and Hempell
and Kok (2010) identify a signicant bank lending contraction in Germany from the
ECB lending survey. Considering the important role of debt use in entrepreneurial
nancing, we conjecture that banks transmitting a credit shock may cause the young
ventures connected to them to grow more inclined to nd new sources of funding,
especially if small nancing volumes imply high relative transaction costs that are
unattractive to large-scale investors (Titman and Wessels 1988; Robb and Robinson
2014).
A novel way to reduce transaction costs in entrepreneurial nancing is crowd-
funding. Schwienbacher and Larralde (2010) provide an overview of nascent equity
crowdfunding literature in relation to entrepreneurial nance, in which they discuss
why founders choose this source of funding. Hornuf and Schwienbacher (2014) and
Mollick (2013) compare crowdfunding to different entrepreneurial nancing
options. Hemer (2011) emphasizes that the funding process itself is the decisive
difference, because entrepreneurs make an open call for funding on a crowd-
funding platform, and investors make their decisions based on the information
provided therein. Moreover, the crowdfunding platform facilitates the transaction
by providing a standardized investment contract and settling the payments.
Bradford (2012) denes equity crowdfunding as a scenario in which supporters or
investors receive a stake in the ventures they fund, in the form of prot participation
or straight equity. We similarly dene equity crowdfunding as a source of funds,
obtained when an entrepreneur sells equity shares of a company to a group of
(small) investors through an open call for funding on Internet-based platforms.
22 D. Blaseg and M. Koetter
3.1 Sampling
Fig. 2 Denitions of stressed Banks. Notes This gure presents the 82 banks in the sample listed
in Table 9 that are connected to the 357 ventures shown in Fig. 1. The link between ventures and
banks is collected from the Creditreform database. The base line identication denes stressed
banks as those that received equity support from the SoFFin. Next, we also dene banks as
stressed if they had, according to the comprehensive assessment by the European Banking
Authority (EBA) of 2014, a restructuring plan in place since before 2013. We distinguish between
banks assessed directly by the EBA (6) and those that were connected to a bank holding company
that was assessed. Finally, we consider all those regional savings banks that were connected to a
Landesbank distressed, because their responsible bank holding company was exposed to the U.S.
subprime market shock (Puri et al. 2011)
We matched the bank names from the Creditreform database with public
information about which banks were supported by the SoFFin. However, ventures
may self-select into bank relationships depending on the health of that bank. For
example, participating in the SoFFin support program may induce certain entre-
preneurs to avoid seeking credit from such a bank.
Therefore, we also dene stressed banks by using the comprehensive assessment
by the European Banking Authority (EBA) that took place in November 2014,
which is after we observe the crowdfunding choices of new ventures in this sample.
The assessment by the EBA cannot by itself indicate credit supply strain; rather, it
offers a testimony of systemic relevance. Our used EBA based measure of stress is
therefore whether a bank had a restructuring plan in place before 2013. As illus-
trated in Fig. 2, we distinguish generally between banks assessed directly by the
EBA and those connected to a bank holding company that was assessed. Finally,
we consider any regional savings banks connected to a Landesbank distressed,
because their responsible bank holding company was exposed to the US subprime
market shock (Puri et al. 2011).
We also follow Berger and Udell (2004) and calculate CAMEL (i.e., capital,
asset quality, management quality, and liquidity) covariates for every bank, which
we use as proxies for its nancial health. Table 2 offers an overview of the
26
Gender 1.449 0.777 1.286 0.667 0.164 Yes 1.081 0.351 1.000 0.000 0.081** No 0.083
City 0.638 0.484 0.857 0.355 ** No 0.742 0.439 0.810 0.402 0.068 Yes 0.152
0.219
Heads 1.464 0.655 1.629 0.843 0.165 Yes 1.653 0.722 1.667 0.796 0.013 Yes 0.151
Rating 3.275 1.235 2.486 1.337 0.790* Yes 3.419 1.362 3.381 1.396 0.038 Yes 0.751*
Scholarship 0.203 0.405 0.200 0.406 0.003 Yes 0.218 0.414 0.143 0.359 0.075 Yes 0.072
Crowdfunding characteristics
CF min. amount 69,936 116,214 53,164 20,022 16,771 Yes
CF max. amount 271,052 434,322 272,857 495,471 1,805.0 Yes
CF realized 216,295 385,257 233,773 498,250 17,478.1 Yes
amount
CF Success 0.797 0.405 0.914 0.284 0.117* No
Number of CF 289.672 328.759 315.000 337.048 25.33 Yes
investors
Firm valuation 2,253,699 2,719,899 1,907,944 1,131,583 345,754 No
before CF
(continued)
29
30
Table 3 (continued)
Crowdfunding Yes No
SoFFin Yes No Yes No
Mean SD Mean SD Difference Equal Mean SD Mean SD Difference Equal Diff-in-Diff
in means variances in means variances
Bank characteristics
Capital 0.049 0.023 0.030 0.002 0.019*** No 0.051 0.040 0.029 0.000 0.0216*** No 0.003
Asset quality 0.002 0.004 0.008 0.001 *** No 0.004 0.012 0.008 0.000 0.004 Yes 0.001
0.006
Management 0.726 0.085 0.747 0.074 0.021 Yes 0.772 0.387 0.734 0.000 0.038 Yes 0.058
Earnings 0.047 0.025 0.027 0.030 0.074*** Yes 0.044 0.021 0.022 0.000 0.066*** No 0.009
Liquidity 0.386 0.326 0.418 0.054 0.032 No 0.427 0.340 0.428 0.000 0.001 No 0.031
Sec./ear. assets 0.427 0.204 0.525 0.038 0.097*** No 0.414 0.213 0.531 0.000 0.117*** No 0.020
Fees/interest 0.414 0.210 0.501 0.095 0.087*** No 0.425 0.218 0.517 0.000 0.093*** No 0.005
Observations 69 35 124 21
Notes Descriptive statistics for the outcome of the equity crowdfunding offerings, characteristics of the ventures, and bank characteristics over the period 20112014 in Germany
on the venture level, separated by the SoFFin indicator. The sample includes all ventures with no missing values. For each variable, the table presents the mean, standard deviation,
5th percentile, 95th percentile, difference-in-means, and difference-in-differences. A offering is successful when the realized amount is larger than the minimum amount requested.
Monetary variables are in thousands of EUR
D. Blaseg and M. Koetter
Crowdfunding and Bank Stress 31
Table 4 contains the descriptive statistics for our main test variable, an indicator
variable (sofn) that takes a value of 1 if the bank is supported and 0 otherwise.
In total, 24 % of all ventures in the sample have a relationship to a bank supported
by the SoFFin. However, the share of companies whose bank is supported by the
SoFFin is 37 % among the group of ventures that used crowdfundingmore than
twice the share of the group of ventures that did not use crowdfunding (15 %).
A venture facing larger credit constraints thus appeared more likely to apply for
crowdfunding, after we control for several venture traits, as we discuss shortly.
We predict the likelihood that a venture i applies successfully for crowdfunding
yi = 1, conditional on venture traits xi and whether it is tied to a bank that was bailed
out by the soffini . We use a logit model as a baseline specication and estimate2:
exp + x
Pry = 1jx = 1
1 + exp + x
In addition to our main variable to test for SoFFin support, we added the
covariates described in Table 10 and summarized in Table 3 step-by-step. Table 5
contains the marginal effects of the baseline logit regression model to explain
crowdfunding.
A range of goodness-of-t indicators, the Pseudo R2 , and Nagelkerkes R2
support the good discriminatory power of the model, despite the relatively low
sample size (Hosmer and Lemeshow 2012). We also compare the predicted prob-
abilities against a moving average of the proportion of cases using a locally
weighted scatterplot smoothing graph, which conrms the t of the model. Like-
wise, the area under the receiver operating characteristic curve (AURROC) of
0.84 for Column 7 in Table 5 strongly indicates that the probability of using
crowdfunding is explained quite well by the covariates.
The comparison of the coefcients across ordinary least squares, logit, and probit
models tells a qualitatively similar story about the impact of a regressor on the
probability of crowdfunding. Robust estimation procedures are qualitatively simi-
lar, mitigating potential misspecication concerns. Henceforth, we report the results
from the logit regressions.
The marginal effect of the main variable of interest shows that the likelihood of
applying for crowdfunding increases when a ventures bank is supported by the
SoFFin. The marginal effect is positive and statistically signicant in all models.
2
We also tested the robustness of all reported results towards using a linear probability model using
OLS, which conrms all reported results.
32
Economically, the effect in column (7) is also important. If a new venture is con-
nected to a bank supported by the SoFFin, the probability that it applies for
crowdfunding increases by 17.5 %. Against the backdrop of an unconditional
probability to apply for funds of 43.9 % (=157/357), this effect is large.
These results support the hypothesis that young ventures are more likely to tap
innovative, alternative sources of external funding, especially then when their
conventional providers of credit are stressed. To assess whether this result is driven
by observable traits related to the degree of information asymmetries and the quality
of the venture, we discuss individual control variables next.
34 D. Blaseg and M. Koetter
Credit scores are a common tool that banks use to evaluate ventures loan appli-
cations, but it is unclear if these ratings affect the availability of debt for young
ventures. Robb and Robinson (2014) explore this question with U.S. data from the
Kauffman Survey, and observe that information about the ventures past payment
behavior can have a negative effect on access to nance among young ventures.
Brown et al. (2012) conrm this view and suggest that information provided by an
external credit agency can affect the availability of nancing for young ventures;
ventures with a good rating have better chances of obtaining a loan, whereas
ventures with bad ratings face difculties getting a loan. In line with prior literature,
we expect that ventures with bad credit scores are more likely to use crowdfunding.
External credit ratings provided by Buergel range from A (good) to C (bad). The
underlying variable (credit) is coded accordingly, such that rating class A takes a
value of 1, indicating that the business relation is approved; rating class B is
coded 2, which covers approvable business relations and class C is coded with
3, or a bad rating, which means that the business relation is a matter of trust or
discretion. Buergel is one of the largest databases on German companies, with more
than 3.9 million entries. With BoniCheck, a product of Euler Hermes, it offers an
instrument for assessing ventures solvency. From the Buergel database, we
deduced whether an external credit rating, in the form of the BoniCheck indicator,
was provided for each venture and, if so, what that rating was. Similar to the credit
scores provided by Creditreform or Dun and Bradstreet, the BoniCheck relies on
past payment behavior, relative to trade credit from utilities and suppliers. This
information is complemented by Buergels subjective assessment of the ventures
future ability to fulll credit obligations, derived from information about the ven-
tures order situation or industry (Brown et al. 2012).
The distribution of good, fair, and bad credit scores is comparable within both
groups, exhibiting a total mean of 1.88, or a fair score on average. The estimated
marginal effect of credit ratings is signicantly positive in all models. A bad credit
rating increases the probability of using crowdfunding by 31.2 % compared with
ventures that have a fair rating.
4.1.2 Size
The decision to nance a venture is based on many factors. Larger ventures can use
economies of scale to reduce information asymmetries, but they also have access
with different sources of nancing, because their risk exposure and the scale of
transaction costs differ. They often own more pledgeable collateral and have more
diverse cash flows. Small ventures instead are informationally more opaque. Thus,
size is an important choice factor when it comes to nancing young ventures
(Berger and Udell 1998). Small ventures often struggle to resolve informational
asymmetries with investors and lenders at acceptable costs, and they therefore are
exposed to higher charges for smaller amounts of capital. Transaction costs also
Crowdfunding and Bank Stress 35
influence funding methods. Small amounts often incur relatively high transaction
costs, which is why some available sources for certain kinds of ventures are not
relevant (Titman and Wessels 1988). For example, the public issues of equity shares
during an initial public offering requires a scale that most small companies cannot
reach in their early stages, so small ventures are excluded from this type of
nancing (Cassar 2004).
In summary, smaller ventures often face problems obtaining traditional sources
of outside nancing, which could influence their use of crowdfunding. Empirical
studies generally propose a positive link between venture size and outside nanc-
ing, leverage, and bank nancing (Coleman 2000; Cosh et al. 2009). Therefore, we
expect that smaller ventures are more likely to use crowdfunding than large ones.
The mean size (log of total assets) of the sample ventures is 11.78. Ventures that
made no use of crowdfunding are larger in terms of total assets, with a log of 12.35
(EUR 230.000), than ventures that use of crowdfunding, whose logged size was
10.99 (EUR 60.000). We specify the log of assets to measure size so that we can
mitigate the influence of outliers in the skewed size distribution.3
The coefcient for size is negative and statistically signicant in all models. In
line with the expected effect, the coefcient estimate indicates that smaller ventures
are more likely to use crowdfunding; a greater size, in terms of logged total assets,
decreases the probability per unit change by 8 %.
4.1.3 Tangibility
Another trait related to nancing, particularly for young ventures, is the structure of
their assets (Cassar 2004). In case a bankruptcy occurs, the nancial loss for
investors can be reduced if the assets are more tangible and generic (Harris and
Raviv 1991; Titman and Wessels 1988). Moreover, the adverse selection and moral
hazard costs should decrease when ventures pledge assets as collateral or charges
get xed on the tangible assets. Tangible assets increase liquidation value, so
companies with a higher share of tangible assets should gain access to traditional
sources of nance more easily. The lower costs of nancing then tend to result in a
higher degree of leverage in the capital structure of these ventures. Empirical
evidence suggests that banks base their nancing decision, to a certain degree on
whether they can hedge the loan with tangible assets (Berger and Udell 1998;
Storey 1994). Considering the substantial information asymmetries at the beginning
of a ventures life cycle and the information needed to forecast future development,
investors have relatively few ways to reduce their risk exposure, other than rela-
tionship banking. The asset structure, in terms of the share of tangible assets, often
serves as a screening tool for banks, such that it has signicant effects on nancing
at the beginning of a venture (Cassar 2004). Consistent with theoretical predictions,
some authors suggest a positive relationship between the share of tangible assets
3
Alternative treatments of the outliers, such as winsorizing, did not alter our results qualitatively.
36 D. Blaseg and M. Koetter
and leverage for large ventures, but research pertaining to small ventures is rare,
with a just a little evidence of a relationship between the asset structure and the use
of debt (e.g. Michaelas et al. 1999). Nevertheless, we expect that the lower the share
of tangible assets of a venture, the higher the likelihood of using crowdfunding.
To calculate the asset structure of each venture for every year since its foun-
dation, we divided the non-current assets by total assets, then take the average of
these values to dene the variable (tangibility), ranging from 0 to 1. For the
entire sample, tangible assets constitute around 15 % of the total assets of the
ventures, but among ventures that did not use crowdfunding, the average tangible
assets were greater 18% than it was for ventures that used crowdfunding (10 %).
The coefcients for the tangibility variable also were negative in all models and
signicantly different from zero. Therefore, ventures with a lower share of tangible
assets appear to have a higher probability of using crowdfunding. A 1% decrease in
the share of tangible assets increases the probability of using crowdfunding by
about 0.4 %.
Financial ratios and external ratings alone cannot explain the nancing decisions of
new ventures. Regarding young ventures in particular, many investors include the
owner or management team in their assessment, because their importance during
the rst years of operations cannot be underestimated (Cassar 2004). For example,
due to credit discrimination or the risk aversion of some nanciers, the gender
composition of the management team can influence the capital structure (Coleman
2000). Arenius and Autio (2006) provide evidence that female-owned businesses
are often nanced differently than male-owned businesses. Other authors suggest
that female-owned ventures have worse initial economic conditions, with a lower
capital base (Verheul and Thurik 2001), and they face the problem of being less
likely to obtain external funding (Coleman 2000). Furthermore, they usually use
different sources to nance their business than do male-owned ventures (Neider
1987; Lerner et al. 1997) and face particular difculties applying for and securing
bank loans (Riding and Swift 1990; Coleman 2000; Anna et al. 2000). Ventures
with mixed gender or purely female teams thus may be more likely to use
crowdfunding than ventures with a male management team.
The number of members in the management team also can affect the chances of
obtaining external capital. Chandler and Hanks (1998) show that ventures founded
and led by a team often are more successful than those founded and led by single
person. Beckman et al. (2007) nd that the number of team members and the team
composition have positive effects on the likelihood of ventures attracting external
nancing. Therefore, we posit that ventures with smaller management teams are
more likely to use crowdfunding.
To control for management team characteristics, we add the number of man-
agement team members (heads) and the gender composition of the management
team. The latter is specied as an ordinal variable (gender), with 1 indicating a
Crowdfunding and Bank Stress 37
A business plan is one of the most important steps to take when launching a
venture. In addition to providing economic efciency, it exists mainly to raise funds
to start or expand a project. Mason and Harrison (1996) thus assert that the business
plan is the minimum requirement for any nancing application, because more than
38 D. Blaseg and M. Koetter
A possible concern in our analysis is that our results could be driven by unob-
servable bank characteristics that may be correlated with the SoFFin indicator and
Crowdfunding and Bank Stress 39
subsequent lending and risk taking. The SoFFin indicator could therefore could
merely confound unobserved traits with credit supply crunch effects.
To mitigate this concern, we specied bank-level control variables in a next step,
measured as the average over the period 20092014. We included the same control
variables described previously to gauge the nancial health of banks measured
according to the CAMEL supervisory ratings system (i.e., capital, asset quality,
management quality, and liquidity). Table 6 reports the results of the baseline
model with a stepwise integration of CAMEL covariates.
The positive effect of crunched banks on the use of crowdsourced nance
indicated by support from the SoFFin, remained statistically and economically
signicant even when we controlled directly for nancial bank proles. The con-
cern that the SoFFin indicator merely confounded unobserved traits as credit supply
shocks thus was invalidated by the intact, signicant SoFFin effect. The absence of
any signicant bank-covariate effect, in turn, most likely reflects the limited
information contained by an averaged cross-section of bank data to which we are
constrained given the lack of panel rm data. Future research extending the
information about rms to longitudinal data is therefore important.
Some of the ventures were founded after the capital injections by the SoFFin, so
that our results could driven by the ventures choice of a bank supported by the
SoFFin, rather than a non-supported bank. Table 7 shows the effect of the alter-
native bank stress indicators illustrated in Fig. 2.
Column (1) replicates the baseline results with bank-specic controls. The
alternative bank stress indicators in column (2) refer to the connection of one of the
local savings banks with a stressed Landesbank, as in Puri et al. (2011). These
authors show that local savings banks restricted loan supply when they were
connected to a Landesbanken with substantial subprime exposure. We similarly
include an indicator of whether a regional savings bank in our sample belonged to a
stressed Landesbank. Although the marginal effect of the Landesbanken variable
was positive, indicating a higher probability of using crowdfunding when the
respective bank of a venture belonged to a stressed Landesbank, the coefcient was
very small and not signicant.
Next, we included the results of the EU-wide bank stress test by the EBA,
published in November 2014, because it gauges information that was not available
to ventures that might have selected banks on quality.
In column (3), we specify a more direct measure of the health of the banks tested
(direct and indirectly). Financial institutions reported, during the comprehensive
assessment in November 2014, whether they had a restructuring plan in place
before December 2013. The new ventures, sampled between 2011 and 2014, are
unlikely to have had full knowledge of such restructuring initiatives when choosing
whether to apply for crowdfunding, conditional on their existing bank relationships.
40
For the restructuring plan variable, the marginal afrmed indeed that the probability
of using crowdfunding increased by 17 %.
In summary, for the existence of restructuring plans shared with the EBA, we
found results that were qualitatively similar to those we obtained with the SoFFin
indicator.
The previous analysis indicates that ventures are more likely to use crowdfunding
when their bank is stressed. But applying for crowdfunding does not automatically
imply tthe successful completion of the funding request. Only 85 % of the ventures
in our sample were able to convince the crowd and collect the minimum requested
funding volume. Thus, the wisdom of the crowd may be just as skilled as con-
ventional intermediaries in selecting lemons out of the pool of applicants.
To test this conjecture, we differentiated between ventures that applied for
crowdfunding and those that successfully obtained crowdfunding nancing as a
function of stressed versus healthy bank relationships. With this information, we
provide more direct evidence of whether the wisdom of the (investor)crowd can
substitute for bank credit as a major funding source of new ventures if banks are
shocked.
In Table 8, we compare (1) the probability of applying for crowdfunding with
(2) the probability of successfully completing a crowdfunding request in the full
Crowdfunding and Bank Stress 43
bank distress. Thus, credit supply shocks appear to determine the choice to seek
alternative funding forms, but do not necessarily discriminate between projects that
can or cannot convince the crowd.
5 Conclusion
Appendix
Table 9 (continued)
BvD ID Bank name Bank-venture Category SoFFin Landesbank EBA direct EBA indirect
observations
13727 Sparkasse Koblenz 2 Savings
13732 Sparkasse Landshut 1 Savings Bayern LB X
13740 Sparkasse Mainz 2 Savings
13742 Sparkasse Markgraeflerland 1 Savings X
13762 Sparkasse Passau 1 Savings Bayern LB X
13803 Stadt- und Kreis-Sparkasse Darmstadt 1 Savings X
13804 Stadt- und Kreissparkasse Erlangen 3 Savings Bayern LB X
13839 Sparkasse Aachen 1 Savings West LB X
13842 Stadtsparkasse Augsburg 1 Savings Bayern LB X
13858 Sparkasse Harburg-Buxtehude 1 Savings X
13866 Stadtsparkasse Duesseldorf 3 Savings West LB X
13869 Verbundsparkasse Emsdetten Ochtrup 1 Savings West LB X
13885 Sparkasse Hannover 4 Savings X
13894 Kreissparkasse Kaiserslautern 2 Savings
13896 Kasseler Sparkasse 1 Savings X
13912 Stadtsparkasse Muenchen 7 Savings Bayern LB X
13937 Stadtsparkasse Schwerte 1 Savings West LB X
14008 Volksbank Ludwigsburg eG 1 Cooperative
14011 Volksbank Paderborn-Hoexter-Detmold 1 Cooperative
14037 Sparkasse Hoexter 1 Savings West LB X
14067 Volksbank Stuttgart 2 Cooperative
14090 Sparkasse Muelheim an der Ruhr 1 Savings West LB X
14104 Berliner Sparkasse 31 Savings X
(continued)
D. Blaseg and M. Koetter
Table 9 (continued)
BvD ID Bank name Bank-venture Category SoFFin Landesbank EBA direct EBA indirect
observations
14123 Herner Sparkasse 1 Savings West LB X
14133 Postbank 18 Private X
14166 Volksbank Mittelhessen 1 Cooperative
14199 Sparkasse Leipzig 1 Savings Sachsen LB
14469 Ostsaechsische Sparkasse Dresden 2 Savings Sachsen LB
14530 Volksbank Karlsruhe 1 Cooperative
Crowdfunding and Bank Stress
Table 9 (continued)
BvD ID Bank name Bank-venture Category SoFFin Landesbank EBA direct EBA indirect
observations
44155 VR-Bank Passau 1 Cooperative
44562 Sparkasse Bremen 1 Savings X
45341 Raiffeisenbank Heinsberg 1 Cooperative
45375 Sparkasse Herford 1 Savings West LB X
45877 Raiffeisenbank Parsberg-Velburg 1 Cooperative
46123 Volksbank Welzheim 2 Cooperative
46801 HypoVereinsbank 11 Private
47101 VR Bank Muenchen Land 1 Cooperative
47634 Volksbank Brilon-Baeren-Salzkotten 1 Cooperative
47699 Vereinigte Volksbank Maingau 1 Cooperative
47734 LBBW 2 Landesbank X
49769 Sparkasse Schaumburg 1 Savings X
49838 Volksbank Sauerland 1 Cooperative
Total Bank Observations 82 (357) 2 (87) 22 (38) 6 (207) 36 (75)
Thereof cooperative banks 27 (47)
Thereof landesbanken 1 (2)
Thereof private banks 9 (198)
Thereof savings banks 45 (110)
Notes These descriptive statistics detail the banks in the full sample. The number of bank-venture observations appear in brackets
D. Blaseg and M. Koetter
Crowdfunding and Bank Stress 49
Table 10 (continued)
Variable name Source Description Measurement
unit
Landesbanken Sparkassen-Verband Dummy variable equal to one if the Binary
bank of the venture is a savings bank
that owns holdings in one of the
affected Landesbanken (Bayern LB,
Sachsen LB, West LB)
EBA European Banking Dummy variable equal to one if the Binary
Authority bank of the venture is directly or
indirectly included in the 2014
EU-wide stress test conducted by the
European Banking Authority (EBA)
EBA direct European Banking Dummy variable equal to one if the Binary
Authority bank of the venture is directly
included in the 2014 EU-wide stress
test conducted by the European
Banking Authority (EBA)
EBA indirect European Banking Dummy variable equal to one if the Binary
Authority bank of the venture is indirectly over
holdings included in the 2014
EU-wide stress test conducted by the
European Banking Authority (EBA)
CET1 16 European Banking Fully loaded Common Equity Tier 1 %
Authority (CET1) ratio in the adverse scenario
2016
CET1 16 European Banking Difference between the CET1 ratio %
CET1 13 Authority starting 2013 and the fully loaded
CET1 ratio in the adverse scenario
2016
CET1 16 < European Banking Dummy variable equal to one if the Binary
8% Authority CET1 ratio of the tested bank is lower
than 8 % in the adverse scenario 2016
Restructuring European Banking Dummy variable equal to one if the Binary
plan Authority bank of the venture had an
restructuring plan before 2013
Bank characteristics
Capital Bankscope Proxy for capital adequacy of a %
ventures bank measured as the ratio
of total equity to total assets
Asset quality Bankscope Proxy for asset quality of a ventures %
bank measured as the ratio of loan
loss provisions to total gross loans
Management Bankscope Proxy for managerial quality of a %
ventures bank measured as the ratio
of total costs to total income
(continued)
Crowdfunding and Bank Stress 51
Table 10 (continued)
Variable name Source Description Measurement
unit
Earnings Bankscope Proxy for earnings of a ventures bank %
measured as the return on average
equity
Liquidity Bankscope Proxy for liquidity of a ventures bank %
measured as liquid assets to deposits
and short-term funding
Sec./ear. Bankscope Proxy for liquidity of a ventures bank %
assets measured as securities to total earning
assets
Fees/interest Bankscope Non-interest income divided by net %
interest income
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54 D. Blaseg and M. Koetter
Author Biographies
Susanne Chishti
Currently the largest industry in alternative nance, peer to peer lending has
experienced both headlining successes and serious challenges during its early
development. The last ve years have seen most of the main players in the UK
launch their investment platforms with a sustained customer uptake moving alter-
native nance further towards the mainstream. In 2015 the volume of P2P business
lending reached a record 1,490 m.1 It is not uncommon for P2P platforms to offer
returns of over 10 % to savers looking for better returns than are currently offered
by high street banks2 after years of record-breaking low interest rates. Borrowers
looking for loans are now able to nd new avenues and affordable rates through
P2P lending platforms.
1
http://www.nesta.org.uk/sites/default/les/pushing_boundaries_0.pdf.
2
http://www.thisismoney.co.uk/money/diyinvesting/article-3062370/The-investment-trusts-backing-
lending-platforms-10-return.html.
S. Chishti ()
FINTECH Circle, London, UK
e-mail: info@FINTECHCircle.com
3
https://www.gov.uk/government/uploads/system/uploads/attachment_data/le/467443/bpe_
2015_statistical_release.pdf.
How Peer to Peer Lending and Crowdfunding Drive 57
value and a better customer experience. Preferable rates and increased access are
not the only factors to be taken into account when looking at previous growth
gures. The ease in which interested parties can interact with these platforms, the
transparency of the deals available and the speed at which things can be achieved
are all considerations that are attracting individuals and institutions to this sector.
FinTech companies have cherry picked and developed these core banking services
and as a result lending, borrowing and investing have recently seen some of the
most signicant changes in living memory. Central to alternative nance, the
continued performance of P2P lending and crowdfunding will determine the future
of this sector.
As both of these platforms adapt to the rapidly changing landscape of nance a
wider FinTech ecosystem is developing around them. For those who can meet the
challenges ahead to support the demand for continued growth, advanced credit
scoring abilities will provide new opportunities for those who are able to assess a
wider proportion of potential borrowers. Rather than only relying on traditional
credit scoring calculations, FinTech companies are harnessing an abundance of new
information by using software developed for big data and their ability to develop
improved algorithms to automatically match lenders with borrowers. Newly
developed credit scoring models and a high level of borrower vetting have kept
Zopa and RateSetter defaults at some of the lowest rates in the lending industry,
though unlike a bank savings account there is no FSCS coverage which insures
most UK savings accounts up to 85,000.4
4
http://www.fscs.org.uk/what-we-cover/products/banks-building-societies/.
58 S. Chishti
Since 2015 the FCA has regulated P2P lending sites to ensure transparency and
that they have the funds to dampen risk exposure to lenders. Zopa has a Safeguard
fund to repay investors in the event of a borrower defaulting on their loan. Their
fund is in a trust held by a not-for-prot organisation. RateSetter was the rst to
provide a provision fund and their website states that no investor has lost a penny
since their launch in 2010. With an investment spread across multiple borrowers,
defaults at these rates become manageable with repayment funds in place. However
both of these young industries have only been operating during times of ultra low
inflation which can be seen as giving them favourable terms in comparison to their
main competitors. The limitations of the P2P industry will continue to be tested.
Lending Club in the USA has seen their CEO stand down over questionable sales
practices5 highlighting the potential dangers of a burgeoning industry driven by
investor demand for high-yielding xed income assets, while the difculties of
forecasting its performance during times of higher interest rates and inflation
becomes a crucial issue for the future.
P2P lender Funding Circle has been reported to be trebling its loan volumes to
SMEs every year.6 Founded in 2010 by Samir Dasai, Funding Circle has lent to
small businesses globally: $2 billion to more than 15,000 businesses.7 Their
business model includes the option for investors and borrowers to trade parts of an
existing loan and Funding Circle takes a 0.25 % fee on each sale.8 They were the
rst peer to peer lending site in the country to focus solely on loans to businesses
and are currently the fth largest net lender to small businesses.9
5
http://www.ft.com/cms/s/0/22559850-15d9-11e6-b197-a4af20d5575e.html#axzz48MJxuygb.
6
http://www.standard.co.uk/business/markets/funding-circles-samir-desai-after-the-banking-
cowboys-here-comes-the-new-wave-loan-arranger-9082657.html.
7
https://www.fundingcircle.com/us/about/press/.
8
https://www.fundingcircle.com/lenders/terms.
9
https://www.fundingcircle.com/blog/press/.
How Peer to Peer Lending and Crowdfunding Drive 59
2.2 Zopa
Launched in 2005 Zopa was the rst peer to peer lending site founded ve years
before most of its competitors. Founded in the UK it has a strong international
presence and is now Europes largest and oldest P2P lending organisation.10
Originally a consumer loans company Zopa have now teamed up with UBER to
create a market for drivers who would like to buy their own car. Challenger bank
Metro have also partnered with Zopa to enter into the P2P market by using the
platform to lend to customers. This could be seen as a signal to institutional lenders
and investors that alternative nance is here to stay.
2.3 RateSetter
Launched in 2010 RateSetter co-founders Peter Behrens and Rhydian Lewis have
lent over 1b to date.11 Now partnered with the British Business Bank (BBB) they
lend through RateSetter to those needing loans for business purposes. They are seen
as one of the lowest risk P2P lenders with a strict vetting policy for borrowers.
RateSetters provision fund currently stands at over 17,993,00012 and lenders can
start with as little as 10. Also typical of FinTech platforms RateSetter is a great
example of a website design and functionality that gives the user an experience
matched with the ease and simplicity of their business model.
2.4 Crowdcube
Darren Westlake and Luke Lang established the worlds rst equity crowdfunding
platform in 2011. As a platform it aims to enable anyone to buy equity in unlisted
UK registered businesses, investing as little as 10. If the business fails to raise the
set target then no funds are taken from investors. In the beginning their average
raise for a business was a little over 100,000 in their rst two years, though the
average now is around 500,000.13
10
https://en.wikipedia.org/wiki/Zopa.
11
http://www.crowdfundinsider.com/2016/01/80641-ratesetter-tops-1-billion-claims-record-pace-
for-uk-marketplace-lending/.
12
https://www.ratesetter.com/invest/everyday-account/protection.
13
http://www.wired.co.uk/news/archive/2015-07/08/crowdcube-darren-westlake-wired-money-
2015.
60 S. Chishti
2.5 Seedrs
Seedrs was founded in 2012 by Jeff Lynn and Carlos Silva as part of an MBA
project which soon went on to raise 1.3 million.14 Also based on the all or
nothing equity crowdfunding business model, Seedrs acts as single legal share-
holder on behalf of all investors in a deal (via a nominee structure). In 2015 the
combined forces of the alternative nances sector came together with the lending
site Assetz who raised 3 million by equity fundraising with Seedrs.15
2.6 SyndicateRoom
P2P lending accounts for around 90 % of the alternative nance market.18 With the
worlds rst company launching in the UK, London has continued to play a central
role with eye opening growth rates over the last 5 years. The HM Treasurys
ongoing efforts to create more competition for the banking sector has included tax
breaks and regulation favouring new entrants into the alternative nance market
who are now able to challenge the incumbents. The most successful models
14
http://www.crowdfundinsider.com/2013/12/29179-seedrs-closes-2013-high-note-3-million-
raised-december/.
15
http://www.crowdfundinsider.com/2015/04/66388-seedrs-leads-the-way-in-raising-capital-for-
other-crowdfunding-platforms/.
16
https://en.wikipedia.org/wiki/SyndicateRoom.
17
http://www.businessweekly.co.uk/tech-trail/funders/businesses-can-now-bank-diverse-range-
funding-options.
18
http://www.4thway.co.uk/news/uk-leading-the-way-on-p2p-lending/.
How Peer to Peer Lending and Crowdfunding Drive 61
developed in the P2P lending space have produced the Big Three - Zopa, Funding
Circle and RateSetter. Their new title coined by the industries press is reminiscent
of the Big Four and although maybe tongue in cheek it is a reminder of where P2P
lending is potentially heading.
The options on offer to lenders have diversied over recent years. Most com-
monly a lender is able to choose who they lend to and at a xed rate set on a
borrowers request for a loan. Also there is the option to lend via a reverse auction
for a loan where the investor offering the lowest rates to a borrower is successful. It
is also possible that borrowers can be vetted by the lender for each individual loan.
P2P lending sites can operate a marketplace lending model where lenders are
offered basic information about the loans on offer that are underwritten by the
platform itself and are then given the rate already agreed by the borrower. Similarly
the platform can package interest products from existing loans with annual rates and
the returns being paid at the end of each year rather than on a monthly basis. An
environment in which loans can be packaged, bought and sold enables a market
where lenders can cash in early but only if they can nd a buyer or are willing to
pay an early withdrawal/exit fee.
P2P lending rst became popular with unsecured consumer loans and now
includes business lending with the option to be secured by the borrowers property.
Whether secured or unsecured, this offers SME lending more flexibility to both
investor and borrower. Previously SMEs attempting to nd deals from a high street
bank were up against a lack of transparency with hidden borrowing fees to uncover
and understand, often being unexpectedly charged even after committed due dili-
gence. The peer to peer technology based lending model has harnessed data in ways
the legacy systems of banks have not been able to deliver. As a result P2P loan
applications are processed at higher speeds and with more clarity on the agreements.
With this increased access to nance SME lending has reached a pivotal moment in
banking history as P2P platforms have claimed their stake in the lending market and
now institutions notorious for being slow moving are starting to take notice.
62 S. Chishti
The foundation of P2P lending was originally built on the principle of facilitating
large groups of individuals (peers). Site owners have started to market this concept
less as new products become available that make the peer to peer title less relevant,
though this is one of the key values that separates them from their main com-
petitors. The technology that makes P2P lending work serves as a platform where
investors and businesses can interact on a scale that offers the advantages of choice
and diversity. This has driven the widely publicised success of this model and peer
to peer loans are now accepted as an asset class of their own. Institutions have had
the experience with positive results in raising funds, investing and even launching
their own P2P lending platforms. The endorsement and cash flow provided by
institutional investment has been of great benet to this developing industry but it
could be possible that if the large amount of small investors who are still driving
this phenomenal growth are overshadowed by the power of institutional share-
holders, P2P lending could potentially move towards the old models it has suc-
cessfully disrupted.
In April 2016 peer to peer investments became eligible for individual Savings
Accounts (ISAs), tax free savings vehicles for UK residents. After a consultation
that looked at potential concerns such as problems that could arise from P2P
platforms not legally owning the loans they originate, the majority of the contrib-
utors did not recognise any undue risk and now peer to peer lenders will be able to
act as ISA managers. There have been well documented issues in recent years about
loan originators not having the same interests as direct lender/borrower relation-
ships. In the case of peer to peer lending the lifeblood of these facilitators depend on
their valued transparency and brand reputation which some argue holds their main
interests rmly with their customers. Also Zopa and Funding Circle are both
institutionally funded at about 30 %,19 the up side to this being the level of scrutiny
they provide for other investors to follow can inspire condence that reliable due
diligence will have been done on the loan originations.
With peer to peer loan origination the principle risk is passed on from borrower
to lender which also leaves the lender with exposure to agency risk from the P2P
platform. With provision funds and a healthy default track record there can be a
common misconception by inexperienced lenders that taking their savings from a
bank to a peer to peer investment with a higher rate will not be without higher risks.
Without a substantial track record lenders can be challenged to assess agency risk
on 5 year commitments when the industry itself has not been in existence for much
longer. Since 2010 interest rates have remained consistently low which has
favoured alternative nance against the banks. This is something that will inevitably
change at some point. It will be interesting to observe the impact of rising interest
rates on the P2P sector.
19
http://www.alt.com/article/1140_key_talking_points_from_p2p_ceo_breakfast.
How Peer to Peer Lending and Crowdfunding Drive 63
Alternative nance paired with Londons FinTech sector has followed in the
footsteps of the UKs centuries old global nancial industry. Between 2012 and
2014, P2P lending in the UK has accounted for approximately 90 % of the alter-
native nance market while Europes peer to peer lending industry made up 59 %
of the market according to a Cambridge Judge Business School report released in
2015.20 Collectively the European alternative nance industry increased its trans-
action volumes by six times in this three year period, though during 2015 alone the
UK market is expected to grow over ve times than is forecast for the rest of
Europe.21 With a thriving FinTech industry and a strong nancial heritage the UK
is set to carry on its leading position within Europe into the foreseeable future.
In 2013 Funding Circle launched in the US and partnered with San Francisco
based business lender Endurance Lending Network Inc. which now trades under the
Funding Circle name. Only a few blocks away one of Americas earliest and most
successful peer to peer rms Lending Club has moved with stealth towards
increased institutional lending. The success of Lending Clubs IPO has been a game
changer for the global Fintech sector. In 2015 institutional investors provided
approximately 45 % of Lending Clubs funding.22 The early days of alternative
nance being seen as something that was most likely to be a one off experiment in
social economics now seems like a distant memory and an industry with such a
strong start in life should be able to weather the storms ahead routinely associated
with our global cyclical economy.
In the UK the extra money that institutions have injected into P2P business
lending has boosted its performance and is overtaking its original counterpart P2P
consumer lending. With larger loans and the attraction of higher returns new
entrants have entered the business lending market. Without much competition from
banks who are still notoriously cautious in lending to SMEs there are now more
business lending platforms than those lending to consumers. Together with the
governments willingness to encourage SMEs with new incentives for both new
businesses and alternative nance, FinTech has been able to create new automated
systems unburdened by archaic over-complicated legacy systems and increased
bank regulations. SMEs can now raise funds via this technology within a fraction of
the time than banks can offer. The wider implications on the economy during these
critical times are positive as the widening ecosystem of FinTech companies who are
building and maintaining these platforms are also attracting record levels of
investment into the UKs nancial technology services.
20
Cambridge Alternative Finance: Moving Mainstream 2015.
21
Cambridge Alternative Finance: Moving Mainstream 2015.
22
http://www.ft.com/cms/s/0/9e966ff2-ed48-11e5-9fca-fb0f946fd1f0.html.
64 S. Chishti
Crowdfunding platforms have reached larger groups of investors from a wide range
of backgrounds, otherwise inaccessible to entrepreneurs and early stage companies.
Originally a platform used most commonly by SMEs, bigger companies are also
using this platform to pitch for funds. Innovation agency. Nesta reported that equity
crowdfunding in the UK had raised 332 m in 201523 This comes at a time when
raising funds for new business ideas would have been impossible for many without
crowdfunding websites to publicise their proposals to the large number of potential
investors that these platforms attract.
Historically business angels and early stage venture capitalists have nanced the
best funding rounds when banks have not been as open to supporting early stage
businesses. At rst funding rounds many startup founders still rely on friends and
family to invest in them during their early days. With an increase in the access to
funds and equity, crowdfunding has encouraged new entrepreneurs to launch
companies contributing towards economic growth. That is a good example where
the FinTech revolution clearly benets all sectors of our economy and not just
nancial services.
The funding process starts with a brief presentation of the business raising funds
posted on one of several crowdfunding sites along with the founders background
and their nancial projections. The crowd is then invited to invest within a number
of weeks to close the entire raise. These campaigns are not aimed exclusively at
sophisticated investors and are in general inherently more risky than investments on
peer to peer lending sites. The UK Crowdfunding Association, was formed in 2012
with the aims of promoting crowdfunding as a valuable and viable way for UK
business projects or ventures to raise funds, to be the voice of all crowdfunding
businesses in the UK (donations, loans and equities) to the public, press and pol-
icymakers and to publish a code of practice that is adopted by UK crowdfunding
businesses.
Most startups do not succeed in the long run. Disclaimers on crowdfunding sites
warn would be investors of the risks and suggest not to part with more money that
can be afforded to be lost. Business angels and venture capitalists usually only
expect a small percentage of their investments to create their overall return. For
example, it is expected that on average only one or two companies out of ten
investments will generate a healthy return. This strategy can be taken further with
crowdfunding allowing investors to back a larger number of companies with
smaller investments as a way to manage risk. Unlike peer to peer lending you will
not be able to cash in an investment for a number of years, if at all. If the company
23
http://www.nesta.org.uk/sites/default/les/pushing_boundaries_0.pdf.
How Peer to Peer Lending and Crowdfunding Drive 65
makes a prot this money is usually reinvested back into the company and there is
no obligation to pay dividends. The best opportunity for an investor to sell their
shares often comes when the company is sold to a trade buyer or is floated via an
Initial Public Offering (IPO) on a securities exchange. These exit options combined
with the high risks of investing into early stage companies are commonly known
among experienced investors. What also needs to be taken into account is that
dilution in follow-on rounds (all companies have to go through several funding
rounds before they exit) is almost a certainty for early stage investors.
When a business goes forward to another round of funding, it issues new shares
which lower the percentage of the company an original shareholder owns. Prefer-
ential rights can also be granted to new, larger shareholders and individuals closely
associated with the company which will have a negative effect on shares previously
bought. Thus crowdfunding investors need to be aware in which share class they are
investing in and the various rights they have in comparison to other investors in
other share classes. On occasion crowdfunding sites themselves are able to act as a
representative of the investors that can help towards maintaining pre-emtion and
voting rights and can prevent the over dilution of shares. In general, the trans-
parency of alternative nance and crowdfunding platforms has been good, but in
the case of shareholder rights extra due diligence is required.
The risks of crowdfunding such as the dilution of shares, illiquidity; lack of
dividends and potential loss have been presented with clear disclaimers on the main
equity crowdfunding sites as hopeful investors attempt and sometimes succeed in
making many times their invested amount. What is unclear is to what extend the
majority of crowdfunding investors really reads and fully appreciates the legal
meaning of these risk disclaimers. The last thing this prospering new sector needs is
a mis-selling scandal which has so heavily tarnished the image and reputation of
established players. Quite often backers simply enjoy the opportunity to help a
66 S. Chishti
24
https://www.syndicateroom.com/about-us/success-stories/mill-residential-reit.
25
http://www.fca.org.uk/static/documents/nalised-guidance/fg15-04.pdf.
26
http://allabout.siansplan.com/hacked-way-100k-crowdfunding.
How Peer to Peer Lending and Crowdfunding Drive 67
of the raise was achieved in the rst two weeks this would signal that the full
amount would follow. With Sians Plan they managed 40 % during this time but had
to work overtime to revive the raise after incoming investments dropped off the
charts half way through their 90 day time window. A daily routine of engaging
posts on Twitter, Facebook, LinkedIn and email created some momentum and
around 50 % of investments came from social media activities. With money coming
in and lots of visible marketing efforts the crowd is more likely to be inspired by a
busy and popular campaign.
Rapid growth and the publicity generated by ongoing successes, usually in the
form of numerous large raises done in record time has led to concern that some
companies could be overvalued. This can be overcome by funding rounds being
endorsed at the beginning by recognised investment companies or angel networks
whilst still maintaining the unique advantages of a crowd led platform. Overvaluing
startups with too optimistic projections is a frequent mistake by the companys
founders and management teams risking a down-round the next time they raise
money leading to dissatised investors and bad publicity. Experienced business
angels and VCs will always take the valuation into consideration when analysing
the risk-adjusted returns. For the many individuals who do not have professional
experience, this aspect of investing is not as transparent and the importance of
understanding valuations and projections is a good example of why seeking
independent nancial advice would be a worthwhile endeavour for the uninitiated
investor wanting to become involved in equity crowdfunding as a long term
investment strategy.
One of the most signicant developments in alternative nance in the UK is the
Innovative Finance ISA announced during the 2015 budget. A consultation has
established that equity crowdfunding can overcome issues such as illiquidity and
become ISA eligible. These eagerly anticipated new ISA products have seen delays
since the initial start date of April 2016. Many applications that have been sub-
mitted to the Financial Conduct Authority (FCA) are still waiting to be processed
and may be months away from approval.27
Government support for FinTech initiatives has been strong in the alternative
nance arena in tandem with their focus on helping SME businesses drive the UK
economy. The Seed Enterprise Investment Scheme,28 (SEIS) and the Enterprise
Investment Scheme (EIS)29 both support the funding of SMEs by providing
attractive tax breaks in the form of income tax relief for private investors who take
the risks of investing in early stage companies. A clear indication that the gov-
ernment wants to create more competition with alternative sources of nancial
support for businesses.
27
http://www.moneysavingexpert.com/news/savings/2016/04/major-peer-to-peer-lenders-still-months-
off-unveiling-isas-amid-approval-backlog-.
28
http://www.gov.uk/seed-enterprise-investment-scheme-background.
29
http://www.gov.uk/government/publications/the-enterprise-investment-scheme-introduction.
68 S. Chishti
Author Biography
Abstract In 1978 China Financial sector has began a gradual reform process.
Within 40 years the country went from a mono-bank model to one composed of
hundreds of wholly-owned State banks and joint stock commercial banks. Yet this
diversication has the banking landscape has not resolves credit allocation inef-
ciency. Indeed, whilst SME represent 80 % of the economic output of the country, it
is only receiving 20 % of the credit originated by banks. This has spurred the
development of shadow banking, an informal and unregulated network of lenders
and borrowers. The emergence of Financial Technology has allowed for this activity
digitized itself in the form of Peer-to-peer lending channel. The combination of and
unregulated market and large credit gap has lead to the emergence of a sector that
had only one platform in 2007 and over 2000 in 2015. Therefore the author submit
that the emergence of the P2P sector in China is neither new, nor unexpected.
Ultimately, this systemic shift caused by the P2P sector offers China a regulatory and
market reform opportunity as the shadow has been brought to the light.
J. Barberis ()
Asian Institute of International Financial Law, Faculty of Law,
University of Hong Kong; and FinTech HK, Pok Fu Lam, Hong Kong
e-mail: janos@ntech.hk
D.W. Arner
Duke-HKU Asia America Institute in Transnational Law, and Member,
Board of Management, Asian Institute of International Financial Law,
Faculty of Law, University of Hong Kong, Pok Fu Lam, Hong Kong
e-mail: douglas.arner@hku.hk
1 Introduction
In 1979, China began the transformation of its economy and the modernization of its
nancial sector. However, ever since, its credit market has suffered from allocation
inefciencies that particularly affect small and medium sized enterprises (SMEs). In a
time of slowing economic growth, this misallocation of capital has an important
impact in that SMEs represent 80 % of the economic output of the country, whilst
only receiving 20 % of the credit originated by banks.1 This mismatch has spurred the
growth of the shadow banking industry in China, an informal sector performing credit
allocation between lenders trying to move liquidity from savings accounts with yields
limited by restrictive rate ceilings and non-State rms looking for the much needed
capital to nance their growth. Since 2009 Chinas shadow banking industry has
expanded its activities via Peer-to-Peer (P2P) lending channels. In just a few years,
nancial technologies (FinTech) have allowed a trillion-dollar and decade-old
industry to emerge at the beginning of the second decade of the 21st century.
In July 2015, Chinas P2P lending platforms numbered 2,136, with settlements
of around RMB 82.5 billion transactions in that single month.2 More worryingly,
130 closed in the previous 2 months alone and over 1,250 are regarded at risk by
local credit rating agencies.3 The speed with which this sector emerged has pre-
vented regulators from drafting adequate legislation to ensure consumer and pru-
dential safeguards, while at the same time underpinning development of the market.
However, in March 2015, the Chinese Banking Regulatory Commission (CBRC)
announced the enactment of new capital requirements for P2P platforms.4 The
sector went from light-touch regulation with low barriers to entry to one where
actors may need to set aside over Yuan 30 million in regulatory capital.5
This change of approach by regulators is a reflection of the fact that the P2P
sector in China has reached a critical size. It went from too-small-to-care to
too-big-too-fail.6 Yet, it performs an important allocation role, especially for SMEs
that have constrained credit access. As a result, and going forward, a balancing act
needs to be performed by the legislators and regulators.
1
Violaine Cousin, Banking in China (Palgrave Macmillan Studies in Banking and Financial
Institutions, 2011, 2nd edition), 84.
2
The data information is collected from http://www.wangdaizhijia.com a Chinese website pro-
viding all sorts of information on P2P lending in China. For the P2P data, see http://shuju.
wangdaizhijia.com/industry-type-0-7-2015.html.
3
Judy Chen, Internet Loan Alarms Dagong with 1250 Red Flags (13 March 2015) Bloomberg,
available at http://www.bloomberg.com/news/articles/2015-03-12/internet-loan-alarms-dagong-
with-1-250-red-ags-china-credits.
4
Daniel Ren, China mulls tighter rules on booming P2P lending business (17 April 2015) South
China Morning Post, available at (http://www.scmp.com/business/china-business/article/1744711/
china-mulls-tighter-rules-booming-p2p-lending-business).
5
Ibid.
6
See Douglas W. Arner and Janos Barberis, Regulation FinTech Innovation: A Balancing Act
(1 April 2015) available at http://www.law.hku.hk/aii/regulating-ntech-innovation-a-balancing-
act-1-april-1230-130-pm/.
FinTech in China: From Shadow Banking to P2P Lending 71
7
This topic is explored in more detail by Zhou, Weihuan and Arner, Douglas W. and Buckley,
Ross P., Regulation of Digital Financial Services in China: Last Mover or First Mover?
(September 2015) available at (http://ssrn.com/abstract=2660050).
72 J. Barberis and D.W. Arner
by setting, global, standards for nancial market and regulatory developments that can
be looked upon by developing markets in South-East Asia and Africa.
In other words, the 21st century may witness a shift where the countrys exports
went from Toys made in China to Regulation made by China.
8
Violaine Cousin, Banking in China (Palgrave Macmillan Studies in Banking and Financial
Institutions, 2011, 2nd edition), 63.
9
Ibid. 4.
10
The Agricultural Development Bank of China (ADBC), The China Development Bank
(CDB) and the China Exim Bank (CEB).
11
Michael F. Martin, Chinas Banking System: Issues for Congress (Congressional Research
Service, 2012), 2.
12
Those are: HSBC, Standard Chartered, Bank of East Asia and Citi.
13
J. Cheng, China: A New Stage of Development for an Emerging Superpower (City of University
Hong Kong Press, 2012), 336.
14
Xinhua, Can private banks survive and thrive? (20 May 2015) China Daily, available at (http://
www.chinadaily.com.cn/china/2015-05/28/content_20848289.htm).
15
Violaine Cousin, Banking in China (Palgrave Macmillan Studies in Banking and Financial
Institutions, 2011, 2nd edition), 54.
16
Michael F. Martin, Chinas Banking System: Issues for Congress (Congressional Research
Service, 2012), 26.
FinTech in China: From Shadow Banking to P2P Lending 73
account for only 35 % of GDP and are responsible for 2030 % of overall economic
growth, yet they capture over 80 % of all loans made.17 In this context, the rise of
P2P platforms is enhancing the speed at which two main stakeholders are being
disintermediated. Namely, the primacy of the formal banking system in originating
loans, and therefore, by extension, the State itself.
Whilst the inclination of the State to control banks is by no means new and can be
seen in other jurisdictions such as Japan, France and Germany,18 State interference
causes a series of problems, ranging from inefcient credit allocation within the
economy, accountability issues19 and even in some casesnancial crises. Indeed,
part of the responsibility for the Asian Financial Crisis of 1997 was attributed to
crony capitalism, whereby loans were made on political considerations, as
opposed to sound commercial sense.20 As it stands, Chinese banks today are in a
hybrid position between making loans based solely on commercial logic on the one
hand (and thus beneting the non-State sector) and following directions that may
only be based on political/personal motives, on the other.21
This conflict in the policy of loan allocation is reverberated at the regulatory level.
The PBOCwhich was made responsible for the stability of the nancial sector
following the 1995 Central Bank Law22has a clear position in requesting that
banks increase the availability of loans to SMEs.23 However, the CBRC, created in
2003, is more focused on the safety and soundness of individual institutions. As a
result, it tends to focus on the avoidance of non-performing loans (NPLs).
A recent example of the impact of government intervention on shadow banking
occurred in the wake of the 2008 Global Financial Crisis, in the context of a massive
Chinese economic stimulus. Indeed, the shadow banking sector was stimulated by a
CNY 4 trillion package (approximately $570 billion) introduced by the Chinese
government in an objective to prevent recession and maintain high levels of domestic
17
Violaine Cousin, Banking in China (Palgrave Macmillan Studies in Banking and Financial
Institutions, 2011, 2nd edition), 84.
18
Simon Cox, Pedalling Prosperity The Economist Special Report (May 2012) available at:
(http://www.economist.com/node/21555762).
19
See (1.2).
20
Douglas W. Arner, Financial Stability, Economic Growth, and the Role of Law (Cambridge
University Press, 2007), 225.
21
Michael F. Martin, Chinas Banking System: Issues for Congress (Congressional Research
Service, 2012), 1.
22
Stephen Bell and Hui Feng, The Rise of the Peoples Bank of China. The Politics of Institutional
Change (Harvard University Press, 2013).
23
Violaine Cousin, Banking in China (Palgrave Macmillan Studies in Banking and Financial
Institutions, 2011, 2nd edition), 124.
74 J. Barberis and D.W. Arner
growth.24 When, however, the government interventionism slowed down and the size
of the stimulus package decreased, the publics demand for credit could not be
satised by the regular banking system alone. This in turn increased the demand for
alternatives and greatly boosted shadow banking activities.25
In this respect, it is perhaps important to note that the development of the P2P
sector in China, similarly to that in the USA, witnessed an increase since 2008.26
However, the difference is that whilst the United States was faced with an important
credit supply shortfall, forcing people to seek alternative lending channels, Chinas
P2P sector can attribute its growth to the fact that SMEs were looking to maintain the
situation of credit abundance that followed the stimulus program of the government.27
For many years China was therefore in a situation where it had to strike a balance:
maintaining sufcient economic growth necessarily implies nancial reform to
better allocate savings into the nancial system.28 At the same time, regulators must
also be able to prevent the liberalization process from creating various asset bubbles
that would affect the real economy if they were to burst. This dilemma is reflected in
former Premier Wen Jiabaos demands for reform and PBOC Governor Zhou
Xiaochuans concerns regarding nancial stability.29 So far, the decision had been
to reach a compromise. Violaine Cousins book Banking in China referred to an
analysis conducted by McKinsey Global Institute in 2006, which estimated that the
foregone GDP growth resulting from an inefcient nancial sector was 13 %.30
It transpires that this sub-optimal growth level is the result of a conscious choice.
The factions that are prone to liberalization and the ones that prefer stability have settled
for a compromise: a slightly lower rate of growth, but more stability which do not put the
24
Guo, Li and Xia, Daile, In Search of a Place in the Sun: The Shadow Banking System with
Chinese Characteristics (July 15, 2014). European Business Organization Law Review, Vol. 15,
No. 03, page 398, Available at (http://ssrn.com/abstract=2562288).
25
Guo, Li and Xia, Daile, In Search of a Place in the Sun: The Shadow Banking System with
Chinese Characteristics (July 15, 2014). European Business Organization Law Review, Vol. 15,
No. 03, page 398, Available at (http://ssrn.com/abstract=2562288).
26
See Morgan Stanley, Can P2P Lending Reinvent Banking (17 June 2015) available at (http://
www.morganstanley.com/ideas/p2p-marketplace-lending/).
27
Arner, Douglas and Barberis, Janos and Buckley, Ross. The Evolution of FinTech: A new
post-crisis Paradigm? (September 2015) page 17 available at (http://papers.ssrn.com/abstract=
2676553).
28
Janos Barberis, A crack in the great wall Too-big-to-Fail Them: A societal perspective (Sept
2013) page 36.
29
Michael F. Martin, Chinas Banking System: Issues for Congress (Congressional Research
Service, 2012), 44.
30
Violaine Cousin, Banking in China (Palgrave Macmillan Studies in Banking and Financial
Institutions, 2011, 2nd edition), 58.
FinTech in China: From Shadow Banking to P2P Lending 75
nancial resources unnecessarily at risk.31 However, as the economy slows down, the
capacity of engaging in a sub-optimal efciency path for Chinas nancial market is not
sustainable. Indeed, it has been pointed out that failing to adequately reform Chinas
nancial system poses the risk to jeopardize future economic growth.32
In other words, it is submitted that the combination of slower economic growth
as well as the rise of P2P lending platforms in China is challenging the extent to
which this balancing act can be maintained. The gatekeepers of nancial liberal-
ization, namely the State power to grant a banking charter or licence, are losing
their effectiveness. Since 2007, the barriers to entry into Chinas nancial system
have been side-stepped by private individuals and Internet nance companies33
delivering over RMB 251 billion of credit in 2014 directly to the public and SMEs.
It may be argued that this is nothing new, indeed the raison detre behind shadow
banking is precisely that of providing nancial products and services to the public,
outside of a traditional and supervised regulatory framework. As discussed in the
introduction section to this chapter, this industry has a decade old history that can be
traced back the Xi-Zhou Dynasty (1045-256 BC).34 However, the point at which this
parallel and informal banking system, described by Kellee S. Tsai as Back alley
banking, has been able to come to the light is largely missed.35 In less than 7 years,
China has witnessed the emergence of over 1,500 P2P lending platforms with a total
loan origination capacity of RMB 251 billion (Fig. 1). To put this in perspective, in
2007 China only had one P2P platform (Fig. 2). These numbers reflect the
year-on-year growth of the market and not its absolute size within the nancial sector
as a whole. It is difcult to evaluate the precise weight of the P2P sector within the
total outstanding loans in Chinas credit market, but to date this remains marginal.36
This exponential growth rate of the P2P industry in China has directly chal-
lenged the governments capacity to gradually implement liberalization policies
within the banking sector.37 Whilst regulators, government and SOEs were
crossing the river by touching the stones,38 the private sector, led by Internet
31
Ibid.
32
This idea is explored in more details in Regulation of Digital Financial Services in China: From
Last Mover to First move? by Weihuan Zhou, Douglas W. Arner and Ross P. Bucley (Sept 2015).
33
Arner, Douglas and Barberis, Janos and Buckley, Ross. The Evolution of FinTech: A new
post-crisis Paradigm? (September 2015) page 34 available at (http://papers.ssrn.com/abstract=
2676553).
34
Hsu S. and Li J., Informal Finance in China: American and Chinese Perspectives (Oxford
University Press USA, 2009), 14.
35
Kellee S. Tsai, Back-Alley Banking: Private Entrepreneurs in China (2004) Cornell University
Press.
36
Guo, Li and Xia, Daile, In Search of a Place in the Sun: The Shadow Banking System with
Chinese Characteristics (July 15, 2014). European Business Organization Law Review, Vol. 15,
No. 03, page 408, Available at (http://ssrn.com/abstract=2562288).
37
Arner, Douglas and Barberis, Janos and Buckley, Ross. The Evolution of FinTech: A new
post-crisis Paradigm? (September 2015) page 34 available at (http://papers.ssrn.com/abstract=
2676553).
38
This expressions illustrates the cautious approach of the government in China when reforming
markets.
76 J. Barberis and D.W. Arner
Transaction Volume
(in RMB Billion)
300
251.5
250
200
150
97.6
100
50
22.9
1.4 8.4
0
2010 2011 2012 2013 2014
Fig. 1 Transaction Volume (in RMB Billion). Source iResearch (showed during HKIFA conference)
1000 800
500
200
1 20
0
2007 2011 2012 2013 2014
nance companies, has been literally leapfrogging their traditional regulatory and
banking counterparts.
It may be argued that, irrespective of its origin, nancial liberalization is positive
since it is expected to both support growth, but also increase job prospects.39 Yet, it
also needs to be remembered that the latest crisis revealed the negative effect of
inadequate liberal deregulation, which destroyed more jobs than those saved and
created in the 1980s.40 There is therefore value in government intervention that is
39
Avgouleas E, Governance of Global Financial Markets: the Law, the Economics, the Politics
(Cambridge University Press, 2012), 106.
40
Ibid. 60.
FinTech in China: From Shadow Banking to P2P Lending 77
15%
10%
5%
0%
2012 2013 2014
Fig. 3 P2P Lending platforms with reported problems (as percentage of total). Source Data
Source wangdaizhijia.com (from HKIFA conference)
highly targeted and precise. Even more so, because every change within the
nancial sector will affect a fragile economic, social and political equilibrium.41
Indeed, even the P2P sector itself is currently experiencing an increased amount of
defaults and closures, as can be seen in Fig. 3.
Whilst the initial wave of nancial liberalization was driven from the bottom-up,
as the industry increasingly engenders systemic risks within the nancial system,
this needs to be effectively addressed by regulators.
It is neither desirable nor possible for the P2P sector to continue its development
in isolation from government policies and regulatory obligations. This is equally
because of the systemic size of the sector as well as of the benecial economic
impact it yields.42 Therefore, one can expect that this sector, which had thus far
been unregulated, will now be tted within the broader context of nancial market
infrastructure. This forms the subject of the following section.
The remainder of this chapter considers the market reform opportunities brought
about by the current developments of P2P lending. The misallocation of credit
within the Chinese economy has been endemic for decades, and this has lead
individuals and corporate parties to create a parallel and non-ofcial network that
41
For more details, refer to Janos Barberis A Crack in the great wall Too-big-to-fail then: a
societal perspective (Sept 2013).
42
Arner, Douglas and Barberis, Janos and Buckley, Ross. The Evolution of FinTech: A new
post-crisis Paradigm? (September 2015) page 24 available at (http://papers.ssrn.com/abstract=
2676553).
78 J. Barberis and D.W. Arner
would perform the credit intermediation that they were otherwise lacking. In the
context of China, non-bank nance and shadow banking thus capture both the
essential elements that we now see in the P2P sector, namely the need for alter-
native forms of nancing to support non-State growth, particularly among SMEs
whilst at the same time addressing potential risks to consumers and the nancial
system.43
The thesis of the second part of this chapter is that for the Chinese government,
the emergence of P2P lending offers a unique opportunity that solves a decade-old
tension which thus far prevented the formalization of the shadow banking indus-
try.44 As will be detailed below, the various routes towards market reforms had the
potential to generate negative externalities which would outweigh the initial
objectives. In essence, because both the shadow and the formal banking sector
provide a vital lifeline of credit to SMEs and SOEs respectively, any reform had the
potential of disrupting a fragile equilibrium. More specically, in respect of shadow
banking, the fact that it was informal and off-line generates a level of information
asymmetry which made it difcult to evaluate the potential consequences of
bringing the sector to the light. Policy-makers risked forcing the sector deeper into
the shadows or simply impeding its much-needed function from an economic
growth perspective.
Most importantly, as was seen in Sect. 2, it appears that since 2008 the shadow
banking sector has indeed been increasingly brought to light, both as a result of
greatly increased academic, policy and market research attention as well as the result
of technology. This is the critical element providing the basis for the authors sub-
mission. Namely, that shadow banks have been attracted to the light by the market
share potential and efciency gains brought by technology, as they move their
operations from off-line to on-line models, which in turn gives a regulatory window
of opportunity to reform this sector in a way that was not possible until now.
The positive impact of that transition is that not only has it removed the
pre-existing information asymmetry that limited the possibility of government
reform, but it has also constrained the capacity of the sector to move further back to
the shadows. Indeed, SMEs and individuals who were former users of shadow
banks, and now borrowers or lenders of P2P platforms, are unlikely to settle for the
necessarily less competitive and transparent terms offered by the off-line shadow
banks.45
43
In other words, China is witnessing the rise of Shadow Banking 2.0. For more of the historical
analysis on the use of technology within the nancial services sector, please refer to Arner,
Douglas and Barberis, Janos and Buckley, Ross. The Evolution of FinTech: A new post-crisis
Paradigm? (September 2015) page 24 available at (http://papers.ssrn.com/abstract=2676553).
44
This is illustrated in Sect. 2.1.
45
As it currently stands there is limited qualitative and quantative surveys that exactly looks at the
P2P industry and would allow to bring empirical data to this statement. However a recent research
project lead by Tsinghua University and Sydney University will offer valuable data set in that
respect.
FinTech in China: From Shadow Banking to P2P Lending 79
The risks caused by shadow banking are not novel and in 2013, a survey reported
that 63 % of respondents expected that shadow banking [will] cause a crisis in
China.46 As a result, the idea that shadow banking should be left free of gov-
ernment intervention is not viable. This is because there is an inherent risk of social
unrest attached to a failing informal banking sector.47 This has led the government
to experiment, with limited success,48 over an extended period of time with various
approaches of bringing the shadows to the light by regulating a sector that is by
denition informal.
If it is true that some regions are more relaxed in letting informal banks operate
within their jurisdiction with little or no control, this is because local ofcials view
shadow banking operations as a popular (minjian) form of grassroots credit.49
This lenience can be regarded as active non-action. In other words, as long as the
activities of the local informal operators do not disturb the economic, social and
political climate, they are left untouched. In that respect, a regulatory ofcial
interviewed by Joe Zhang conrmed this by characterizing the sector as a tolerable
nuisance.50
However, if this was about to change, we would witness an immediate
crack-down on the sector. Indeed, this is precisely what happened in October 2012
when a default of informal banks in Wenzhou threatened to transform into a
regional crisis.51 The event would perhaps have remained unnoticed if it were not
for the fact that the potentially affected province, Zhejian, is home to 55 million
people, and also considered to be the historical capital of entrepreneurship in China.
One should bear in mind the fact that three leading ofcials (then Premier Wen
Jiabao, PBOC Governor Zhou Ziachuan and then Finance Minister Xie Xuren)
went there to personally witness the problem caused by informal nance, and
subsequently called for the closure of those institutions.52
46
Caixin survey, available at: (http://service.caixin.com/pollcode/resulten/batch/576).
47
Hsu S. and Li J., Informal Finance in China: American and Chinese Perspectives (Oxford
University Press USA, 2009), 144.
48
Yet, the difculty of introducing comprehensive nancial reform in the shadow banking sector is
not exclusively conned to China. United States regulators have also struggled to provide for
complete coverage of this sector, as seen by the sparse treatment of shadow banking in the
otherwise extensive Dodd-Frank Act.
49
Hsu S. and Li J., Informal Finance in China: American and Chinese Perspectives (Oxford
University Press USA, 2009), 144.
50
Joe Zhang, Inside China's Shadow Banking: the Next Subprime Crisis? (Enrich Professional
Publishing, 2013), 91.
51
Michael F. Martin, Chinas Banking System: Issues for Congress (Congressional Research
Service, 2012), 7.
52
Michael F. Martin, Chinas Banking System: Issues for Congress (Congressional Research
Service, 2012), 44.
80 J. Barberis and D.W. Arner
53
With a similar point being made about P2P lending and current increase in market risk it creates.
54
A private money-lending association, and thuspart of informal nance.
55
Hsu S. and Li J., Informal Finance in China: American and Chinese Perspectives (Oxford
University Press USA, 2009) pp. 21 and 141.
56
Michael F. Martin, Chinas Banking System: Issues for Congress (Congressional Research
Service, 2012), 2.
57
China Daily, Entrepreneurs face dilemma over funds (22 July 2013), available at: (http://usa.
chinadaily.com.cn/opinion/2013-07/22/content_16811976.htm), accessed 24 August 2013.
58
Joe Zhang, Inside Chinas Shadow Banking: the Next Subprime Crisis? (Enrich Professional
Publishing, 2013), 84.
59
Hsu S. and Li J., Informal Finance in China: American and Chinese Perspectives (Oxford
University Press USA, 2009), 14.
60
Ibid. 17.
61
Hsu S. and Li J., Informal Finance in China: American and Chinese Perspectives (Oxford
University Press USA, 2009), 16.
62
Ibid. 19.
FinTech in China: From Shadow Banking to P2P Lending 81
number is attributable to the fact that membership was made compulsory in vil-
lages, explaining the sheer size of the sector by an obligation people have, as
opposed to a genuine inclination to use RCCs. Because Regional Credit Cooper-
atives did not respond to a true social necessity, informal nance has risen again.
Second, the governments next attempt to crack down on this sector was seen in
1998 with the fall of the Three Star Holding Company. Following government
investigations, this informal bank faced a lack of condence from its depositors and
investors. This caused a bank run, which in turn prompted the local government to close
the company, leading to over 30,000 people marching on the streets.63 As a result, the
governments measures of closing down a company formed by a farmer, as opposed to
even more inefcient State-run enterprises, had occasioned instability and controversy.
Finally, the persistence and pervasive nature of informal nance in China can be
explained by the theory of institutional demand.64 Indeed, informal nance is
simply the symptom of a formal sector that is both dysfunctional and unable to
provide small, often unsecured loans to SMEs or individuals. Thus, suppressing
informal nance would be ineffective and push that sector even deeper into the
shadows.65 The risks of such an approach stem from the likelihood that this will
further impede both the monitoring,66 and also the prospect of regulating this
segment of the economy in the future.
From the above analysis, it appears clear that the reform margin government
bodies have is very narrow. Because of the fact that shadow banking and P2P
lending supply credit to the non state actor that generate 80 % of the countrys
economic output,67 any regulatory heavy-handedness may be destabilising from a
social, economic and nancial perspective.
At the other side of the spectrum, one needs to consider that instead of xing the
symptoms of shadow banking, the government may have more success in resolving
the inefciencies within the formal banking sector itself, especially given the far reach
of government control within banks. In practice, this revolves around the liberalization
of the formal nancial sector. Yet, this move towards a more market-orientated
nancial system has its own limitations, three of which are highlighted below.
First, the liberalization of market rates will have political repercussions in the
sense that the State would lose its control over the nancial sector, which it is
reluctant to do, although it is now likely that this process will largely be complete
63
Ibid. 93.
64
Ibid. 25.
65
Hsu S. and Li J., Informal Finance in China: American and Chinese Perspectives (Oxford
University Press USA, 2009), 35.
66
The UK has shown the advantage of not cracking down on sensitive sectors. For example, by
allowing extremist Salast groups to openly protest on the streets and in front of Parliament, this
helped intelligence services to gather data on the membership of such groups. Therefore, even if
the government cannot regulate the informal sector, it should at least monitor it and identify major
supporters and participants.
67
Janos Barberis, A Crack in the Greal Wall Too-big-to-Fail-Them: A societal perspective
(Sept 2013) page 40.
82 J. Barberis and D.W. Arner
68
Violaine Cousin, Banking in China (Palgrave Macmillan Studies in Banking and Financial
Institutions, 2011, 2nd edition), 10.
69
Simon Cox, Pedalling Prosperity The Economist Special Report (May 2012) available at:
(http://www.economist.com/node/21555762) 7.
70
However, the benet of liberalizing interest rates of loans is that SOEs will not borrow as much
and thus free up the much-needed capital for SMEs. (Source Joe Zhang, Inside Chinas Shadow
Banking: the Next Subprime Crisis? (Enrich Professional Publishing, 2013) 104).
71
Michael Pettis, The Great Rebalancing: Trade, Conflict, and the Perilous Road Ahead for the
World Economy (Princeton University Press, 2013), 95.
72
L.T. Alexander, Cybernancing for Economic Justice (2013) 4 Wm. & Mary Bus. L. Rev. 309,
available at: (http://scholarship.law.wm.edu/wmblr/vol4/iss2/2), 319.
73
See Sebastian Diemer, Lending club IPO what drives the value of P2P lending platforms (11
Dec 2014) Kreditech, available at (https://www.kreditech.com/blog/lending-club-ipo-what-drives-
the-value-of-a-p2p-lending-plattform/).
74
See Peter Baeck, Liam Collins and Brian Zhang, Understanding Alternative Finance: The UK
alternative nance industry report 2014 (November 2014) NESTA page 23 available at (https://
www.nesta.org.uk/sites/default/les/understanding-alternative-nance-2014.pdf).
75
Hsu S. and Li J., Informal Finance in China: American and Chinese Perspectives (Oxford
University Press USA, 2009), 133.
FinTech in China: From Shadow Banking to P2P Lending 83
Importantly, for the purpose of the authors argument, the exponential growth of the
P2P industry in China cannot be understood in a vacuum. Instead, it is submited
that the P2P boom in China is not only attributable to the same arbitrage oppor-
tunities (i.e. negative interest rates payable on current accounts, moving excess
savings towards P2P platforms that yield a higher return), but also to the fact that
traditional shadow banks have moved their operations online, attracted by the lower
operating costs and broader market share they can reach by using the Internet.76
This is not to say that the P2P industry is only composed of long-standing actors,
as undeniably there have been new players in the market that have no previous
history as shadow banks. Indeed, this is illustrated by two key new companies.
First, the most publicized example is AliFinance, part of the Alibaba group, which
has already originated 409,444 loans with an outstanding portfolio of 105 billion
RMB ($17.2 billion).77 Second, and perhaps the most (in)famous illustration of a
market overheating is Panda Firework Group Co., a listed reworks manufacturer
that changed its core business entirely to become a P2P lending provider.78
Thus, until a detailed study is performed to examine the origins and sources of
funds of all P2P platforms in China, it is difcult to determine whether this is a
wholly novel industry or a new twist on the old shadow banking model.79 However,
it would be fair to assume that the P2P lending sector is predominantly supported
by operators or funds of shadow banks. It could thus be argued that there is little to
distinguish shadow banks and P2P lenders in China. In both cases they operate
without a formal regulatory framework and perform an intermediation function
between lenders and borrowers, the most noticeable difference being in the origi-
nation channel, which is principally online. Unlike the formal banking system,
shadow banking, whether in its traditional or online form, relies on a different
76
There is currently a very limited amount of primary research on the P2P industry in China and
Asia which limits the capacity of formally linking shadow banks with P2P platforms. It is expected
that the new effort lead by Cambridge, Tsinghua and Sydney Universities is conducting an Asia
wide Alternative Finance Benchmarking Survey will offer the necessary data set to conrm the
above argument. See JD Alois, The University of Cambridge, Tsinghua University & the
University of Sydney join forces to launch the 2015 Asia-Pacic Alternative Finance Bench-
marking Survey (Crowdfund Insider, November 11) available at (http://www.crowdfundinsider.
com/2015/11/77114-the-university-of-cambridge-tsinghua-university-and-the-university-of-
sydney-join-forces-to-launch-the-2015-asia-pacic-alternative-nance-benchmarking-survey/).
77
Leesa Shrader, Micronance, E-Commerce, Big Data and China: The Alibaba Story, 11
October 2013, CGAP (Consultative Group to Assist the Poor).
78
Bloomberg News, Seeing Bang for Buck, Even China Fireworks Makers Now Do Finance,
April 13, 2015, (http://www.bloomberg.com/news/articles/2015-04-12/seeing-bang-for-buck-
even-china-reworks-makers-now-do-nance).
79
It is expected that Tsinghua University will conduct quantitative and qualitative research on the
topic in 2016.
84 J. Barberis and D.W. Arner
nancial market infrastructure to fund and originate its loans. In this relation, Guo
and Xia point out some of the variations in the nancing mechanisms of traditional
nancial institutions in China and shadow banks:
In the regular banking system, the whole process of credit intermediation takes place within
one bank. However, in the shadow banking system, institutions coordinate to complete the
intermediation chain. In this system, commercial banks and nancial companies also
originate loans, as in the regular banking system, but they do not hold the loans or bear the
credit risks. []The shadow banking system does not rely on bank deposits to support its
lending business. Shadow bank deposits come from money market mutual funds
(MMMFs).80
In addition, Guo and Xia note that the borrowers who resort to the services of
shadow banking or P2P lending providers are often individuals or entities who have
had difculty obtaining credit through the normal nancial system.81
Once one accepts the fact that shadow banking and P2P lending represent the
same industry, but are conducted via new channels, this opens an important reg-
ulatory window of opportunity to reform shadow banking in a way that was not
possible before. Section 3.1 of this chapter revealed that the difculty in reforming
the shadow banking system came from two elements:
1. High asymmetry of information limiting the capacity to evaluate the
positive/negative externality of any reforms, and
2. Irrespective of its unregulated nature and the risk it holds, the shadow banking
sector performs an important credit supply role for SMEs.
For policy-makers and regulators this means that the capacity for reform is
exceptionally narrow, with a high probability that the negative externalities out-
weigh the benets of formalizing the sector. Nevertheless, with hindsight, it might
appear that this inaction has played in regulators favor and will ultimately allow
them to better regulate the shadow banking sector in future.
The authors submission, and contribution to this topic, is that the (active?82)
absence of regulation of the P2P lending sector had the outcome of eliminating
80
Guo, Li and Xia, Daile, In Search of a Place in the Sun: The Shadow Banking System with
Chinese Characteristics (July 15, 2014). European Business Organization Law Review, Vol. 15,
No. 03, page 395, Available at (http://ssrn.com/abstract=2562288).
81
Ibid, 402.
82
Active or not, this point can be the one of discussion. Indeed, if active, it would have meant that both
policy makers and regulators were the mastermind to let a sector remain unregulated in views of
formalizing it in the future. This is perhaps giving too much credit to these bodies, however, in itself
this may not be surprising. China has already used its accession to the WTO as a way to bring
back-door liberalization into State-owned-enterprises. Direct reform, without having recourse to the
WTO obligations would have made the task much harder for political reasons. Second, again using a
WTO analogy, China has revealed its capacity of playing a forward-looking chess game in the context
of the card networks. In practice, this meant that China has allowed the Union Pay card network to
grow by shielding it from the competition of its US counterparts (e.g. Visa and MasterCard) and
against WTO rules. China was aware of that but kept the infringing behaviour up until the point of the
WTO court judgement, conrming that this was the case. Importantly, China knew that it had a losing
FinTech in China: From Shadow Banking to P2P Lending 85
barriers to entry. As a result, between 2007 and 2014, P2P lending platforms have
gained traction and market acceptance emanating from SMEs that seek credit and
lenders who look for higher yields than those offered within the traditional banking
sector. Importantly, the technological component of P2P platforms creates a com-
petitive advantage vis--vis physical shadow banks that translates into better
interest rates paid or charged to users of P2P platforms. Not only this, but the lack
of physical location, beyond pure cost benets, removes friction and increases ease
of use for consumers. Therefore, whilst one may see shadow banks and P2P
platforms as substitutes, the latter are clearly superior.
Since mid-2014, there has been an increase in consultation activity on the part of
Chinese regulators to gradually consider the imposition of rules for P2P plat-
forms.83 Namely, these are meant to cover regulatory capital, licensing obligations
as well as better loan origination and credit scoring mechanisms so as to avoid
excessive credit creation. These upcoming obligations will necessarily increase the
operating cost of P2P platforms which in turn erodes the cost-competitive benet
that they hold against physical shadow banks.84
Yet, it is very unlikely that the future onus on P2P platforms would be so high
that it turns into a regulatory overkill which makes this online business less eco-
nomically viable than physical origination.85 Moreover, whilst certain actors may
have been solely operating on the pre-condition that this sector remains unregu-
lated, one may at most witness a concentration of players within the P2P space.
Importantly a reduction in the number of platforms is not expected to equate to a
fall in the number of users. For example, between them My089.com and LuFax
have over 30 billion RMB in outstanding loans, or over 10 % of a market valued at
241 billion RMB for 2014.86
The outcome of the above analysis is that, if understood correctly, regulators in
China may have willingly allowed for the unregulated development of the P2P
(Footnote 82 continued)
case but also knew that any damages to be paid are from the date of the judgement and dont
back-date to the start of the infringing behaviour. As a result, China has rightly masterminded
the plan to grow the Union Pay card network and give a de facto dominant market share and its
cost for doing so would be negligible (e.g. legal fees) as they wont include WTO nes. This
analysis of the UnionPay case was made by Jane K. Wing in a 2012 seminar entitled: The
US-PRC UnionPay WTO Dispute: Bringing the Back Ofce Front & Center available at (http://
www.law.hku.hk/aii/wp-content/uploads/2012/05/ppt-ProfWinn-5Oct2012.pdf).
83
Liz Mak, Consolidation imminent as new rules hit Chinas P2P Sector (12 August 2015) South
China Morning Post, available at (http://www.scmp.com/business/banking-nance/article/
1848743/consolidation-imminent-new-rules-hit-chinas-p2p-sector).
84
This observation is an extension of the cost structure analysis between banks and P2P platforms
which can be found on the following gure (http://www.kreditech.com/wp-content/uploads/2014/
12/10845953_10206006364738406_740803989809562525_n.jpg).
85
The reason from this comes from the fact that the cost and human capital structure of online P2P
platforms is much leaner than traditional banks.
86
Zoe Zhang, Overcoming Challenges of Internet Finance Innovation in Hong Kong (28 May
2015) HKIFA.
86 J. Barberis and D.W. Arner
lending sector. This then lead to a mass market adoption which is hard to reverse
due to the cost benets (e.g. flexibility, convenience, time87) for all the stake-
holders, even after factoring for compliance costs. Furthermore, the scalability
opportunity provided by the online business model of these shadow banks of the
21st century means that it becomes much more cost effective for regulators to
supervise one institution with a critical mass of users (e.g. for example AliFinance
has over 400,000 borrowers) as opposed to a fragmented industry.
In other words, regulating the P2P industry appears to have been not only the
most efcient way of handling the problem caused by shadow banking, but the only
way to do successfully. Whether or not this is the result of careful planning from
policy-makers, or sheer coincidence, this is positive for China as a whole as it
creates a framework around the P2P sector which plays a critical role into the
countrys nancial market reform and economic growth.
Whilst Sects. 2 and 3 illustrated the regulatory and policy benets of bringing the
shadow banking to the spotlight, albeit indirectly, through P2P lending, the chapter
now turns to the broader topic of regulatory added value in the context of FinTech.
Indeed, if the authors left open for further discussion the point whereby Chinese
regulatory inaction was actually intended to formalize a sector that eluded them thus
far, China has the opportunity to make a claim as a forward-looking regulator in
line with the 21st century.
This section starts by introducing the concept behind Regulatory Technology
(RegTech) before focusing on the extent to which this is applicable to Chinese P2P
sector. The relevance of discussing RegTech echoes the fact that, with the increased
use of technology within the nancial services industry, regulatory bodies have the
opportunity to access a level of granularity in risk assessments that did not previ-
ously exist. Indeed, Andy Haldane, the ex-head of stability at the Bank of England,
when discussing the future of regulation shared his vision:
What more might be feasible? I have a dream. It is futuristic, but realistic. It involves a Star
Trek chair and a bank of monitors. It would involve tracking the global flow of funds in
close to real time (from a Star Trek chair using a bank of monitors), in much the same way
as happens with global weather systems and global internet trafc. Its centre piece would be
a global map of nancial flows, charting spill-overs and correlations.88
87
See Peter Baeck, Liam Collins and Brian Zhang, Understanding Alternative Finance: The UK
alternative nance industry report 2014 (November 2014) NESTA page 23 available at (https://
www.nesta.org.uk/sites/default/les/understanding-alternative-nance-2014.pdf).
88
Andrew G. Haldane (Keynote), Managing global nance as a system (29 October 2014) Bank
of England, available at (http://www.bankofengland.co.uk/publications/Documents/speeches/
2014/speech772.pdf).
FinTech in China: From Shadow Banking to P2P Lending 87
This vision of a data-led regulatory system is not new. Back in 2009 the SEC
created the division for Economic and Risk Analysis under the supervision of
Henry Hu,89 looking at driving data insight for better regulation. However, it seems
clear that since 2007 there has been an increase in activity emanating from regu-
lators, industry and academia alike on this topic. For example, in 2014 in Australia,
the Center for International Financial Regulation initiated a research project entitled
Regulatory Analytics and Data Architecture (RADAR).90 In addition, post-2007,
Scott Peppet published a paper on smart mortgages whereby the use of data could
limit the default risks.91 However, one needs to balance the opportunity opened by
technology and some practical barriers to actual and successful implementation, all
of which are discussed below.
The nancial sector has been the largest spender on IT systems for decades92 and
this trend is unlikely to stop, especially in respect to regulatory and compliance
spending. Indeed, prior to 2007, technology was used by banks as part of their
tool-kit to comply with their various reporting and compliance obligations,
including but not limited to93:
Legislation/regulation gap analysis tools
Transaction reporting tools
Regulatory reporting tools
Activity monitoring tools
Case management tools
In the wake of the 2008 Global Financial Crisis, the regulatory onus and the level
of scrutiny requested by regulators has dramatically increased.94 Indeed, regulators
have moved towards a risk-based approach where access to data is key to performing
89
Professor Henry Hu is teaching Law at the university of Texas at Austin, before that he was the
inaugural director of the Division for Economic and Risk Analysis within the SEC. Full biography
available here (https://law.utexas.edu/faculty/huht/).
90
Centre for International Finance and regulation, Regulatory Data Architecture and Analytics
(20142015) available at (http://www.cifr.edu.au/project/T019.aspx).
91
Peppet, Scott R., Smart Mortgages, Privacy and the Regulatory Possibility of Infomediation.
U of Colorado Law Legal Studies Research Paper No. 09-13. Available at SSRN: (http://ssrn.com/
abstract=1458064) or (http://dx.doi.org/10.2139/ssrn.1458064).
92
Arner, Douglas and Barberis, Janos and Buckley, Ross. The Evolution of FinTech: A new
post-crisis Paradigm? (September 2015) page 40 available at (http://papers.ssrn.com/abstract=
2676553).
93
Lory Kehoe RegTech is the New FinTech: How Agile Regulatory Technology is helping rms
better understand and manage their risks (2015), page 5 DELOITTE available at (http://www2.
deloitte.com/content/dam/Deloitte/ie/Documents/FinancialServices/ie-regtech-pdf.pdf).
94
Tony Ciro, The Global Financial Crisis: Triggers Responses and Aftermath (2013) page 143.
88 J. Barberis and D.W. Arner
95
Daniel Gutierrz Big Data for FinanceSecurity and Regulatory compliance considerations
(20 Oct 2014) available at (http://insidebigdata.com/2014/10/20/big-data-nance-security-
regulatory-compliance-considerations/).
96
Formulation coined by Glen Hubbard in Financial reforms fails on too-big-to-fail.
97
Micahel Mainelli, RegTech - worthy of Investment (24 June 2015) available at (http://igtb.
com/article/regtech-%E2%80%93-worthy-investment).
98
Halah Touryalai, Big Banks Fined $2.3B over illegal Libor cartels, more Fines on the way
(4 December 2013) Forbes, available at (http://www.forbes.com/sites/halahtouryalai/2013/12/04/
big-banks-ned-2-3b-over-illegal-libor-cartels-more-nes-on-the-way/).
99
Janos barberis, The 2007 Metldown: A legal Phenomenon (June 2012) page 12 available
at (http://ssrn.com/abstract=2296812).
100
Charles Roxburgh, Minouche Shak and Martin Wheatley, Fair and Effective Market Review:
Final Report (June 2015) available at (http://www.bankofengland.co.uk/markets/Documents/
femrjun15.pdf).
FinTech in China: From Shadow Banking to P2P Lending 89
Firms have started to make progress in response to the limitations of existing surveillance
solutions, including the use of new technology and analytics which go beyond the
key-word surveillance and simple statistical checks previously used by rms to detect
improper trading activity and discussed earlier in this section.101
101
Charles Roxburgh, Minouche Shak and Martin Wheatley, Fair and Effective Market Review:
Final Report (June 2015), page 90 available at (http://www.bankofengland.co.uk/markets/
Documents/femrjun15.pdf).
102
Charles Roxburgh, Minouche Shak and Martin Wheatley, Fair and Effective Market Review:
Final Report (June 2015) page 91 available at (http://www.bankofengland.co.uk/markets/Documents/
femrjun15.pdf), (http://www.bankofengland.co.uk/markets/Documents/femrjun15.pdf).
103
Vytautas Cyras and Reinhard Riedl, Formulating the enterprise Architecture compliance
problem (2009) available at (http://ceur-ws.org/Vol-924/paper14.pdf).
90 J. Barberis and D.W. Arner
104
Vytautas Cyras and Reinhard Riedl, Formulating the enterprise Architecture compliance
problem (2009), page 146 available at (http://ceur-ws.org/Vol-924/paper14.pdf).
105
To some extent if regulation if fully automated, the concept of compliance culture may become
challenged all together.
FinTech in China: From Shadow Banking to P2P Lending 91
The above two illustrations serve and important purpose within the debate
around the potential and benets of RegTech. Indeed before looking at the
(re)transcription of compliance obligations into IT processes the rst question is
much more fundamentalhow should Financial Technology itself be regulated?
To date the debate, especially in Asia, seems to be more on understanding what
is the best framework so as to provide the right balance between market innovation
92 J. Barberis and D.W. Arner
(e.g. which as seen is benecial in the case of P2P lending in China) but also market
condence (e.g. again the P2P sector has shown how it can destabilize markets, as
show with Chinas recent stock market volatility).106
Furthermore, whilst is the West the topic of RegTech has been developed much
more by regulators (with the UK government dedicated a chapter of the Blackett
Review107 on the Topic and Europe is pushing towards increase data transparency
with MiFID) in practice there are still uncertainties, as reported by Chris Brummer
and Daniel Gorne,108 as to whether or not principle based approaches are better
suited than rule based approaches.
Therefore it seems that whilst the rational and potential benets of a fully data
driven regulatory system are clear,109 the application in practice of such a system
remains distant. Thus, and in the context of China, it is fair to say that whilst
FinTech provides an efcient method to engage into market reform process, neither
the regulators nor the industry is ready to fully move compliance into the digital
ages. However, and as it will be discussed in the concluding part, this is not to say
that China may not export its FinTech innovation.110
106
Unknown, Some Chinese are take 22 % margin loans to nance sock purchases (1 July 2015)
available at (http://www.bloomberg.com/news/articles/2015-06-30/hidden-china-stock-debt-revealed-
in-online-loans-at-22-interest).
107
Government Ofce for Science, FinTech: Blackett Review (18 March 2015) available at
(https://www.gov.uk/government/publications/ntech-blackett-review).
108
Chris Brummer and Daniel Gorne, FinTech: Building a 21st Century Regulators Toolkit
(October 2014), page 8, available at (http://assets1b.milkeninstitute.org/assets/Publication/
Viewpoint/PDF/3.14-FinTech-Reg-Toolkit-NEW.pdf).
109
Given the fact that the authors expect that wide adoption RegTech in China is unlikely in the
next 5 yearspotential applicability in the context of P2P lending will not be discussed in length.
However, on an introductory note and expanding on the theme of how Shadow Banks transited to
P2P platforms, technology could be used to maintain certain benets of physical networks and
originations. Indeed, part of the low delinquency rates of loans made by informal networks can be
explained by the social peer pressure emanating from the fact that the borrowers and lenders are
from the same community. Furthermore, specic lending groups share not only capital but also
expertise. Geographical proximity acts both as a deterrent for borrowers to default but also par-
ticipate in the skill transfers necessary to improve the success of the enterprises nanced by the
loan. Therefore, platforms can consider using geo-location as provided by IP addresses of bor-
rowers and lenders so as to geographically match these. Obviously the limitation of this use of
technology is that you arbitrarily limit the scalability benet of the internet as you select only local
participants. From a regulators perspective doing the above would also increase concentration risks
and perhaps consumer protection risks if the physical proximity favours the recourse of force for
debt recollection. Therefore, the benet might be in creating a balanced ratio between local/
regional P2P lenders for any borrower.
110
See, Gulveen Auakh Alibaba, Ant Financial invest about $680 million in Paytm, up stake
to 40 % (30 September 2015) The Economics Times, available at (http://economictimes.
indiatimes.com/industry/banking/nance/banking/alibaba-ant-nancial-invest-about-680-million-
in-paytm-up-stake-to-40/articleshow/49148651.cms).
FinTech in China: From Shadow Banking to P2P Lending 93
In closing, this section places the discussion of Chinas P2P sector within the
broader context of the role FinTech plays in Chinas nancial market development.
This discussion matters because P2P advances need to be understood as integral to
Chinas objective of devising a framework that supports and supervises the
development of digital nancial services.
For China the benet of doing so is clear. As we saw in the second part, P2P
lending opened a window of opportunity to regulate the shadow banking industry.
Likewise, FinTech also opens the path for a gradual liberalization of the countrys
nancial system. This is done by indirectly introducing competition (via the new
private banks) and efciency (via the use of technology) within a State-owned
banking system hampered by legacy IT systems and behavioural biases that end up
beneting SOEs.
Whilst still a work in progress, there have been noticeable developments. Since
2014, there is a clear trend where the government is actively promoting comple-
mentary, if not alternative, nancial products and services aimed at SMEs and
individuals. Indeed Zhou, Arner and Buckley reported that the introduction of the
new deposit insurance system has allowed the arrival of 5 new private banks and
approved the establishment of 13 privately controlled nancial leasing companies
and nancial companies afliated to corporate groups and 162 village and
township banks with private sector taking a dominant share.111 The latest and
most signicant policy landmark is without doubt the issuance of the Guidelines on
the Promotion of the Healthy Development of Internet Finance112 on 18 July 2015.
Chinas Great Leap Forward in 1958, was Maos objective to quickly transit the
country from an agrarian society to one powered by industrialization and socialism.
However, when it comes to nancial market reforms, the speed at which these
occurred was much more gradual, giving to the expression crossing the river by
touching the stones all its meaning.
This changed in 2007 as China swiftly transited from shadow banking to P2P
lending. The country has scratched the surface of the broader trend of nancial
market structures reformed as a result of technological changes. Looking ahead, it is
important for China to reach the balance between supporting the efciency brought
by the nancial technology sector, whilst framing this within a regulatory
111
Zhou, Weihuan and Arner, Douglas W. and Buckley, Ross P., Regulation of Digital Financial
Services in China: Last Mover or First Mover? (September 2015), available at (http://ssrn.com/
abstract=2660050).
112
Guan Yu Cu Jin Hu Lian Wang Jin Rong Jian Kang Fa Zhan De Zhi Dao Yi Jian (Guideline on
the Promotion of the Health Development of Internet Finance), promulgated on 18 July 2015. The
Chinese ofcial version of the Guideline is here: (http://www.mof.gov.cn/zhengwuxinxi/
zhengcefabu/201507/t20150720_1332370.html).
94 J. Barberis and D.W. Arner
framework that maintains healthy competition and market resilience. To date, this
appeared to have been the case. Even though P2P market growth has been
explosive, the reform process engaged in by the recent consultation will favor
market concentration as opposed to rupture. Not only this, but China has been able
to both regulate the industry itself and settle it within a specic complementary role
to banks.
Going forward, China is developing a tiered regulatory regime and by doing so,
the competitive and liberalization pressure brought by the FinTech sector is man-
ageable, both for regulators but also for incumbent nancial institutions. This
decision to move towards a tiered regime has consequences beyond Chinas bor-
ders. Indeed, worldwide, the FinTech industry is challenging traditional nancial
market infrastructure and pre-existing regulatory frameworks, and P2P lending is
spearheading this charge.
In the West it is the market itself that is adapting to this shift. The P2P sector is
essentially turning towards Institutional-to-Peer system and allowing traditional
banks to originate loans or deploy excess liquidity in a more effective way.113
However, China is formalizing this harmonious relationship between banks and
FinTech players by creating a tiered regulatory regime. In other words, China is
leapfrogging the world in terms of FinTech regulation and building a specic
framework for it. Indeed, the UK which is often regarded as the most advanced
jurisdiction in terms of FinTech regulation has to its credit moved from a rule- to a
principle-based approach, granting slightly more flexibility to new entrants but
failing to perfecting a framework for collaboration.114
This puts China at the forefront of regulatory developments within FinTech and
signals a dramatic change in the origin of where regulatory standards may emerge
from. In effect, China is potentially challenging the pre-emminence of the UK and
the USA in terms of nancial regulation in this area. However in practice we may
expect that only developing nations with a similar level of nancial infrastructure
and necessity for broad market reform (e.g. Vietnam, Malaysia) to look at the China
model as a standard.115
113
Zoe Thomas, Institutional investors eye P2P lending Platforms (19 June 2015) IFLR, available
at (http://www.ir.com/Article/3463890/Institutional-investors-eye-P2P-lending-platforms.html).
114
To some extent this is not fully accurate. The FCA has recently engaged into a consultation for
the feasibility of opening bank APIs to third parties. Furthermore and most noticeably the recent
announcement of a regulatory sandbox for spring 2016 would create a very important precedent
for the UK and other regulatory bodies globally. See FCA, Regulatory Sandbox (10 November
2015) available at (https://www.fca.org.uk/news/regulatory-sandbox).
115
Arner, Douglas and Barberis, Janos and Buckley, Ross. The Evolution of FinTech: A new
post-crisis Paradigm? (September 2015) page 30 available at (http://papers.ssrn.com/abstract=
2676553).
FinTech in China: From Shadow Banking to P2P Lending 95
Acknowledgments The authors gratefully acknowledge the nancial support of the Australian
Research Council Linkage Grant (Regulating a Revolution: A New Regulatory Model for Digital
Finance) and the Hong Kong Research Grants Council Theme-based Research Scheme (Enhanc-
ing Hong Kongs Future as a Leading International Financial Centre).
Author Biographies
116
Ashley Lee, Chinese deposit insurance to prompt FinTech innovation (2 April 2015)
available at (http://www.ir.com/Article/3441991/Chinese-deposit-insurance-to-prompt-ntech-
innovation.html).
117
Fareed Zakaria, The Post-American World: Release 2.0 (W. W. Norton & Co.; 2nd Revised
edition, 2011), 34.
96 J. Barberis and D.W. Arner
Nicolas T. Courtois
Abstract Bitcoin has a number of features and properties which are sometimes
presented as interesting and positive. In fact they are closer to engineering mistakes.
Serious problems are programmed in the DNA (the source code) of great majority
of crypto currencies. Small details in the source code can make very big difference.
In this chapter seven major sins of Bitcoin are discussed highlighting risks and
suggesting solutions.
N.T. Courtois ()
University College London, London, UK
e-mail: n.courtois@ucl.ac.uk
launched (Nakamoto 2008; Nakamoto et al. 2014) in 2009 it has been always been
clear that it is an experimental rather than mature electronic currency ecosystem.
A paper at the Financial Cryptography 2012 conference explained that Bitcoin is a
system which uses no fancy cryptography, and is by no means perfect (Barber et al.
2012). In a more recent paper (Courtois 2014) we have taken the view that Bitcoin
and other similar crypto currencies has a number highly problematic self-defeating
properties, which do not contribute to the success of bitcoin and somewhat create a
space for bitcoin clones to thrive. In modern startup culture, very frequently tech-
nology push replaces common sense and bugs are presented as features. In contrast,
we believe that our duty of academics is rst of all to study and inform. Our job is to
cultivate an informed debate about advantages and disadvantages of various tech-
nical design choices which are inevitably made in every real-life system.
Bitcoin has been a victim of its own success and has created great expectations
which it can now hardly live up to. It has for many years already been in an
unchartered territory which the mysterious founder (Nakamoto 2008) of bitcoin has
clearly not anticipated, for example the centralization of mining (Felten 2014) and
the full scope of 51 % threats, see Courtois (2014) and our later Sect. 6. Bitcoin is a
relatively simple system yet in which billions of dollars are at stake. While banks
and governments spend billions on security, bitcoiners are expected to trust cryp-
tography and wisdom of a handful of developers to steer through all the security
pitfalls. This is a lot to ask and surely academics can help in this task too.
In this chapter we explore seven major issues which we view as the most important
technical or/and security problems in current bitcoin. Bitcoin has been largely an
imperfect design suffering from serious fundamental flaws and things did not always
work as predicted. A key observation in Courtois (2014) is that a number of unfor-
tunate engineering mistakes are programmed into bitcoin source code, they are in the
DNA of bitcoin. There are also other protocols such as Stratum which have made
quite controversial choices, cf. Courtois (2014, 2015). Bitcoin could be quite difcult
to x, as it is not always obvious that the right choice will be made by the bitcoin
community, or that they will be made at the right time, and it is simply very naive to
believe that the right choices will naturally prevail. Bitcoin allows researchers to
discover the task of designing an autonomous decentralized nancial system is very
hard. On the one side, it seems that bitcoin have already made the impossible possible:
it works and has known a relative success. On the other side, the ideal of decentralized
crypto currency, which bitcoin has actually created, and the reality of it, are yet very
remote. Yet potentially, bitcoin is good enough as explained in Antonopoulos
(2014). Good enough to achieve some sort of persistent dominant position, cf.
Antonopoulos (2014), Courtois (2014), a sort of self-reinforcing natural monopoly
due to its tremendous popularity and large adoption (the network effects).
bitcoins is like signing a bank check which allows to transfer some bitcoins to a
new owner. These checks are part of the ofcial bitcoin history which is stored
precisely in this blockchain database. Bitcoin is an open protocol in which
anyone can participate. A bitcoin equivalent of a bank account is a certain string of
some 33 characters which is produced using cryptography, which allows the digital
signatures on these checks to be implemented: only the owner of a certain secret
quantity (known as a private key) can spend bitcoins from one account, while
anyone can send bitcoins to that account. All the money transfers ever made in
bitcoin are entirely public, except that in principle we do not know who is the
owner of any given account.
In addition events in the blockchain ledger are hard to counterfeit: participants
in the bitcoin network must spend substantial computational effort in order to
produce valid blocks. Events are added to bitcoin history in increments called
blocks and each block contains about 500 transactions. Adding valid events to
bitcoin history is very much like burning a DVD: requires both certain relatively
costly equipment and to spend energy (electricity). The exact implementation of
this is through solving a certain hard cryptographic puzzle which works like a
lottery and which we studied in detail in Courtois et al. (2014a, b).
This process of manufacturing the (common) bitcoin transaction ledger has an
interesting incentive mechanism: basically participants in this costly process are
rewarded with newly created bitcoins. They have strong incentive to be honest, as
the bitcoins which they earn for participating are only valid if other participants
later conrm their block as being valid and correct. This process is called bitcoin
mining and works very much like a lottery in which the next successive winner
approves a bunch of recent transactions and also the block generated by the pre-
vious winner (miner of the previous block). This is expected to create conditions in
which it is not protable to cheat (e.g. falsify the bitcoin history and spend again the
same quantity of coins). The bitcoin network is expected to police itself, miners not
following the protocol risk that their blocks will be later rejected by the majority of
other miners and such miners would simply not get the reward for which they work.
We refer to Sect. 3 of Courtois (2014) and to Lee Kuo Chuen (2015) for a longer
description of bitcoin. A more detailed technical description can be found in
Antonopoulos (2014) and the primary ofcial bitcoin protocol specication is
available at Technical Specication of the Bitcoin Protocol (2014).
date since when bitcoin has been widely recognized and used as a mainstream
nancial instrument which ordinary people can use.
Bitcoin has also known a gold rush which has been short-lived yet highly
reminiscent of the historical Klondike gold rush in the 1890s. The rapid appreci-
ation of bitcoin in 20132014 and possibility for anyone to mine bitcoins for their
own account has transformed bitcoin, at least temporarily, into a potential
get-rich-quick scheme (Matthews 2014; Mease 2014). In the long run this has not
contributed to bitcoin being taken seriously as a payment instrument and its sub-
stantial volatility (but also usability) are among the most frequently cited reasons
why bitcoin has not known a larger adoption in ordinary commercial transactions
(Fig. 1).
Bitcoin has once achieved market price of more than 1000 USD, after which a
correction followed. In contrast in the last 12 months the bitcoin price have
remained remarkably stable at around 250 USD.
It is also in early 2013 when bitcoin become a major high-tech business topic.
A new type of industry have emerged, bitcoin startups, companies which live
exclusively within and for the bitcoin economy. In particular companies manu-
facturing specialized equipment (ASIC machines) the only purpose of which is to
produce (mine) new bitcoins very efciently, cf. Courtois (2014a). It is also in 2013
that bitcoin has transitioned from a geek amateur community to a more professional
phase with new bitcoins are produced for prot, by a restricted group of bitcoin
miners in which people need to invest money upfront with entry barriers. However,
miners, this including ourselves and our friends, have known highly uncertain and
disappointing returns on their investment.
In this respect, we have at several occasions such as public conferences about
bitcoin, claimed the following conjecture to be true, in practice if not in theory:
Conjecture 2.1 (Courtois) Mining is almost always done at a loss.
Justication 1: One reason for that could be that the investors have been facing an
extremely fast exponential decline in mining protability. In fact for a very long
time in bitcoin history, the income from mining would be divided by two every
month, which is just an incredibly fast decrease unlike for any ordinary investment
ever seen, cf. Sects. 2.12.3 of Courtois (2014). A quick calculation then shows
that the income from mining is not much larger than for example twice the income
from the rst month of mining. This is a very fast decline in protability which
probably will come as a surprise for many investors. In addition there have been
major moral hazards delays and losses due to dishonest ASIC manufacturers, and
some outright scams, and generally an asymmetry of power between small and
large investors, cf. Sect. 2.4 of Courtois (2014) and Appendix of Courtois (2015)
for a detailed discussion and specic examples. Overall investors could very hardly
predict the return on their investment correctly and therefore have rather
overinvested.
Justication 2: We also offer a privacy economics argument: freshly mined coins
provide anonymity services: they have no origin and cannot be traced to the origin
of funds which have been used to purchase mining equipment and pay for elec-
tricity. Furthermore, new bitcoins created can be attributed to cryptographic keys
chosen independently at random and later transferred to other parties privately
(outside of the bitcoin blockchain) without any digital trace-ability for these sec-
ondary transfers. These anonymity services are valuable and we conjecture that
there will always be a certain non-negligible percentage of people who are willing
to mine at a loss. Such miners will contribute to the expansion of the bitcoin hash
rate which will negatively affect mining protability for all miners. It is possible
that some investors will anticipate all this and avoid investing in bitcoin mining,
and there will be adjustments with investors switching their miners off earlier than
planned. However in general many miners are trapped with sunk costs (cost of the
mining hardware paid upfront). Therefore a larger number of rational miners will
inevitably also mine at a loss in order to recover as much money as they can, and
minimize their losses.
This has been a key nearly central question in our work. In Courtois (2014),
Financial Times Videos (2015) it has been estimated that more than a billion dollars
have been invested into purchase bitcoin miners with the intention of bitcoin
mining. This can be seen as a distributed hash infrastracture of bitcoin which
underpins bitcoin and allows it to run. Arguably the bitcoin cryptographic com-
putation power and hash rate is now just incredibly large, cf. Courtois (2014, 2015).
Now the question is, if we put aside the race to acquire a scarce number of new
bitcoins and the speculative bid on their future market price, does this monumental
investment bring additional benets. For example, does it make bitcoin very robust
and secure, so that it could not be broken or abused by some powerful entities. On
the surface is seems that yes, for example in (Sams 2014) we read that:
102 N.T. Courtois
The amount of capital collectively burned hashing xes the capital outlay required of an
attacker to obtain enough hashing power to have a meaningful chance of orchestrating a
successful double-spend attack on the system [] The mitigation of this risk is valuable,
[]
In reality, this protection is very largely illusory and ineffective as we are going
to show in the present paper, cf. also Courtois (2014). In general it is a fallacy to
consider that money currently burnt in hashing serves as an effective protection
against attacks. This is because money at risk, for example in large transactions, can
be substantially larger than the cost of producing a short term fork in the block
chain. It is easy to show that the amount of money needed to commit for-prot
double spending attacks remains moderate and has nothing to do with hundreds of
millions of dollars spent on ASIC miners by investors. Mining is highly centralized
due to the fact that most miner mine in miner pools (Courtois 2014; Rosenfeld
2013) and it is sufcient to hack some pool manager servers in order to command a
substantial fraction of the bitcoin hash network. A lack of correct appreciation of
51 % attacks is a big recurrent problem in bitcoin community, cf. Sect. 6 below. In
addition the current bitcoin specication mandates the so called The Longest Chain
Rule, and there is a number of additional important technicalities which make things
worse and bitcoin even more fragile and more prone to attacks, cf. Courtois (2014,
2015a, b), some of which questions we are going to explain below. We also need to
stress that bitcoin could implement additional integrity protections on the top of
existing ones, some such ideas are outlined in Sect. 7 of Courtois (2014).
The current bitcoin has been designed to be truly decentralized and function in an
asynchronous way even in highly imperfect network conditions. The key under-
lying principle which allows to achieve this objective is the Longest Chain Rule of
Satoshi Nakamoto (Nakamoto 2008). It can be stated as follows:
1. Sometimes we can have what is called a fork: there are two equivalent solutions
to the cryptographic puzzle, or two equally valid blocks are mined.
This happens about 1 % of the time, cf. Table 1 in Courtois (2014b).
2. Different nodes in the network have received one of the versions rst and
different miners are trying to extend one or the other branch. Both branches are
legitimate and the winning branch will be decided later.
3. The Longest Chain Rule of Nakamoto (2008) says that if at any later moment
in history one chain becomes longer, all participants will switch to it
automatically.
With this rule, Satoshi have shown (Nakamoto 2008) that that bitcoin should
quickly reach a consensus. Importantly this rule is also how bitcoin attempts to
solve the problems of 51 % attacks and fraud or double spending.
Features or Bugs: The Seven Sins of Current Bitcoin 103
We are now going to explain why this rule is problematic. In fact this same
consensus mechanism in bitcoin is a solution to two entirely distinct problems:
1. It allows to decide which blocks obtain a monetary reward and resolve
potentially arbitrarily complex fork situations in a simple, elegant and con-
vincing way.
2. It is also used to decide which transactions are accepted and are part of ofcial
history, while some other transactions may be rejected.
Overall one single mechanism to rule both blocks and transactions is rather a
mistake. For example it violates one of a well-known principles in security engi-
neering: the principle of Least Common Mechanism (Saltzer and Schroeder 1975),
cf. also Courtois (2009). We need to observe that the transactions are generated at
every second. Blocks are generated every 10 min. In bitcoin the receiver of money
is kept in the state of incertitude for far too long and this with no apparent
reason. The current bitcoin currency produces a situation of discomfort and
dependency or peculiar sort. Miners who represent some wealthy people in the
bitcoin network, are in a privileged position. Their business of making new bitcoins
has negative consequences on the smooth processing of transactions. It is a source
of instability which makes people wait for their transactions to be approved for far
too long and delays their acceptation cf. Courtois (2014), Financial Times Videos
(2014). At then end of the day this ends up violating also another very widely
accepted principle of security engineering: the principle of Network Neutrality. We
claim that it should be possible to design a better and faster mechanism in bitcoin,
cf. Courtois et al. (2014), Courtois (2014).
In crypto currencies, the central bank and the monetary policy which is expected to
regulate the number of coins in circulation has been simply replaced by a relatively
simple algorithm. In traditional at currencies, the main objective of a successful
monetary policy is to control the inflation, insure nancial stability and overall
healthy functioning of the economy. In crypto currency we also have that, except
that the original bitcoin monetary policy is quite peculiar. It is clearly the one thing
which is the most frequently modied by designers of various bitcoin clones with a
whole array of interesting variants which generate new coins at different speed
according to some pre-determined scheme.
Interestingly in crypto currency and unlike in traditional currencies, this algo-
rithm or monetary policy plays a sort of dual role. It surely regulates the bitcoin
monetary supply and the bitcoin economy, but it also has a security function.
Production of new coins in an incentive for miners to behave well and not abuse the
104 N.T. Courtois
network, and if this incentive is removed, the network will be less secure against for
example 51 % or double spending attacks (our primary focus). In bitcoin the total
number of bitcoins ever to exist is bounded by 21 million, which property has been
very frequently criticized. In Wired Entreprise (2013) J. Kroll from Princeton
university explains This limited-supply issue is the most common argument
against the viability of the new currency. We refer to Sect. 5 of Courtois (2014) for
a detailed discussion. A xed monetary supply implies that the income from mining
is bound to decline substantially in the future. This has alone has serious security
consequences as explained also in Wired Entreprise (2013) there will be no
incentive for people to keep contributing processing power to the system [] If the
miner reward goes to zero, people will stop investing in miners,. Then the hash
rate is likely to decrease and bitcoin will no longer benet from a protection against
double spending attacks.
Moreover the author explicitly says that the problem is NOT solved by trans-
action fees and says: [] You have to enforce some sort of standard payment to the
miners, [] change the system so that it keeps creating bitcoins. In a paper pre-
sented at WEIS 2013 and co-authored by Kroll (2013). this is presented as a clear
dilemma, either break the monetary policy or increase the fees. Yet increasing the
fees is something which is likely to destroy bitcoin. This is brilliantly explained by
Sams (2014). The argument is that basically sooner or later deflationary curren-
cies and growth currencies will be in competition. Then all the other things
being more or less in equilibrium, in deflationary currencies most of the prot from
appreciation will be received by holders of current coins through their appreciation.
Therefore less prot will be made by miners in these currencies. However miners
control the network and they will impose higher fees. In contrast in growth coins,
there will be comparatively more seignorage prot and it will be spent on hashing.
Miners will make good prots and transaction fees will be lower. Thus year after
year people will prefer growth currencies due to lower transaction fees.
Overall we see that this is crucial question of how the cost of the infrastructure
necessary for the maintain a digital currency is split between new adopters (which
pay for it through appreciation) and users (which pay through transaction fees). It is
obvious that there exists an optimal equilibrium between these two sources of
income, and that there is no reason why the creator of bitcoin could possibly get it
right. Serious adjustments should become necessary in the future.
There is yet another argument: it is possible to believe that bitcoin will appreciate so
much that halving the miner reward (currently every 4 years in bitcoin) will be
absorbed by an increase in bitcoin price. We claim that this is unlikely. This is
mainly because the bitcoin adoption has been stable in the recent years and
sometimes even declined (cf. Sects 2.5 and Fig. 9 in Courtois (2014). Therefore we
Features or Bugs: The Seven Sins of Current Bitcoin 105
nd it very hard to believe that it is going to double every 4 years [this would be
very fast] and even less it is expected to double by sudden jumps at the boundaries
of the intervals arbitrarily decided by the creator of bitcoin.
The overall conclusion is that it is easy to see that the bitcoin current restricted
monetary supply is a self-defeating property on at least two accounts:
1. If bitcoin is limiting the monetary supply beyond what is reasonable, and if as
a result of this bitcoin economy suffers from excessive deflation, bitcoin
adopters are likely to circumvent this limitation by using alternative coins. This
is likely to erode the dominant position of bitcoin.
2. With time the miner reward in new bitcoins per block decreases and tends to
zero. Then actual cost (in bitcoins) of manufacturing each new block will also
tend to zero, and the price tag (in bitcoins) for creating a fork in bitcoin
blockchain should also tend to zero, while the amount of money (in bitcoin) at
risk of double spending in each block, does not decrease. Then with time it
becomes increasingly easier and more protable to commit fraud in bitcoin
blockchain.
The only solution to this problem we are aware of, is to reform the bitcoin
monetary policy.
wiki, does even consider that there are any real problems in bitcoin. The section
about 51 % attacks does NOT even get into the part entitled Might be a problem.
It appears in the following part entitled Probably not a problem, cf. Ofcial
Bitcoin Wiki (2014) which many people would maybe not read, why bother if it
probably is not a problem?
Satoshi on 51 %. The very serious misconceptions on this topic go straight back to
the original paper of Satoshi. The inventor of bitcoin describes a greedy attacker
being able to assemble more CPU power than all the honest nodes, see Sect. 6 in
Ofcial Bitcoin Wiki (2014). The attacker is also portrayed as having considerable
wealth which he would endanger by engaging in the attack. It is clearly suggested
that the attack would have little to gain and a lot to lose from being dishonest.
Satoshi has invented a term CPU power and always explicitly states the prin-
ciple of one-CPU-one-vote. In reality nowadays it is rather one-ASIC-one-vote.
A reasonable term is hash power commonly measured in GH/s where one hash
per second is a capacity to hash one block header. cf. Courtois (2015).
Control versus Ownership. In general a very common mistake is to claim that
51 % attacks occur when the attacker owns or is in possession of 51 % of all the
hash power. This mistake again goes back to Satoshi (Nakamoto 2008) and is
committed again and again by major Bitcoin experts and evangelists, cf. for
example Cawrey (2014), Perry (2012). The Ofcial Bitcoin Wiki (2014) has a
subsection with this super highly misleading title: Attacker has a lot of computing
power. Quite happily just below they correct it and say it is rather about temporary
control not ownership.1
Most people fail to see that the key problem is the control (not ownership) of
hash power for the purpose of mining blocks, and this can be a lot easier and
cheaper. For example the attacker could be one single malicious pool which gathers
more than 51 % of hash power under his sole control (controlling but not owning
hash power). It is worth noting that this situation has already happened at least once
in both Bitcoin, Litecoin and Dogecoin Courtois (2014).
Another serious mistake is to consider that control is exclusive. For example in
the Abstract of his paper Satoshi writes: As long as a majority of CPU power is
controlled by nodes that are not cooperating to attack the network theyll []
outpace attackers. This is not correct in general. The key point is that control is
NOT exclusive, both the miners and the attacker can have some control on the
mining process. So a majority of CPU power is controlled by nodes as Satoshi
says and also at the same time it could be controlled by the attacker in a more or less
subtle ways, cf. for example Sect. 8.3 in Courtois (2014).
1
They explain that the exact scenario is when he controls more than 50 % of the networks
computing power and they make it clear it can be temporary: for the time that he is in control.
However almost to make things worse again, this ofcial wiki at numerous places refers to another
article about Bitcoin attacks written for more general audience (Perry 2012) which again claims
that 51 % attacks are so amazingly cost-prohibitive to perform.
Features or Bugs: The Seven Sins of Current Bitcoin 107
On Visibility. Many people stress that that 51 % attacks, and for example double
spending events would be visible to anyone to see on the public blockchain
(Cawrey 2014). This is simply not true, the bitcoin blockchain does NOT record
double spending events, it rather hides them and would show only one transaction
out of two, cf. also Decker (2014).
2
This decision also has denitely infringed on the initial intentions of Satoshi explicitly stated in
Sect. 6 of his paper (Nakamoto 2008) where he explains that the fact that a block provides a
monetary reward for the creator of the block is something which adds an incentive for nodes to
support the network. This incentive is now broken.
108 N.T. Courtois
shown to be broken insecure, we can blame either the real world which does not
satisfy our assumption, or the designers and engineers of bitcoin which have not
been able to design a secure system based on this assumption. In other worlds we
could determine without ambiguity who is to blame. In this respect Satoshi shows a
bad example of not being clear about what his assumption is and yet explicitly
several times claiming that his system is secure:
A. For example in the abstract of his paper (Nakamoto 2008) Satoshi says that he
assumes that majority [] are not cooperating to attack the network. Here
Satoshi claims the system is secure under this assumption, which security claim
is not true as people can easily be part of an attack without cooperating (as
already explained above).
B. Now in the conclusion of his paper Satoshi again claims that the system is
secure if honest nodes control a majority of CPU power. which is a very
different and STRONGER assumption than A. above: nodes could be not
honest and deviate from the protocol for fun or for prot in a variety of creative
ways without cooperating with any attacker.
Does this stronger assumption make that bitcoin becomes secure? Of course
not, the security result claimed by Satoshi is wrong again if you take it literally:
even if honest nodes control a majority of hash power, because the control is
not exclusive, bitcoin can still be attacked.
On The Honest Option It is nonsensical to claim that the attacker would prefer to
behave honestly, and that it is more protable to play by the rules (Nakamoto
2008). This is claimed by Satoshi on the grounds that the attacker should be able to
generate new coins which would be an honest way to use his hash power, see
Sect. 6 of Nakamoto (2008). In reality, in almost all bitcoin mining scenarios
known to us, the attacker does NOT control the money from mining: he does NOT
have the private keys used for mining. This is because the whole process of mining
requires exclusively the public keys. It would simply be an unnecessary mistake
for any miner or for any mining pool to have the private keys around to be stolen by
the attacker which targets the mining process. Therefore the attacker typically does
NOT have an honest option at all.3
On Percentages. The notion of 51 % attacks is also very highly misleading
because presenting the hash power as a percentage gure does NOT make sense
because the hash rate is measured at two different moments. Therefore the pro-
portion of hash power used in attack is NOT a number between 0 and 100 %. It
could in particular be larger than 100 %. In fact the relative hash power at one
moment can be easily of the order of 500 % and many times bigger than a few
minutes later, cf. Courtois (2014) for an actual historical example.
3
In contrast Satoshi have claimed that he always has such an option, in Sect. 6 of Nakamoto
(2008) we read: he would have to choose between using it to defraud people by stealing back his
payments, or using it to generate new coins.
Features or Bugs: The Seven Sins of Current Bitcoin 109
Miners versus Adopters versus Pools. It was also sometimes wrongly assumed
that the bitcoin adopters are more or less the same as miners, they own the devices
and the computing power cannot change hands very quickly.
It is in general not sufcient to trust the pools not to be malicious. Attacks could
be executed without the knowledge and consent of these companies by a single
rogue developer.
Bitcoin Versus Competitors. Many bitcoin adopters did not anticipate that in the
future bitcoin will have to compete with other crypto currencies and that hash
power could instantly be moved from one crypto currency to another, these
questions have been studied in detail in Sects. 1011 of Courtois (2014).
Attacks could also operate through re-direction of hash power in bulk to another
pool, such attacks are studied in Sects. 8.28.3 of Courtois (2014) and in Courtois
(2015).
In the same way, people wrongly assume that bitcoin achieves very substantial
computing power which no one can match, which is still the case today however it
is quite problematic to see if this will hold in the future.
Rented Cloud Miners. Attacks can be facilitated by the fact that an increasing
fraction of all available computing power in bitcoin exists in the form of rented
cloud miners. This situation is due to several factors. Investing in wholly owned
mining equipment has been excessively risky. This is both due to the impossibility
to know if and when miners will effectively be delivered (cf. Appendix of Courtois
(2014, 2015) and due to the price volatility. Investing in short term rented mining
capacity is clearly less risky. Another reason is that some large investors may have
over-invested in large bitcoin mining farms consuming Megawatts of electricity
(we know from the press that such facilities have been built in Sweden, USA, Hong
Kong, China, Georgia, etc.) and now they want to rent some parts of it in order to
get immediate cashflow and return on their investment. Furthermore renting hash
power leads to the possibility of running for-prot attacks with cooperating peers
who may or not be aware of participating in an attack, see Sect. 7.9 in Courtois
(2014) which describes a real-life company which allows to facilitate double
spending attacks and proposes to miners to rent their computing power to others for
a small reward premium.
There is some sort of intuitive understanding in the bitcoin community that the
Longest Chain Rule solves all problems in this space, and there is simply no
problem, or if there is, it is probably not very serious. In our experience very few
bitcoin enthusiasts are willing to admit that the brilliant creator of bitcoin could
have created a system which has serious security problems.
110 N.T. Courtois
Fig. 2 A simple method to commit double spending. The attacker tries to produce the second
chain of blocks in order to modify the recipient of some large transaction(s) he has generated
himself. Arguably and under the right conditions, this can be quite easy to achieve. The attack is
clearly protable and the only problem is the timing: to produce these blocks on time
For example many authors claim that the problem has already been xed: and that
the x is to wait for 6 conrmations, cf. Perry (2012). In fact if a lot of money is at
stake in a large transaction (or in many small transactions) it is possible to see that a
larger attack could be mounted, e.g. as in later Fig. 2. In general as the money at
stake involved in each block is likely to grow in the future, the risk will also increase
and we agree with Ofcial Bitcoin Wiki (2014) to say that no amount of conr-
mations can x this problem. More conrmations are needed for larger transactions.
In this section we have shown that 51 % attacks have been historically extremely
poorly understood and very few sources get it right. It clearly is a complex problem
which involves a variety of attacks and threats which deserve to be taken seriously.
The key observation is that the attacker does NOT need to be very powerful, on
the contrary. The most shocking discovery is that anyone can commit such fraud
and steal money. They just need to rent some hashing power from a cloud hashing
provider. This needs only to be done only for a very short time, like less than 1 h,
for example through redirection (man-in-the-middle attack) of hash power which is
in the physical possession of other miners but under logical control of extremely
few pool manager servers. In a competitive market they do not need to pay a lot for
this. Not much more than 25 BTC per block. This is because miners do not mine at
a loss, or maybe at a small loss cf. Conj. 2.1 page 4 and therefore the inherent cost
of mining one block should be just about 25 BTC. The attacker then just needs to
temporarily displace the hashing power from other crypto currencies for a very
short period of time which is easy to achieve by paying a small premium over the
market price. We should note that rapid displacement of hash power happens every
day in crypto currency community, see Sects. 1011 in Courtois (2014).
For example here is what happened to the UNO hash rate in 2013: it has declined in
a very substantial way each time the miner reward has been decreased.
Similarly, the hash power has been moving from Dogecoin to Litecoin in very
substantial ways. This was due to the Dogecoin monetary policy which has
decreased the mining incentive. This resulted to a progressive transition in several
steps from a situation in which both currencies had a nearly-equal hash rate and no
currency could convincingly attack the other, towards a situation where a fraction of
hash power used by Litecoin miners could be used to abuse the users of Dogecoin
and double spend, in a way steal someones coins.
It is important to note that shortly after we have written about this threat, the
founder of Litecoin have proposed a x to the Dogecoin community which they have
later adopted, in the form of so called merged mining, which indeed xes this
problem. In particular Josh Mohland, one of the key architects behind Dogecoin have
agreed with us that without a reform Dogecoin would basically face certain death, at
least in the sense of double spending attacks, cf. Higgins (2014) (Figs. 3 and 4).
Fig. 3 The growth and decline of UNOBTANIUM hash power in 2012/2013. we observe sudden
jumps and periods of intensive mining followed by steady decline in days following each block
halving dates in the hash power
Bitcoin has this anonymous founder syndrome. There were numerous security
scandals in which a lot of bitcoins have been stolen (Decker 2014). Alt-coins are
much more vulnerable as shown above and in Courtois (2014). All this can create
some uneasy feelings. In general it is a common misconception to believe that open
source code is most probably secure. We dont believe this to be correct Anderson
(2005), Courtois (2009) in general. In bitcoin we need to ask ourselves a number of
questions:
1. Why should open source code be secure if very little or insufcient effort is
typically made in order to make it secure?
2. In the traditional industry developers are paid, and seem to never get the security
right: we have endless security breaches and alerts. There is little hope that
bitcoin developers can do better.
3. For example the Dogecoin developers and promoters did not want to admit any
responsibility for their actions. They have said that Dogecoin was never
intended to function as a full-fledged transaction network, citing (Higgins
2014) and that yes it was going towards a certain death, mostly and exactly for
reasons exposed in our papers, Can we hope that bitcoin developers will be
more responsible?
4. Actually open source software is not more secure than closed source according
to experts (Anderson 2005). Moreover quite possibly, on the contrary, it will be
less secure. Malicious developers are more likely to work on such source code
than honest developers. This is because rogue developers will be motivated by
prot, while honest developers may see little incentive to work on this code.
Accordingly, a recent paper (Maese 2014) takes a view that:
The open-source nature of the developer population provides opportunities for frivolous or
criminal behavior that can damage the participants in the same way that investors can be
misled by promises of get rich quick schemes. [] Regulations could ensure that cyber-
security requirements are engineered into the code [] One of the biggest risks that we face
[] in the digital age [] is the quality of the code that will be used to run our lives.
More generally we need to address the question of how an open source system
such as bitcoin nevertheless hope to be secure and trusted.
114 N.T. Courtois
We recall one of the most important principles of computer security and modern
security at large, the open design principle (Saltzer and Shroeder 1975). On the
surface, bitcoin seems to be an open design. We have a white paper, the original
paper of Satoshi (Nakamoto 2008) and more detailed specication (Todd 2014) and
source code (Nakamoto et al. 2014).
A closer examination reveals that the open source and open design are two
different things and the open source model suffers from some major problems. An
open design should mean that we should NOT use any cryptography standards of
questionable origin, or run source of code of unknown origin. Unhappily a lot of
code and also the cryptography in bitcoin has obscure origins. Bitcoin cryptography
is clearly a closed design. 100 % of the cryptography standards in bitcoin have been
developed entirely behind closed doors at the NSA, and there is some ambiguity
about to what extent these standards are secure.
As we have already explained, bitcoin violates the principles of open and trans-
parent design because 100 % of the cryptography standards on which it depends
have been developed entirely behind closed doors. However this is also the case for
most industry rms. Is cryptography in bitcoin in any way less good than the
cryptography used by major security vendors? Yes it is!
Features or Bugs: The Seven Sins of Current Bitcoin 115
Bitcoin uses elliptic curve cryptography. Here is what Neal Koblitz himself, one
of the two inventors of this form of cryptography, and member of advisory board of
Ethereum meant to be a successor of bitcoin, have once written about untested
cryptography assumptions:
in the real world if your cryptography fails, you lose a million dollars or your secret agent
gets killed. In academia, if you write about a cryptosystem and then a few months later nd
a way to break it, youve got two new papers to add to your rsum! Neal Koblitz, cf.
Koblitz (2007).
y2 = x3 + 7 mod p
This sort of bizarre curve remains ofcially unbroken in the open research
community, in spite of the fact that tens of academic papers are published each year
about attacks related to small integers in public key cryptography. This elliptic
curve is characterized by the so called small class number which some
researchers suspect to be less secure than general curves, see Sects. 5.1 and 5.3 in
Galbraith and Smart (2014). cf. also Bernstein et al. (2014). The bitcoin elliptic
curve has the lowest jDj of all known standardized elliptic curves, cf. Bernstein and
Lange (2014) and therefore it is potentially the least secure. Following Bernstein
and Lange (2014) such curves allow slight speedups for discrete log attacks
however the literature does not indicate any mechanism that could allow further
speedups. To summarize no really serious attack is on such curves is known.
However in cryptography there has always been a tremendous level of suspicion
against such very special cryptographic objects. History have taught us that in
cryptography special usually means broken.
Koblitz curves in characteristic p were invented by Gallant, Lambert and Van-
stone cf. Galbraith and Smart (2015). and was initially recommended by the
Standards for Efcient Cryptography Group (secg.org) which is an industry con-
sortium created in 1998 by the Canadian Certicom company in order to popularize
efcient ECC solutions. and it is recommended in ANSI X9.63 version from 2011.
It is implemented in OpenSSL but not for example in GnuTLS. It is not in general
widely used in the industry, because simply most academic cryptography experts
116 N.T. Courtois
would not trust and would never recommend this peculiar curve secp256k1 as used
in Bitcoin.
Timely Denial. More importantly, SECG itself does no longer recommend this
elliptic curve. Here is what Dan Brown, the SECG chair has written in September
2013:
I did not know that BitCoin is using secp256k1. I am surprised to see anybody use
secp256k1 instead of secp256r1.
We refer to Topic: NSA (2897) for more details. The only correct way to
interpret this statement is that this elliptic curve is NOT supported and not rec-
ommended by the very people who have standardized it in the rst place. It should
no longer be used in bitcoin and no one should use it. It is very much like using
Windows XP today in 2015, even though it is no longer supported and Microsoft
and using it is simply dangerous.
It is not difcult to switch to another elliptic curve and such a change can happen
overnight without any problems. It would take 5 s to implement this change in
current software and make it also accept the signatures with the old elliptic curve for
some time.
It might seem that such a change would be ineffective because of the
co-existence of new and old signatures. On the contrary, it would be immediately
effective. All the moneys transferred to new addresses would be safe, EVEN IF the
older Koblitz curve was badly broken. Therefore this change would immediately
protect money of anyone willing to create a fresh bitcoin address, and abandon their
old address, which is easy and could be automatically done by a majority of
upgraded bitcoin software (such large scale address updates have already been done
many times in bitcoin community without any problems).
There is also a solution for individual users. Yes, users of bitcoin can also x this
problem themselves, even today. They should basically never reveal their public
key (the bitcoin address is a hashed version, it does NOT reveal their public key)
and always destroy this key (never use it again) each time it is used, and send the
remaining balance to a new freshly created address.
Thus the attackers who are able to break secp256k1 keys will have much less
time: instead of having many months or maybe years to break it, they need to do it
Features or Bugs: The Seven Sins of Current Bitcoin 117
instantly within a few seconds or all the money at this address will be gone forever.
Unhappily many existing bitcoin applications such as Bitcoin core do NOT yet
facilitate implementing this sort of policy.
Bitcoin has a number of features and properties which are sometimes presented as
very interesting and positive. In fact they are closer to engineering mistakes. Most
of these features have been blindly copied by other currencies, so called alt-coins
which typically change only the monetary policy and leave other features
unchanged. Naive customers are presented with software systems which are
claimed to be payment systems and currencies which creates expectations that they
will be relatively stable and that they are protected against attacks. In reality serious
problems are programmed right there in the DNA (the source code) of great
majority of crypto currencies. Small details in the source code can make very big
difference, for example the choice of the elliptic curve used to secure bitcoin
transactions.
In our work we show that the question of 51 % attacks are almost never correctly
understood and most crypto currencies simply do NOT yet have a good protection
against major attacks, cf. Sects. 67.2. In addition sudden jumps and rapid phase
transitions in miner reward are programmed at xed dates in time which can lead to
the decline of some currencies, cf. Sect. 7.2 and Courtois (2014). More importantly,
hash power redirection attacks can just temporarily displace the hash power or
abuse miners without their knowledge, cf. Sect. 6 and Courtois (2014). We dis-
covered that the Longest Chain Rule does not solve the problems of bitcoin con-
sensus in an appropriate way. It is probably OK for deciding for which blocks
miners will obtain a monetary reward However there is no reason why the same
exact slow and unstable mechanism would also be used to decide which
transactions are valid. This is NOT a feature, it is a bug, An engineering mistake
on behalf of Satoshi Nakamoto, the founder of bitcoin. It affects not only the
security of bitcoin but also its usability: it makes transactions unnecessarily slow,
especially for larger transactions which require more conrmations. Bitcoin could
potentially be a lot faster, cf. also Financial Times Videos (2014).
In general, all the 51 % and double spending vulnerabilities can get substantially
worse with time see Sects. 5 and 7.2. Here rewarding the creators and early
adopters conflicts with allowing the miners a decent income later on. The current
monetary policy is another very major self-defeating property of many existing
crypto currencies. Accordingly the 51 % attacks are somewhat bound to get worse
with time: the cost (in bitcoins) of orchestrating a double spending attack on bitcoin
is likely to decrease, while the money at risk in a successful crypto currency is
likely to increase with time, cf. Sect. 5.1. We agree with Wired Entreprise (2013) to
say that crypto currencies should keep allowing miners to make some serious
income in order to make attacks more costly.
118 N.T. Courtois
Acknowledgments We thank Xavier Alexandre, George Danezis, Gerald Davis, Pinar Emirdag,
Michael Folkson, Clment Francomme, Pawel Krawczyk, Jean-Jacques Quisquater, Guangyan
Song, Tim Swanson and John Shawe-Taylor for their extremely helpful suggestions, observations
and comments.
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(2014b). https://en.bitcoin.it/wiki/Double-spending
Perry, D.: Posted as GUEST: Bitcoin Attacks in Plain English. http://codinginmysleep.com/
bitcoin-attacks-in-plain-english/. Accessed 5 Oct 2012
Rosenfeld, M.: Mining pools reward methods. Presentation at Bitcoin 2013 Conference. http://
www.youtube.com/watch?v=5sgdD4mGPfg
Saltzer, J.H., Schroeder, M.D.: The protection of information in computer systems. In:
Proceedings of the IEEE, 63(9), 12781308 (1975)
Sams, R.: The Marginal Cost of Cryptocurrency. Blog entry at cryptonomics.org. http://
cryptonomics.org/2014/01/15/the-marginal-cost-of-cryptocurrency/
Swanson, T.: What Dogecoin Must Do to Survive. http://www.coindesk.com/what-dogecoin-
must-do-survive/. Accessed 25 May 2014
Technical Specication of the Bitcoin Protocol: https://en.bitcoin.it/wiki/Protocol_specication
Todd, P.: Why I Just Sold 50 % of my Bitcoin: GHash.io. http://daytradernews.com/bitcoin-
trading/why-i-just-sold-50-of-my-bitcoin-ghash-io.html. Accessed 13 June 2014
Wired Entreprise: http://www.wired.com/wiredenterprise/2013/11/bitcoin-and-deation/all/.
Accessed 25 Nov 2013
Wong, J.I.: Gavin Andresen Rejects Bitcoin Centralisation Concerns at Web Summit, 6 Nov 2014.
http://www.coindesk.com/gavin-andresen-rejects-bitcoin-centralisation-concerns-web-summit/
120 N.T. Courtois
Author Biography
Adam Hayes
Abstract Bitcoin has ushered in the age of blockchain-based digital currency sys-
tems. Secured by cryptography and computing power, and distributed across a
decentralized network of anonymous nodes, these novel systems could potentially
disrupt the way that monetary policy is administeredmoving away from todays
human-fallible central bankers and towards a technocratic, rules-based algorithmic
approach. It can be argued that modern central banks have failed to stem macro-
economic crises, and may have, in fact, exacerbated negative outcomes by incen-
tivizing excessive risk-taking and moral hazard via unconventional monetary tools
such as quantitative easing and negative interest rates. A central bank typically serves
three primary functions: to issue and regulate the supply of money; to serve as
clearinghouse for settlement of payments transactions; and to serve as lender of last
resort. Could a digital currency system serve as a rational substitute for a central bank?
This perspective paper examines that question, and then suggests that indeed it could
be plausible. While Bitcoin in its current form will prove to be inadequate to function
as monetary authority, I put forward what an operative case could resemble.
Fluid began to flow through plastic tubing, from one small tank to the next, as the
rhythmic hum of hydraulic pumps whirred in the background. The economists who
had gathered at the London School of Economics quieted down. Graduate student
Bill Phillips, who would later gain notoriety for describing the relationship between
inflation and unemployment, stood at the controls of the six-and-a-half foot by ve
foot analogue machine he had himself built. Phillips had arrived at the LSE from his
home in New Zealand by way of Asia, where he was held prisoner in Java by the
invading Japanese forces for three-and-a-half years. Now, in 1949, he adjusted
the slider for the tax rate, set various dials, and ddled with the valve that balanced
A. Hayes ()
University of Wisconsin-Madison, Madison, USA
e-mail: hayes2@icloud.com; hayes2@me.com
the budget; moments later The Phillips Machine gurgled and produced an estimate
for the unemployment rate and interest rates, supposedly within a 2 % margin of
error (Phillips and Leeson 2000). Later dubbed MONIAC, it was an achievement in
technology over fallible human minds in formulating monetary policy and
informing central bankers to precisely what action to take upon observing the
economy.
Since the Phillips Machine was rst turned on, there has been a decline in the use
of simple technocratic decision-making for monetary policy. Central banking has
become much more nuanced, opaque, and complex as economies have grown larger
and more intertwined. The nuance and complexity has also brought with it
uncertainty regarding policy decisions which manifests itself in nancial markets in
the form of volatility: Will the bank raise interest rates? By how much? When will
they do it? Why was a specic word used in a statement by the Bank versus the
word they have usually used? Every last shade is scrutinized. Central bankers have
shifted the conceptual basis of monetary affairs away from rules and standards such
as gold or xed exchange rates, and toward an evolving relationship with the
public, rooted in sentiments and expectations (Holmes 2009).
The debate over whether central banks should be governed by rules, or instead by
achieving a set of goals whatever way possible is an old and ongoing one. If market
participants incorrectly judge how interest rates will change, or if the central bank
surprises the market by changing rates contrary to expectations, market fluctuations
could increase. This applies to both how often rates are changed and by how much.
In fact, empirical research has shown that too much tinkering with interest rates can
produce negative economic outcomes (Kydland and Prescott 1977).
Policy think-tanks have also voiced favor for rules-based monetary policy. In
February 2015, the Heritage Foundation commented that an explicit monetary
policy rule will greatly improve transparency and predictability, a belief echoed
stridently at the November 2015 monetary policy conference hosted by the Cato
Institute.1 http://www.cato.org/research/banking/rl-monetary-policy.html.
While pneumatic tubes and mechanical dials are relics, sophisticated algorithms
spanning silicon and optical bre have replaced them. In this digital age, can cutting
edge technology allow monetary policy decisions to function in technocratic manner,
and bring with it the potential for stability that some level of certainty brings to markets?
For simplicity, I take the position that technology today can, indeed, produce
such a resultbut at the same time I am not advocating that this decision falls on
the correct side of the debate over a rules-based policy being most favorable.
Rather, I posit that a technology-driven rules-based system can exist within the
framework of a decentralized,digital currency system, even if such a framework
proves to be inferior to centralized at banking in terms of effectiveness, and for
any number of reasons.
1
http://www.heritage.org/research/reports/2015/02/why-congress-should-institute-rules-based-mone-
tary-policy.
Decentralized Banking: Monetary Technocracy 123
It should also be made clear that technology, in and of itself, is not sufcient to
promote stability given a set of explicit rules. Algorithmic (high-frequency) trading
rms are largely thought to have contributed to recent flash crashes (Kirilenko et al.
2015), and have also caused the public to distrust market participants (see Michael
Lewis Flash Boys). At the same time proponents of algorithmic trading cite evidence
that the technology actually increases market efciency and liquidity (Boehmer et al.
2014). More empirical work is needed to resolve this emerging discussion.
Regardless, there are bound to be both positives and negatives for any techno-
logical intervention, and reducing the potential negatives should be paramount. Of
course, many of the algorithms employed in high-frequency trading are kept secret
and proprietary, so it is unclear whether failures caused by such systems are the
result of the technology itself or manmade flaws in the code. Any algorithmic
approach to central banking must be both robust and transparent so that any
technical errors can be easily identied and corrected.
Modern day central bankers face decisions and take actions which are much more
complex than their predecessors (QE, negative interest rates, bailouts), making them
potentially more vulnerable to mistakes, miscalculations, and unintended
consequences. Their core mandatesnamely to maintain price stability and low
inflationhowever, remain intact. Is it possible to turn some of the core roles of
central bankers over to technology?
Certain facets of monetary policy already follow a systematic approach (Clarida
et al. 1998). The Taylor Rule, for example, informs central bankers how they
should change nominal short-term interest rates in response to changes in inflation
and GDP output. One version of the Rule is:
it = t + rt* + t *t + y yt y*t 1
In this equation, it is the target short-term rate (e.g. the federal funds rate in the U.S.),
t is the rate of inflation as measured by the GDP deflator, t * is the target rate of
inflation, rt* is the assumed equilibrium real interest rate (or neutral rate), yt is the change
in real GDP, and yt* is the change in potential GDP output, as determined by a linear
trend. Taylor proposed that the sensitivities of each term () should be 0.50 (Orphanides
and Wiland 2008). Thus, given some macroeconomic data and observations, a certain
lever of economic policy will be pulled to the specied setting.
Orphanides and Wieland (2008) nd that, indeed, this sort of systematic
rule-of-thumb response predominantly explains how the Federal Reserve Open
Market Committees (FOMC) decision-making has been characterized over the past
decades. Even if the individual decision makers or committees formulating these
responses overtly deny that they are following such a heuristic, the outcomes
(incidentally or not) show otherwise.
124 A. Hayes
2
Cryptocurrencies today are based on a blockchain data structure, which is essentially a distributed
ledger system. The technical details of Bitcoin, cryptocurrencies and Blockchains are beyond the
scope of this chapter.
Decentralized Banking: Monetary Technocracy 125
While it has been made apparent that Bitcoin in its current form is likely a poor
candidate to operate as an important global reserve currency, a system that builds
off of its core technologythe blockchainmay in fact be a viable use case.
Despite its shortcomings, Bitcoin has proven itself useful with respect to aspects
of the concept of money. It has established that a conceptually digital money-form
can be an acceptable store of value and a means of payment, both crucial features of
any currency (Ingham 1996; Bamert et al. 2013).
A currency needs to have societal trust in its security and delity.
Blockchain-based cryptocurrencies have exhibited recognition of so-called trustless
trust. As a distributed network, Bitcoin transactions have never been compromised
or hacked and a bitcoin has never been forged or counterfeited.3 A well-understood
consensus mechanism amongst a network of anonymous and far-flung nodes has
shown that a central authority or overseer is not a necessary requirement.
For a digital currency to operate as monetary authority, it must at the very least
satisfy the requirements of being money. Aristotle, in ancient times, proposed four
characteristics needed for something to be a good form of money (Smithin 2002):
1. It must be durable. Money must stand the test of time and the elements. It must
not fade, corrode, or change through time.
2. It must be portable. Money must hold a high amount of worth relative to its
weight and size.
3. It must be divisible. Money should be relatively easy to separate and re-combine
without affecting its fundamental characteristics, i.e. it should be fungible.
4. It must have intrinsic value. This value of money should be independent of any
other object and contained in the money itself.
Does a digital currency fulll these criteria? Taking Bitcoin as the general
example, it is durableits security is iron-clad and its existence is permanent in the
blockchain data structure without any degradation. It is portableit can be accessed
from any internet connected computer or mobile device. It is divisibleone bitcoin
can be broken down to eight decimal places (the smallest such unit known as a
satoshi), and it is fungible. It has intrinsic value.
This fourth point warrants some elaboration. Some have asserted that Bitcoin has
no intrinsic value at all; that it has any market price is solely due to fleeting social
popularity and the hope of speculators (Yermack 2013; Hanley 2013; Woo et al.
2013; Polasik et al. 2014).
Hayes (2015a), however, has demonstrated that Bitcoin does have some sort of
intrinsic value, directly related to its cost of production. In other words, it behaves
much like a commodity produced in a competitive market: electricity goes in and
bitcoin comes out. If the average cost of production decreases, producers will offer
their product in the market at lower and lower prices, in competition with each
other, until marginal cost approaches marginal product (Hayes 2015b). Therefore, it
3
Certain hacking events or theft have compromised services that use Bitcoin, such as Mt. Gox, but
never Bitcoin itself.
126 A. Hayes
decades across various schools of thoughts ranging from the Monetarists to the
Austrians (Kotlikoff 2009). Proponents of full-reserve banking argue that not only
could such a monetary system function, but that it would also eliminate the risk of
bank-runs, bailouts of the nancial sector, and increase macroeconomic stability
(Rothbard 1974). In the wake of the 2008 nancial crisis the idea was again
revived, nding favor with Martin Wolf, chief economics commentator of the
Financial Times, who has called for stripping banks of their right to create credit
money.4 His argument that allowing banks to create money by lending out
deposited funds is what is responsible for creating destabilizing credit bubbles and
busts has also been echoed by a number of well-respected economists (Cochrane
2014; Krugman 2014; Polleit 2010). A digital currency-based technocratic mone-
tary authority would likely have to operate in a 100 % reserve environment.
Bitcoin has a xed rate of unit formation (one block every ten minutes), and a
rule for constant predetermined growth of the money supply does happen to have
some theoretical support. The so-called Friedman Rule (Friedman 1948) proposes
that the central bank should establish a xed constant rate of growth for the money
stock, and maintain that growth rate no matter what emerged from the state of the
economy. Such a rule has some advantages: it is easy for the public to understand;
the rate of inflation cannot take off toward plus (or minus) innity; and,
market-determined interest rates are free to fluctuate in response to changing eco-
nomic conditions (Taylor 1999). A xed rule, however, critically ignores feedback
from the economy and does not have the ability to adjust and smooth out the effects
of macroeconomic changes.
McCallum (1988) and Meltzer (1969) have augmented the constant growth rate
formula with quantity-based rules that yield a dynamically changing growth rate of
the monetary base contingent on widely available economic indicators. Notably, the
McCallum Rule has been proposed as an alternative to the Taylor Rule, and it has
been empirically shown to perform better during crises (Benchimol and Fourans
2012). Such a rule would be much easier to implement with a digital currency
system as regulator of monetary supply, since there would be no target interest rate
in the traditional sense. The McCallum rule determines the optimal change in the
monetary base given changes in GDP, inflation and the velocity of money. It is also
intended to reflect long-lasting, permanent changes in the demand for the monetary
base that occur because of technological developments or regulatory changes, and
not intended to reflect cyclical conditions (McCallum 2000).
If we take a monetary policy with an explicit inflation target (say 2.5 % annu-
ally), one could easily construct a rule for a digital currency to follow that will
change the rate of monetary formation from one time period to the next. This can be
achieved by adjusting how many monetary units are produced when each block of
digital currency is created, or by changing the interval in which blocks of currency
are produced. For example, if the economy is growing too rapidly, the rate of
money formation should be reduced over the next time period. This would have a
4
http://www.ft.com/intl/cms/s/0/7f000b18-ca44-11e3-bb92-00144feabdc0.html.
128 A. Hayes
similar effect to raising interest rates in that it would make money scarcer on the
margin. In practice, to promote stricter monetary policy the number of currency
units in each block would be reduced over some interval (for example from 25 to 10
coins per block), and/or the time between block formation can be made longer (for
example from 10 to 15 min), while to promote expansionary monetary policy the
reverse would take place.
Such a rule-following digital currency could operate completely independent
from the central bank. It would only need to incorporate publicly available
macroeconomic data into its function as feedback in order to adjust the rate of new
money formation in the succeeding periods. Not only would such a currency be
independent, but it could be made completely decentralized, with no single
authority or regulator in place. Like Bitcoin and other cryptocurrencies today, it
could even exist across a decentralized network, democratizing the money-creation
process.
A completely decentralized monetary system may seem wildly idealistic, but a
digital currency can also exist across a distributed permissioned blockchain,
where each node in the network is a known and trusted entity. Banks and nancial
institutions could be obvious candidates to operate these nodes, and yet still operate
with transparency with a well-understood consensus mechanism from the point of
view of the population. Within a nations borders, a permissioned blockchain is
probably most appropriate as it can keep out foreign actors, can greatly reduce the
need for expensive and resource consuming mining operations, and greatly
increase the speed and capacity of transactions.
Bitcoin has come under pressure lately with respect to its limitations on the
block size, capping the number of transactions it can process and slowing down
conrmations. An open blockchain where all nodes are (for all intents and pur-
poses) anonymous such as Bitcoin requires an energy-intensive consensus mech-
anism (mining, or proof-of-work) in order to prevent bad actors from undermining
the system. Under a permissioned blockchain all nodes are vetted and known,
making such an expensive and potentially limiting mechanism unnecessary. The
system will need to have the capacity to handle the extremely large amount of
transactions that are likely to occur each and every second across a nations
economy.
Given that a digital currency system like the one described relies on publicly
available, anybody can deduce its next move(s). Market participants, rationally
motivated by prot maximization, will be incentivized to act on any perceived
mispricings observed in the market which differ from how the digital currency
mechanism is expected to behave as it reigns in or bolsters the rate of money
formation. Under a fairly reasonable no-arbitrage assumption, this will serve to
increase market efciency as it will greatly reduce the asymmetry of information
that people can trade on.
To sum up the above analysis, a viable digital currency system could function as
central bank if it: (1) has a potentially unlimited money supply, (2) follows rules
based on dynamically changing the rate of new money formation; (3) has a
mechanism to obtain feedback from the economy; (4) operates in a 100 % reserve
Decentralized Banking: Monetary Technocracy 129
3 Conclusion
Prof. Bennet T. McCallum has recently written a piece on Bitcoin which appeared
in the journal for the Cato Institute (McCallum 2015). In it, he acknowledges that
Bitcoin in its present form could not satisfy the role of the monetary authority. For
example, he reiterates that with a limit of 21 million bitcoins and an economy that
grows each year, deflation will become a rampant problem. He does, however,
generally propose the viability some alternative digital currency system, such as
described in this section, but (perhaps ironically) he fails to incorporate his own
namesake Rule into his analysis.
With advances in blockchain technology now removed from the constraints of
Bitcoin, it is possible to encode smart contracts, algorithms that will act as a trusted
enforcer of agreements. With deployable smart contracts, a blockchain-based
monetary authority, which follows a McCallum-like rule for new money creation,
can also engage freely in emergency measures such as open market operations to
drastically increase or decrease the money supply when warranted. Such a situation
may be runaway inflation or deflation, a collapse in employment, or a period of
recession. In these cases, the digital currency itself will act as a decentralized
autonomous organization (DOA), making decisions on its own and interacting
with real nancial markets directly. Such a DOA could feasibly buy up existing
digital currencyand even destroy some of that currency by sending it to unusable
wallet addressin order to quickly reduce the money supply outstanding.
The DOA could engage in purchases of foreign currencies in FOREX markets, as
well as stabilize prices by purchasing bonds and equity in exchange for its stock of
digital currency. Coupled with improvements in articial intelligence and machine
learning, an AI-enabled DOA acting as monetary authority can truly be removed
from government, central authorities, or the influence from policymakers and
corporate lobbies.
Bitcoin has proven itself to be a fairly robust use-case of blockchain technology
in creating a global, decentralized digital currency and payments system. Bitcoin,
however, is flawed in many ways if it is to be adopted as a true economic currency.
Many of these issues can be rectied to make a more useful and dynamic digi-
talcurrency, able to meet changes in supply and demand for money. If programmed
as a decentralized autonomous organization, a blockchain-based monetary authority
can even engage in its own emergency measures with effects similar to quantitative
easing in order to stimulate a flagging economy or else halt rampant inflation.
Doing so will enable a truly independent monetary authority to operate and perhaps
even improve the prospects for economic stability and efciency.
130 A. Hayes
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Author Biography
1 Introduction
We live in a world of bits and bytes. Zipping through the air, it pervades human
lives the world over. The technological backdrop to this situation is twofold: our
incredible world-wide ubiquitous communications infrastructure known as the
Internet and all the metal-and-plastic boxes at the ends of this network known
variously as computers, laptops, mobile phones and tablets. Looking at the awe-
some alterations to society that have taken place in the last few decades with
G. Wood () J. Steiner
Co-Founder and CTO, ETH CORE LIMITED, London, UK
e-mail: fao.gavin@ethcore.io
J. Steiner
Co-Founder and COO ETH CORE LIMITED, Berlin, Germany
e-mail: jutta@ethcore.io
3 A Global Computer
If we review our ideal a little more deeply functionality to remember and enforce
past statements by participants, there are three concepts that we can explore:
remember [past statements], enforce [those statements], and by participants.
The easiest to understand and reason about is the latter. It relates to the notion of
identication of a statement with a specic individual. Identication really just
136 G. Wood and J. Steiner
means the ability for someone to prove that they are the same individual as that
associated with a previous statement or event. There are numerous solutions to this
problem in the real world depending on the gravity of the situation. From keys and
codes which are often used for entry to an inline service or building, to passports
and birth certicates, often needed for entry into a country or into marriage. For
mid-level purposes, however, the classic pen-and-paper signature is the de facto
means of identifying oneself and recording ones approval.
Pen-and-paper signatures work (theoretically) on the basis of it being difcult to
replicate another persons signature, under the assumption that one has access only
to other signed documents. In the digital word of fax, scanners and Photoshop, this
idea is of course ludicrous.
While the pen-and-paper signature is far from perfect, there does exist a true
analogue in the digital realm, a technology that people can trust but no replicate,
allowing to sign documents and make others sure it was us who did it. This tech-
nology is called public/private key cryptography (or PKI). Us is in fact anyone with
access to a particular secret number (its a big, random one so nobody can guess it and
its typically password protected so its hard to steal). The term documents, is
actually any piece of digital information, and includes everything from the simplest
text message to the most complex PDF. Finally, the term sign in this case simply
means appending a small piece of information to the document.
Using such cryptography we can begin to understand how we might be able to
identify statements by participants made on or over the Internet in a strong fashion.
Indeed this technology is used already to help us recognise fake websites: that small
green lock to the left of the location in the browser is the indication that the website
has a trusted digital signature. The other two aspects of our ideal are a little more
difcult to address. While technology like PKI can solve the participants identi-
cation issue, the remember and enforce elements require an unorthodox approach.
Remember statements and automatically enforcing them essentially means
having a language in which it is possible to have a machine record statements and
execute on them. Luckily, these machines exist: theyre called state-transition
machines or, more commonly, computers. The languages also exist: theyre called
computer languages, the most basic of which are called machine code. Under this
language, we need no longer talk about statements as much as transactions, their
machine equivalent, representing a valid arc between two states. Transactions are
simply code executions valid for both parties.
These languages have their drawbacks, of coursetheyre difcult for humans
to write and even more difcult for us to understand. They are abstract and deal
only in the simplest mathematical and logical notions. However, they have two
advantages that make them unavoidable for us: they are generally Turing complete,
meaning that any conceivable logical statement can be expressed and executed
given enough time and storage spaceand they are unambiguous, meaning there is
only a single meaning for any given statement.
While codes are a possible solution of the remember and enforce elements,
our great remaining problem is that we are unable to use a traditional computer to
enforce these languages: The issue is twofold. On the one hand, the unquestionable
Trustless ComputingThe What Not the How 137
1
Omni and Counterparty can be dened as algorithmic extensions of Bitcoin, while Ethereum
represents an open-source fully decentralized platform for smart contracts. See http://www.
omnilayer.org/, http://counterparty.io/ and https://www.ethereum.org/ for more information.
138 G. Wood and J. Steiner
their business logic (i.e. software) will run securely and as intended. Such a
computer system is called trustless, because the users of it need not trust in the
behaviour of any particular operator (or minority thereof), but only in the rational
behaviour of the majority leading to the computers emergence.
Does the invention of the blockchain computer match our specications and
needs for an ubiquitous trustless computer? Indeed, there are a number of key
differences between the blockchain type of a computer and a traditional computer;
rst and foremost, it is decentralised, or physically non-localised. Secondly, as it
will be discussed later, it is fundamentally secure in a way matched by no tradi-
tional computer. Finally, it is completely auditable: much like we can comprehend
how our bank accounts balance ends at a particular amount through reviewing all
transactions on our account, we can apply the same process to the blockchain
computer with ease and understand how it arrived at a particular conguration of
information with complete clarity.
Traditional hardware computers (e.g. desktop PCs, mobile phones, etc.) are limited
by the physical world. My PC or laptop cannot run in two or more places at once
however much I may wish. Even though it seems that modern (web) applications
run on several devices, the truth is that to keep consistency, the applications core
program is executed (or at least coordinated) on a single, centralized server, with the
client device effectively being merely a powerful display.
In contrast, the computing power at the centre of blockchains need not be
localized to one single machine: for any blockchain there is no single machine that
similarly governs the business logic or the data on which it operates. Instead of
appealing to a single authority at the core to know about the current state of the
system, users unambiguously discover the state of the machine by applying a
number of rules and publishing data openly. This works because the sharing of such
data is incentivised by a mechanism that forms part of the rule set.
input/output (I/O) devices and conduits, such as an Ethernet cable. Having physical
control over the I/O allows in addition, possibly clandestine, further operations to
be executed, incoming information to be hidden or altered, the state of the system to
be modied and for such actions to happen without trace.
Recent years have seen a surge in attacks undermining the protection mecha-
nisms erected around centralized systems. Leveraging the most elevated access
rights, an attack that targets IT and operational support could eventually lead to the
system being fully compromised. The notion that some level of physical security is
sufcient for total business information security is flawed entirely: the physical
world lends itself well to providing us a false sense of security over the information
and processing that happens in the digital world.
With the blockchain, security is different: it does not matter who or where you
are, the blockchain computer runs totally unaware of anything until and unless
strong cryptographic authentication by a user is provided. More precisely, any and
all input to the machine at all times for it to be accepted is necessarily and always
authenticated. This authentication is provided in terms of an unforgeable digital
signature: a cryptographic widget which allows someone to prove their identity
without giving away the ability to prove it in the future (see call-out box for more
details). Output, or the ability to inspect the results from the machine, on the other
hand is completely unprotected and open for everybody to inspect. The security of
the blockchain computer differs from the physical security systems of conventional
computers in that it matters not what your job is or what your physical access
capabilities happen to be; you strictly cannot interact with the machine unless you
provide the digital key required for the interaction of which you are the owner
(e.g. unless you prove the ownership of an account through the respective digital
signature, there is no way for anybody else to change the accounts balance). In
reality, this means that classic elevated privilege levels tend to be curbed or
removed entirely. The security risk of the weakest link stemming from operators
and IT administrators is drastically reduced.
Computers are deterministic. This means that any decisions they make, or infor-
mation the user can extract from them, is based purely on the historical input of the
machine, e.g. from information received over its network cable or through the
keyboard and mouse. Taken as a whole, these inputs are records of the various
interactions that have led the machine into its present state (e.g. automated bank
transfers in the case of a payroll system or ordering additional components in the
case of a stock control system).
Determinism means that the actions of a machine can be strictly veried and
audited as correct, with one proviso: that all information concerning all inputs is
provided. Typically in traditional systems this is expensive, impractical or impos-
sible. The inputs to a business system often include heterogeneous types of data
140 G. Wood and J. Steiner
(besides keyboard, mouse and network I/O, there is input coming from other
applications, all of which could be time-sensitive) and the auditing itself, which
would essentially be an attempt to play back such inputs, would be technically
challenging. Furthermore, in a business context, auditing may need strong knowl-
edge and assurance of operator identity, which can often be compromised or flawed.
A blockchain computer is different: by design it is perfectly auditable. Each
individual operation of interaction, e.g. the provision of a new employee in the
payroll system or the recording of outgoing stock in the stock control system, is
perfectly recorded and archived. Auditing is as simple as joining the blockchain
network, since the only way to interact usefully with it is to replay all of the
operations of the past oneself in order to build a correct model of the present.
Combined with absolute guarantees of authenticity for each and every interaction
with it, strong and agile data systems can be facilitated which are at its core resilient
to coercion and human factors.
Digitisation of banking, which is to say, the transition of ledgers from pen and
paper to electronic and magnetic, optimised the flow of credit through the economy,
brought banking to the masses and consolidated authority over vast parts of the
economy to a few extremely large banking corporations. But operations suffer from
the centralisation and lack of transparency. Certain services, such as fast transfer of
value, international transfers, digital and effortless point-of-sale payments, have
hitherto only been available through the extensive infrastructure built by banking
industry. Operations are extremely costly. Santander estimates potential cost saving
up to $20bn annually that blockchains could deliver.2 The fundamental complexity
of this infrastructure, at its core, is little more than arithmetic: it must avoid the
unauthorised creation or reduction of value.
A vastly simplied blockchain software infrastructure and smooth inter-operation
would allow services to be mashed-up (combined) to unleash exciting potential
business opportunities previously possible only through cumbersome cross-industry
partnerships, without risk of leaked or stolen information being used to boost cor-
porations prots. Users would be safe in the knowledge that they share only as
much data as is strictly required for the application to function; never giving away
sensitive payment information and never having to trust one faceless organisation
over another. While this is an inconvenient truth now, it will become ever more
important as the data that our device manufacturers own begins to include infor-
mation of a decidedly private and personal nature never before collected.
2
For more information see: Wyman, Oliver, Anthemis Group and Santander Innoventures (2015),
The Fintech 2.0 Paper: rebting nancial services, available online: http://www.nextra.com/
nextra-downloads/newsdocs/The%20Fintech%202%200%20Paper.PDF.
Trustless ComputingThe What Not the How 141
6 Further Examples
Most of the times, the journeys of our material products remain hidden in
sprawling, complex supply chains or are veiled by marketing that can mask sad
truths rendering informed purchases impossible.
At the same time, more and more consumers are demanding genuine trans-
parency on where and how their products are made. Recent regulation, for example
in the EU and UK, requires more supply chain information to be published and also
ensures that perpetrators can be adequately punished. But even with increased
demand and regulation, ensuring the authenticity and chain of custody of products
has proven difcult.
We have long tried to entrust third parties to track and oversee supply chains
employing centralised databases, without success. If that party is the brand itself, or
most powerful actor in the supply chain, then motivations are not aligned. This
could lead to selective disclosure since the party monitoring the information is
responsible for its own bottom line only. If the supply chain data were gathered by a
third party this third party would have to be totally disinterested, yet properly
incentivised to deliver the technical capability of running the system. Third parties
like NGOs or industry associations rarely manage even one of these two. Even if
both of those things were achieved, that third party would become a single point of
weakness, making them and their operations a vulnerable target for bribery, social
engineering or targeted hacking. The truth is, no single third party can make supply
chains more transparent. The key to transparency is the decentralisation of data as
enabled by blockchains, meaning no single party can control and alter what is seen
about the products journey.
Huge benets for customers will emerge from the secure guarantee of a true
chain of custody, along even the most complex supply chains, at a very low cost.
Blockchains offer a unique opportunity for collective supply chain governance.
Finding someone special using remote means is nothing new, however the ubiquity
of the Internet has boosted the numbers of people looking for love through text and
images to astronomic proportions. However, even in todays wired world, much is
wrong with the experience. The Internets, provision of ubiquitous, cheap com-
munication makes it all too easy for love spammers to approach countless
potential dates. Indeed, the technology facilitates such abusers to use the same
specially concocted introduction line to maximise their chances of a reply. Such
activity distorts the date market, placing potentially promising partners under
heaps of thoughtless opportunists.
142 G. Wood and J. Steiner
Fig. 1 N = 2462 for heterosexual couples, respondents are age 19 and older (Source Rosenfeld,
Michael J. and Reuben J. Thomas (2012) Searching for a Mate: The Rise of the Internet as a
Social Intermediary, American Sociological Review 77(4) 523547, p 530. Web. 29 Oct. 2015.)
Figure 1 shows the changing pattern of how heterosexual have met over time in
the US. Several of the most traditional ways of meeting heterosexual partners had
monotonic declines from 1940 to 2009. The Internet is the one social arena that is
gaining in importance over time.3 Solutions to this problem typically fall under two
umbrellas: extract a real-world fee for the service of being able to send messages or,
use some other metric for ltering would-be dates such as a common-friend,
matching mechanisms or pretty face. Both imbue a signal through placing
restrictions on the communications. The latter techniques tend to be too restrictive
or gameable. Charging blanket fees is a sledgehammer of a signal that instantly
reduces the market size and makeup to a particular demographic and, unless levied
for each message sent, does little to reduce spam.
The walled-gardens that constitute the dating sites that make up different con-
gurations of clientele in terms of geography, lifestyle and interests place additional
constraints on the utility of the system as a whole restricting the possibilities and
market size.
3
Ibid, p 528.
Trustless ComputingThe What Not the How 143
In fact, the problem has a fairly simple solution; we wish to keep many of the
aspects of the internet (such as breadth of audience and depth of content), but add
constraints similar to those of real-life dating to our dating communications: as a
recipient we would wish to have some idea of how many other fledgling conver-
sations our suitor is presently engaged. We might be interested to understand to
what degree they would rate our attention over, say, any of the other peoples
attention for which they are vying. As a suitor, we might like to have an online
engagement ring equivalent for dating, for us to be able to credibly state that we
have decided on this person above all others.
Of course these constraints are fairly trivial to implement on a single computer
powering a dating site, but as soon as that computer is merely part of a single
website or business, we fall short of the vision: people could sign up at multiple
websites, perhaps with multiple accounts and thwart the attempts at holding them to
their word. A single global computer, building on a next generation of blockchain
computers that ensure additional selective privacy, facilitates precisely these sorts
of rule, and placed alongside a strong digital identity system (similar to that of
Estonia, Germany) or a decentralised equivalent could be used to enforce the
constraints globally, honestly and without exception.
Trade nance is the lubricant of the world economy machine that enables smooth
international trade. Over the course of centuries, various tools like Letters of
Credit and Bank guarantees have been implemented to mitigate risks between
unbeknownst parties to enable seamless commerce and remove friction from trade
related to the lack of trust. In the simplest example, these tools generate the
assurance that payments will take place once goods are exchanged according to
certain rules. Trade nance not only tries to reduce risk but also to develop tools so
that agents can leverage their trade reputation to achieve better deals. Reliable
information about the flow of goods and the payment history is essential. Todays
offerings usually only start at the end of the supply chainwhen invoices are
approvedalthough risks starts much earlierwhen the purchase order is raised.4
Solutions are fragmented; linking suppliers with banks proprietary platforms
proves to be cumbersome and expensive. Studies come to the conclusion that up to
$1tr/yr of liquidity is lost through the lack of liquidity.5
4
For more information see: SWIFT White Paper (2013) The Bank Payment Obligation: a new
start for Supply Chain Finance, available online: http://corporates.swift.com/sites/sdccor/les/
trade_bpo_white_paper_201304.pdf.
5
For more information see: Hurtrez, Nicolas and Massimo Gesua sive Salvadori (2010), Supply
chain nance: From myth to reality, available online: http://www.nyear.com/attachment/252360.
144 G. Wood and J. Steiner
Blockchains come with the advantage of being not only organisationally but also
jurisdictionally neutral in the rst place (note that yet required compliance can be
implemented). Due to the lack of a single authority operating the platform and the
unprecendented interoperability, on a blockchain, agreements between international
parties can be implemented and related trades executed such that all parties can be
sure that changes to and controls over agreements can only be exercised according
to rules agreed upon in the rst place.
Acknowledgments Dr. Sarah Meiklejohns and Raul Romanuttis efforts at proof-reading and
rephrasing some of the harder sentences are also very much appreciated!
Author Biographies
Abstract Bitcoin and other privately created digital currencies are beginning to
challenge central banks monopolies on money creation. These decentralized
cryptographic payment media could ultimately displace legacy banking, nance,
and Payment services at a lower cost across the globe. These currencies are likely to
continue experiencing a faster rate of improvement than traditional payment media
and require less force for safekeeping. This chapter explores some of the forces that
led to the rise of Bitcoin including the ball-in tax on deposits during the Cyprus
banking crisis in 2013. We also examine the relative stability of Bitcoin as a store
value. We also consider new internet-based P2P lending arrangements using Bit-
coin rather than dollars as a payment media. Finally, we reassess Stanley Fischers
criticism of Hayeks competitive private currency proposal in light of Bitcoin and
other open source digital currencies.
Keywords Bitcoin
Open sources crypto currencies
P2P lending with
Bitcoin
Greshams law and crypto currency adoption in china
Cyprus, and
Iceland
relative stability of Bitcoin
1 Introduction
Money is a social invention (Samuelson 1958; Menger 1892). Through trial and
error processes, societal improvements in monetary capabilities are ongoing.
According to (Cohen 1998; Sargent 2002), private money predated government-
sanctioned coins. Anthropologists have studied it (Hart 2005), and experiments
indicate that there is greater voluntary use of monetary tokens as the size of the
R.D. Porter ()
Cooksville Digital Coin Lab, Evansville, WI 10905, USA
e-mail: rdouglasp@gmail.com
W. Rousse
Northern Arizona University, Flagstaff, USA
e-mail: wade.rousse@nau.edu
using group increases.1 Native Americans used beads on strings as their form of
money, wampum. Many assume that the predicates associated with traditional
monetary technology must inevitably carryover to the new. But the particular form
of money depends on both social customs and technology.
State-issued currency has been the norm for the two last centuries or so. Initially,
gold convertibility backed U.S. currency. However, after Nixon closed the gold win-
dow in 1971, American legal tender, Federal Reserve banknotes, were only able to
satisfy tax obligations or discharge debts. Oddly, in value terms 78.5 % of U.S. ban-
knotes are held in an anomalous denomination, the $100 billcurrently a grand total of
over $1T or more than 32 bills per U.S. resident. For transactions, this concentration is
remarkable since $100 s are effectively disallowed at most retail outlets. Given this
illiquidity, why do so many hold this particular non-interest bearing asset?
We can resolve this paradox by noting that the bulk of the $100 s are stashed
overseas negating their tax-paying capabilities.2 Since the dollar remains the worlds
primary reserve currency, these banknotes are readily accepted in many overseas
banking and payment contexts. Thus, many households in countries with relatively
high and erratic rates of inflation voluntarily choose to hold some wealth in dollars to
avoid the ravages of home grown inflation (Porter 1996 and Banegas 2014).
In the last few years, new global P2P innovations, such as Uber and Airbnb,
have emerged. Uber competes with taxis while Airbnb vies with hotels (Ritter
2015). Similarly, a P2P competitor to traditional bank loans emerged with the
advent of Prosper and LendingClub.3 At about the same time, a fourth category of
cryptocurrencies, such as Bitcoin, began to provide P2P payment services across
the entire Internet. Like Uber, Bitcoin initially exploited a relatively idle resource,
home computers, to protect the integrity of its global ledger, the Blockchain,
through modern encryption and other cryptographic advances.
At its core, the Blockchain ledger keeps track of who currently owns the Bitcoins
as well as the chain of ownership from the rst (Genesis) transaction. Any Bitcoin
holder can authorize an entry on this ledger to move Bitcoins from A to B. The
pseudonymous inventor of Bitcoin technology, Satoshi Nakamoto, had the Block-
chain replicated widely.4 Under his scheme, an individual transaction could be sent
in clear text and veried independently by hundreds of thousands of dispersed nodes
all over the world by virtue of public key/private key cryptographic methods.
1
Cameraa et al. (2013), demonstrated this result in some carefully designed experiments in which
participants voluntarily choose to use monetary tokens.
2
Except in special locations such as Panama, such dollars are not generally legal tender outside the
United States or its territories. Their use is widespread but informal.
3
The Internet has created more efcient P2P matching mechanisms. Some of the new pairings
represent the sharing economy, e.g. car rides (Uber https://www.uber.com) and rooms (Airbnb,
https://www.airbnb.com), while others improved P2P pairings match investors and loan applicants.
Two of the most prominent lenders are Prosper (https://www.prosper.com) and Lending Club
(https://www.lendingclub.com).
4
Champagne (2014) assembles a compendium of Nakamotos writings on Bitcoin from November
2008 to 2011 together with responses and enquiries from others involved in the project.
Reinventing Money and Lending for the Digital Age 147
Airbnb, P2P lending services, and Uber, all operate through a centralized core.
The core handles bookkeeping, designs various interface apps, nds drivers,
investors, or residences and deals with a myriad of regulatory challenges. Unlike
these P2P innovations, Bitcoin operates without any natural center. It moves funds
(Bitcoins) without the use of any trusted party, such as a commercial bank or a
central bank. Inviolate mathematics, not a person or committee, runs the Bitcoin
ledger and is entrusted to manage processing. As email persistently undercut the
cost structure of existing communication schemes such as faxes, rst-class mail,
telegraph, and telephone, Bitcoin and other virtual currencies like Ripple seek to
drastically challenge cost structures for many legacy payment methods: banknotes
and bank wires, checks, and all forms of card payments, credit, debit, or prepaid.5
Like overseas holders who voluntarily use hundred dollar bills for savings, a few
million individuals have willingly chosen to employ Bitcoins.6 Compared to
$100 s, Bitcoins have two unique features: They are scarce and in the digital realm.
They use 21st century cryptography and open source methods. Bitcoin also ushered
in a host of competitors, cryptocurrencies, now totaling around 600. Throughout
this chapter, we use the term math-based currency (MBC) interchangeably with
cryptocurrency or virtual currency, when referring to members of this asset class.
According to the British Museum, the best monetary tokens should be: attrac-
tive, cheap to make, controllable, durable, easy to carry, good for propaganda, good
for both small and large purchases, impossible to forge, and light. Bitcoin embodies
most of these features in a disembodied form as a sequence of binary digits.
Moreover, Bitcoin has a rigid mathematical supply schedule. The basic Bitcoin
protocol makes forging Bitcoins ostensibly very difcult. No one has been able to
overwhelm Bitcoins built-in defenses against such double-spending attacks. One
cant rule out the possibility, but the decentralized Bitcoin network has successfully
resisted such attacks and accumulated a huge war chest of computing power to fend
off such attacks.7 Bitcoin uses a Byzantine fault tolerance mechanism (Lamport
et al. 1982), to carry out a cryptographic style of the proof of work in parallel to
ascertain the legitimacy of all individual transactions.
5
Ripple operates with a more traditional corporate/employment structure than Bitcoin. It has
different mechanisms to build consensus and distribute coins (XRPs). This MBC has also sought to
establish direct banking relationships in part to facilitate global nancial exchange. See ripple.com.
6
There are no denitive estimates of the number of Bitcoin users. The number of outlets accepting
Bitcoin was 100,000 (Curthbertson 2015). As of late October 2015, the number of Bitcoin wallets
was about 4.6 million according to blockchain.info with the leading American Bitcoin banking
outlet, Coinbase, having 2.7 million users. A lengthy discussion of the pitfalls in estimating the
number of users puts the gure at 2.5 million in early 2014, https://bitscan.com//how-many-
people-really-own-bitcoins-and-why-d.
7
The code slowly changes to incorporate improvements, e.g., to scale up. But a real shift in the
underlying protocol would require close to unanimous assent. Otherwise, a large fork in the
Blockchain could disrupt the overall viability of the Bitcoin project. Most users would have an
incentive to avoid such a possibility. Thus, while majority rule protects the integrity of the
blockchain, a higher threshold of mutual agreement would be necessary to introduce signicant
changes in the protocol.
148 R.D. Porter and W. Rousse
Wholesale banking has been in digital form for a long time. But retail payments,
particular banknotes, require physical handling and securing. By some accounts
these various non-digital processing costs exert a considerable tax on dollar holders
(Chakravorti 2013).
From its construction, Bitcoin transactions can avoid the omnipresent
cyber-attacks that have continued to disrupt and elevate costs for legacy banking
and payment schemes. The Bitcoins potential is the ability to expunge such fric-
tions and span the globe much more cheaply than these legacy payment vehicles. In
historically poor and nancially underserved communities, Bitcoin could permit
billions of unbanked households to move beyond mere currency and coin.
Such a revolution has another virtue that is infeasible in the traditional payments
domain. It is possible to protect the inherent wealth embodied in Bitcoins not with
physical force but with cryptography. In the pre-Bitcoin world wealth protection for
individuals and banks required vaults, armed guards, and array of private and public
clerks and overseers.
The emergence of Bitcoin opens up a number of other possibilities. Does money
have to remain a central bank monopoly? When nations standardized and veried
coins and provided security for mints, it was then that physical coins became widely
used as a medium of exchange in the 19th and 20th centuries. Bitcoin detractors
note that since Bitcoin is a private token, it is not legal tender and is therefore not
money. Those questioning Bitcoins provenance are channeling Georg Friedrich
Knapp, who said, The soul of currency is not in the material of the pieces, but in
the legal ordinances which regulate their use. (Knapp 1924, 2).
But the Bitcoin Blockchain provides safety and security without armed guards
and vaults and provides more functionality than nation state monies at a lower cost.
Its attractive nite issue limits are dictated by math and is not subject to pressures to
inflate to escape difcult political choices. Just as U.S. banknotes have become
worthy competitors to Russian and Argentinean banknotes in those countries and
elsewhere as a store of wealth, whats to prevent Bitcoin or other successful MBCs
from displacing inflation-prone nation state currencies?
Kenya, for example, has been transitioning to a payment system based on mobile
phone technology, the M-Pesa system for an increasing share of its transactions. As
such, it would not be that much of a technological jump for Kenyans to go all the
way to Bitcoin-enabled payments on smart phones that the new Kenyan entrant
BitPesa could conceivably provide. And beyond Bitcoin itself, the approximately
600 open source Bitcoin competitors provide a natural seedbed for a Hayekian
experiment to provide MBCs privately and competitively. These new cryptocur-
rencies broaden the potential choices available to everyone and remove some of the
difculties with F.A. Hayeks decades-old proposal for the denationalization of
currency (Hayek 1990).
Over the last century or more, nation states assumed the upper hand in dening
what constituted money. As Cohen (1998) points out, however, though the
arrangements varied considerably, the concept of money didnt originate with the
state, but was taken over by it (Menger 1892). Hayek argued that, as the state took
over stewardship of money, improvements ceased and progress retrogressed:
Reinventing Money and Lending for the Digital Age 149
The great trouble is that money wasnt allowed to develop. After 200 or 300 years of the
use of coins, governments stopped any further developments. We were not allowed to
experiment on it, so money hasnt been improved, it has rather become worse in the course
of time. Money was frozen in its most primitive form. What we have had since was
mostly government abuses of money. (Blanchard 1984).
Menger was writing near the end of a halcyon century of price stability, while
Hayeks views were undoubtedly influenced by the destructive Austrian hyperin-
flation after the Great War.8 In its immediate aftermath, J.M. Keynes concluded that
such episodes were highly disruptive of societal order:
Lenin was certainly right. There is no subtler, no surer means of overturning the existing
basis of Society than to debauch the currency. (Keynes 1919)
In his manifesto, the Bitcoin founder, Satoshi Nakamoto, sang from the same
hymnal as Hayek and Keynes:
The root problem with conventional currency is all the trust thats required to make it work.
The central bank must be trusted not to debase the currency, but the history of at cur-
rencies is full of breaches of that trust. Banks must be trusted to hold our money and
transfer it electronically, but they lend it out in waves of credit bubbles with barely a
fraction in reserve. We have to trust them with our privacy, trust them not to let identity
thieves drain our accounts. Their massive overhead costs make micropayments impossible.
(Champagne 2014, 100)
In todays terms Nakamoto, was unhappy with the performance of central banks.
But he was also disdainful of the lending and payment practices of commercial
bankers. Such practices induced credit cycles and relatively expensive but unsafe
electronic banking environments.
The outline for the chapter is as follows. Section 2 compares the readiness and
tness of Bitcoin and other virtual currencies to gold and other legacy payment
vehicles. More broadly, we revisit Hayeks proposal for the denationalization of
currency. Indeed, the decentralization embodied in Bitcoin and other virtual cur-
rencies makes the possibility of more transnational digital currencies such as Bit-
coin or, alternatively, local currencies suitable for a narrower domain, such as
Scotland or even Detroit, an opportunity that (Jacobs 1984) endorsed.
The third section briefly takes up the forces driving Bitcoin and other virtual
currencies in the last few years. The long-run price of Bitcoin depends on its
ultimate acceptance and what it displaces. Since Bitcoin is a networked good, the
larger its penetration, the more valuable it will be according to McCalfs law.9 We
8
In its origin [money] it is a social, and not a state institution. Sanction by the authority of the
state is a notion alien to it. On the other hand, however, by state recognition and state regulation,
this social institution of money has been perfected and adjusted to the manifold and varying needs
of an evolving commerce. (Menger 1892).
9
(Bob) Metcalfs law asserts that the value of the network is proportional to n2, where n = the
number of network nodes. If there are n nodes, then there are n * (n 1) possible P2P pairwise
network connections, distinguishing between ordered pairs. Finally, n * (n 1) = O (n2) in
Landaus symbol.
150 R.D. Porter and W. Rousse
examine some of the forces operating on Bitcoin and other altcoins in the context of
three dramatic events: the bail-in tax on Cypriot insured deposits, ofcial Chinese
encouragement and subsequent disavowal of Bitcoin, as well as the results of a
Bitcoin-type experiment on Iceland, Auroracoin.
The resulting volatility in the price of Bitcoin, induced by these and other
disruptions, has led some observers to suggest that Bitcoin may be impractical as a
day-to-day currency. Section 4, however, indicates that Bitcoin appears to be
achieving more stability than countries in which the dollar has made strong inroads
as a store of value, such as Argentina and Russia. So, Bitcoins viability as a means
of payment and store of value is still an open question.
Compared to traditional lending vehicles, Bitcoin has two advantages: the ability
to go anywhere cheaply and to be highly divisible. In Sect. 5, we show how new
P2P lending platforms have exploited these advantages in over 100 countries. This
platform allows private citizens to be nanced outside traditional bank lending
channels. A nal section concludes.
10
That is, Bitcoin and Ripple have a xed supply of coins in the long run. The growth component
for Bitcoin over the next 25 years is about 2 %, near the FOMCs current inflation target. Some of
these alternative currencies to Bitcoin have exogenous growth components. Also, some, such as
Freicoin, have a demurrage (usage) fee, to encourage use; see Keynes (1961, 353358). An
economy based on Freicoin might be able to avoid the nonstandard monetary policies that the FED
and other central banks have followed recently in the aftermath of the Great Recession.
11
Satoshi (Champagne 2014, 281282), explicitly compares Bitcoin with gold. He notes that while
it possesses none of golds metallic features such as corrosion resistance, it does have one special,
magical property, [it] can be transported over a communications channel.
Reinventing Money and Lending for the Digital Age 151
And the vast majority of such monies are unwanted: people are unwilling to hold them as
wealth, something that will buy in the future at least what it did in the past has only become
apparent since the 1970s, when all the worlds governments rendered their currencies
intrinsically worthless. (Steil 2007)
There are, however, some important differences between gold coins and Bitcoins.
Bitcoin is a virtual object whose ownership can be completely anonymous and thus
totally invisible, while gold requires storage and protection.12 The inventory holding
costs of Bitcoin are relatively minor compared with gold.13 Bitcoin is also
remarkably divisible, existing in units as small as 108 of one Bitcoin.
In the long run, the primary allure of Bitcoin relative to the dollar is that it will
preserve its purchasing power given that the dollar and other at currencies are no
longer anchored by gold but by promises that can be forgotten. This feature is
probably more important for weaker currencies than the dollar, particularly coun-
tries experiencing high degrees of instability since the world left gold. Of course,
the dollar has one decided advantage over Bitcoin. Since WWII, the dollar has been
the worlds reserve currency. As Chairman Greenspan noted,
Central banks can issue currency, a non-interest-bearing claim on the government, effec-
tively without limit. A government cannot become insolvent with respect to the obligations
in its own currency. A at money system, like the ones we have today, can produce such
claims without limit (Greenspan 1997, 2)
As an aphorism, Greshams law refers to bad money driving out good money in
the short run. But just the opposite holds in the long run as this adage flips on its
head. The logic is straightforward: Should buyers use a superior longer-run value or
an inferior one to complete a given transaction today? Obviously, they will be better
off in the longer run using the inferior instrument today provided neither payment
choice is discounted, whenever they anticipate that the better one might subse-
quently become more valuable.14 This revealed preference essentially represents a
penchant for good money over the long haul:
Standing by itself, the general statement, good money drives out bad, is the more correct
empirical proposition. Over the span of several millennia, strong currencies have dom-
inated and driven out weak in international competition.
The same proposition holds with respect to the use of materials for international money.
(Mundell 1998)
The upshot is this: If currencies can be freely chosen, then the one with the most
desirable properties will win out in the long run.15 This argument applies to all
12
Strictly speaking, as implemented Bitcoins only have a limited degree of anonymity since the
blockchain lists all transactions. More invisible MBCs are being created such as Dash.
13
The transaction costs of holding gold are not small. Among other costs, commissions on buying
or selling coins can be 56 % while insurance runs as much as 1 to 1- % per year.
14
Hayek (1962) explores the history of thought of this concept.
15
Guidotti and Rodriquez (1992) presents this long-run reversal of Greshams law in an optimizing
framework.
152 R.D. Porter and W. Rousse
currencies, including digital ones. That is, if these MBCs represent sufciently
better payment mechanisms than at based monies, there is no reason they couldnt
eventually displace FBCs.
Enforceable taxes create the demand for legal tender. This force will still hold
even as home-production income generated on the Internet may be inherently more
difcult to tax than traditional retail outlets. But MBC-based activities that end up
with a sufciently broad base of users will have the wherewithal to pay the taxes.
Thus, Greenspans declaration that banknote claims can be unlimited requires
some qualications in light of the issue raised by Steil. Simply put, there may now
be more constraints on at currency issuance. Given the Zimbabwean experience,
for example, it is not clear that they could ever issue at banknotes.
On the supply side, the labor and capital content of processing Bitcoin payments
appears to be orders of magnitude less than the legacy payments systems they seek
to supplant. As an open source project that was freely bequeathed to the Internet by
its nominal creator, Satoshi Nakamoto, Bitcoin requires only a small coterie of
programmers. As a result, the associated capital and computing costs are quite
small. Moreover, the vast computing power of the distributed network of thousands
of nodes that support the integrity of the Bitcoin network, the mining community,
voluntarily provides vast amounts of computing power in the hopes of winning
Bitcoins by solving cryptographic puzzles. The resulting cost structure allows
Bitcoin and other MBCs to support worldwide payments more cheaply than legacy
banking institutions or governments.
In ways, these new digital tokens are analogous to the way that gold and silver
coins of standard form and weight often circulated far outside their country of
origin. For example, before our pure at monetary era, coins from the Latin
American Union circulated in over a dozen countries in both Europe and the
Americas for over six decades.
In a recent paper, Erb and Harvey nd it difcult to gauge the target for the price
of gold, given its present value over various time intervals. They conclude:
In the end, investors are faced with a golden dilemma. Will history repeat itself and the real
price of gold revert to its long-term meanconsistent with a golden constant? Alter-
natively, have we entered a new era, where it is dangerous to extrapolate from history? (Erb
et al. 2013)
For example, Erb and Harvey nd scant evidence that holding gold has been an
effective hedge against unexpected bouts of inflation whether measured in the short
term or the long term.
At rst blush, MBCs seem much more alien and opaque relative to that of gold.
But even under a gold standard, monetary arrangements werent necessarily that
secure or foreseeable. The standard itself was not immutable.16
16
It was altered numerous times, e.g., to assuage U.S. silver mining interests. Of course, gold (or
silver) discoveries would alter prices. Moreover, the prices of precious metals depend on demand
and supply. But supply put onto the open market occasionally depends on the behavior of nation
states. Together with the IMF, governments remain the largest holders of gold bullion.
Reinventing Money and Lending for the Digital Age 153
Despite the trust issues, however, Bitcoin is not without a level of voluntary
backing. A broad community of network users relies on the Blockchain ledger,
which tallies users holdings since the networks inception. In turn, the Blockchain
is backed by a decentralized replication, consensus, advanced cryptographic tech-
niques and enormous computing power. In short, Bitcoin is founded on the col-
lective support of a fairly deep and broad community of hundreds of thousands of
users spanning the globe and encompassing virtually all locations. Many of those
that have used the dollar in lieu of their own at currencies, as arguably a poor
mans gold substitute; one might view Bitcoin as disputably a better gold substitute
than the USD, albeit one of somewhat limited use currently to the extent that it
remains much less liquid.
Thus, in many ways Bitcoin and other altcoins are simpler and more straight-
forward concepts than gold. Each consists of thousands of lines of code that con-
nects hundreds of thousands of individuals on distributed networks. And, the BTC
supply function is more rigidly determined than gold because the protocol math-
ematically limits the total supply of Bitcoins in all horizons.
A Bitcoin supporter might even argue that BTCs are more trustworthy than gold.
There were difculties in trusting governments to preserve purchasing power, even
in times when they were nominally still operating under a gold standard, e.g.,
during wars. The New Deal prohibited private gold holding and abrogated the gold
clause in corporate bond contracts. Thus, will a strategy of holding gold as insur-
ance against small probability tail events work when those tail events occur? Put
differently, how viable will such a strategy be if society voids the protection
afforded by owning gold just when its value is the highest?
While nations can still invoke the requirement of having to use their legal tender
inside their borders, this imperative will not necessarily be that compelling when
considerably better alternatives exist. Over 60 years ago, Abba Lerner declared
condently
The modern state can make anything it chooses generally acceptable as money and thus
establish its value quite apart from any connection, even of the most formal kind, with gold
or with backing of any kind. (Lerner 1947, 313)
At the time, a xed exchange rate between gold and various currencies imprinted
an international standard so that investors didnt have to fret that their foreign
(Footnote 16 continued)
Accordingly, the incentives of these players may lineup with political and not necessarily
economic objectives. Finally, one reason that gold often tends to accumulate in the hands of
nations is the considerable amount of force needed to safeguard it, e.g. at Fort Knox. Monetary
instruments went from being in hoards held by individuals (Peebles 2008, 235), to being held in
nancial institutions. There is no reason Bitcoins couldnt revert to this earlier form of dispersed
storage in individual hoards, at least provided adequate safekeeping facilities appear.
Alternatively, Bitcoins, could become part of the short-term liquidity pools in repurchase
agreements and the like.
154 R.D. Porter and W. Rousse
currency positions might collapse overnight. After currencies had become pure
manifestations of sovereignty, the dollar emerged as an international standard and
gradually became the bellwether store of wealth. This phenomenon was especially
true for those in countries with unstable banking systems or currencies such as
Russia, after the fall of the Berlin Wall, or Argentina, which has been subject of a
crazy quilt of bizarre monetary regimes ostensibly forever (Paolera 2001).
Given all these imponderables, it is true that, no matter what happens, the dollar
is currently a stronger anchor than any other at currency. In the world of floating
exchange rates, sharp changes in relative currency valuations can occur. These
fluctuations lead risk-averse investors to seek out the dollar for precautionary
reasons. While the dollar may not be as safe as gold, it is currently safer than every
other currency.
One might counter that while the Bitcoin space has the advantage of Blockchain
technology, which arguably is a real improvement, it has faced a host of problems
that traditional banknotes have not. There has been widespread fraud on many
Bitcoin exchanges, Moore (2013), including one of the most prominent, Mt. Gox.
Moreover, the technology, at least in the early stages, often appears to be prone to
fraud: When people lose their private keys, their Bitcoins are forever lost; they do
not have the recourse options that credit card holders have, but are like banknote
holders who misplace cash. But considering the card space itself, fraud is hardly
inconsequential and, if anything, a more thorny problem to overcome.
2.1 Divisibility
Though gold and Bitcoins have some similarities, there are important differences
with respect to payments. While gold and silver coins once freely circulated in the
Americas, Asia, and Europe, it is not clear that would make much practical sense
today. Today, a twenty-dollar gold coin would weigh only about 1- times that of
an ordinary paper clip, which would hardly make it practical for most transactions.
Bitcoins can be divided into much smaller units or fractional coins up to 108 of
one Bitcoin, which is called a Satoshi. To illustrate, if the BTC price were $250 per
coin, 20,000 Satoshi would be worth a nickel.
As a payment system, BTC transactions make considerably more practical sense
than moving gold around. The advantages of BTC relative to gold coins arises from
the extremely low transaction costs inherent in BTC that make it much more liquid
than gold, though there has been a considerable tendency to hoard it; see (Tasca
2015). Ultimately, this liquidity reduces transaction costs and induces greater usage.
The emerging Bitcoin community is also beginning to recognize that Bitcoin may
be safer than at banknotes or coin if properly secured since their virtual status does
not necessitate physical security.
Reinventing Money and Lending for the Digital Age 155
The Bitcoin revolution exploits open source technology. This feature makes the
characteristics of the currency transparent for all who wish to look under its veil.
Open source-based currencies accurately reflect the time series pattern of the supply
function for new coins. In addition, their security properties will also be evident by
inspecting the code. So with the advent of Bitcoin, the technical substitution pos-
sibilities underlying Hayeks competitive private currency proposal have changed.
Hayek imagined a competitive state of affairs in which alternative currency sup-
pliers created their own coins and marketed them to the public, much like the free
banking era in which private banks issued their own banknotes denominated in
dollars.
The Blockchain, as well other features voiding double spending in other MBCs,
undermine Stanley Fischers criticism (Fischer 1986), of F.A. Hayeks proposal
(Hayek 1990). Based on the technology of the era, Fischer argued that private
currency suppliers would not necessarily create currency tokens that had stable
purchasing power. Rather, private currency producers might have an incentive to
cheat on their promised coin policies or suddenly depart from the prudent strategies.
Fischer thus argued that there were no economic forces ensuring that the private
marketplace had the incentives to produce what Hayek imagined. All Hayek had in
the end was the hope that the supply process would result in stable purchasing units.
But there was no reason to guarantee that would happen.
Put differently, under Fischers critique of Hayek an established private currency
would be tempted to produce inflationary surprises, the problem of dynamic
inconsistency. Moreover, having the state be the sole currency issuer was efcient
compared to Hayeks competitive solution that required competition and multiple
currencies. One currency made it easier to detect counterfeiting.
While both issues represented legitimate concerns when Fischer rst raised
them, the advent of the MBC protocols sweeps them aside. Most MBC protocols
such as the Bitcoin protocol are immutable and strictly programmed to produce
only a xed number of coins. Assuming the protocol remains intact, dynamic
inconsistency is not feasible. Secondly, the Bitcoin protocol has thus far proven to
be resistant to counterfeiting attacks, which were one of the key design objectives of
its creator. Indeed, we now know how to produce monetary trust after Bitcoins
creator specied the production function for the Blockchain. We also know that
Bitcoin has worked quite well empirically to maintain the integrity of the trans-
actions on Blockchain under a variety of real world challenges. This empirical
success removes Fischers objections.
Together with several dozens of successor coins to Bitcoin, such as Litecoin and
Feathercoin, Bitcoin and Ripple provide a seed bed for evaluating F. A. Hayeks
guesses regarding a competitively-determined monetary environment. Hayeks
156 R.D. Porter and W. Rousse
ardently believed that such a currency regime would improve welfare and upend the
monopoly that nation states had in currency issuance. Hayek forcibly argued that
nation states had generally failed to be steadfast currency issuers. Hayek thought
successful currencies able to maintain purchasing power would arise from a
bottom-up marketplace of competitively provided tokens. Efcacious currencies
would attract a sufcient base of users by being more stable sources of purchasing
power.17 That is, Hayeks intuited that the competitive process would yield an
equilibrium in which those private currencies that provided the most stable sources
of purchasing power would become the dominant currency suppliers. It is con-
ceivable that such private MBCs could eventually displace public currencies across
the globe or could conceivably be adopted by some public authorities.
It is too early to judge where the rapidly expanding list of MBCs will end
up. The family of competing currencies is only now beginning to emerge together
with the varied regulatory response across the globe. Perhaps most importantly, for
the digital currencies to succeed and become mainstream nancial products, there is
a paramount need for a greater degree of stability and safety on the currency
exchanges. Sufce it to say it is difcult to see where the competitive process will
end up when it has matured and there is a more widespread adoption. But the
variety of coins being created is interesting and impressive in ways.
17
It is interesting that a private currency supplier (Stalnaker 2011), ended up pursuing approxi-
mately the strategy that Hayek argued a private currency producer would be obliged to follow to be
successful (Hayek 1990, 6061).
Reinventing Money and Lending for the Digital Age 157
Chart 1 shows the time series of the number of various cryptocurrencies. The
number of coins reached the 100 mark in early 2014, following the big burst in the
dollar price of Bitcoin near the end 2013. Subsequently in 2014 entrepreneurs
added over 400 new altcoins by October before the process began to plateau. All of
these new currencies obey production functions that strongly distinguish them from
legacy payment vehicles.
For example, consider security. By the very nature of the open source process,
potential security holes can be directly accessed and modied if need be to
incorporate technical advances in cryptology or computing.
At rst glance, any open source structure seems deliberately uneconomic: Why
freely share code as open source projects repeatedly do? The answer, we think, is
the lines of code are not static but part of the changing structure of an ongoing
project that is in a continual state of improvement. Open source efforts are, in their
own way, like a currency: As more programmers use them, the code has greater
value. Here is Metcalfs law at work once again. Indeed, in some computer envi-
ronments, these arrangements work quite well and allow various competitors to
cooperate and share knowledge with mutual benets for all. For example, human
capital regressions nd greater log wages for open source coders in the Apache
webserver project than others, amounting to a growing secular wage premium of
1327 %.18
Open source code can be customized to suit particular requirementsto change
on the flywithout waiting for the next release of commercial code. Currently, the
MIT media lab supports ongoing Bitcoin programming efforts, which consist of a
small staff of three programmers, plus occasional volunteers from all over the
world.
The resulting speed of advance in the digital sphere of coin creation and
extension compared with legacy production methods for banknotes is impressive.
First, we just noted that in Bitcoins short experience, several hundred copycat
cryptocurrencies have been created. While some of these new coins are relatively
trivial extensions, all have had an opportunity to thrive in the competitive cryp-
tocurrency marketplace. Some like Dogecoin started as a prank, but has remained in
the top ve in market cap of all virtual currencies.
In terms of P2P money transfers Bitcoin works reasonably well as do some
competitors like Ripple. The main problem confronting Bitcoin has been outside
the P2P domain in trying to extract immediate value by converting Bitcoins to other
currencies, such as the dollar, the euro, or the yuan. These transactions occur
generally on centralized exchanges that have witnessed a considerable share of
fraud and start-up problems, Mt. Gox, being the prime example.
An Empirical Analysis of Economic Returns to Open Source Participation, Il-Horn Hann, Jeff
18
It is helpful to gain some insight into the economic forces impinging on MBCs by
looking at three actual events. The rst two, China and Cyprus, catapulted Bitcoin
in 2013 onto the world stage. The third, Auroracoin on Iceland in 2014, demon-
strates the difculties in supplanting nation state currencies with something argu-
ably better.
The Chinese real economy has grown rapidly at nearly double-digit rates over the
last 35 years or so, yet its nancial system retains strong repressive elements.
Chinese are still forced to hold yuan, which is not freely convertible into other
currencies, but fluctuates in a relatively narrow floating band to the dollar set by the
Peoples Bank of China (PBOC). PBOC ofcials have signaled that they intend to
make their currency fully convertible, but Chinese citizens today have to abide by
strict annual limits of $50,000 on the funds they can pull out of China.
There is considerable tension between the United States and China arising from
an economic constraint of sorts, the Trifn dilemma. As the reserve currency for the
world, the United States is in the enviable position of receiving an interest-free loan
when it gives dollars to foreigners. But this benet comes at a price, the Trifn
dilemma or paradox. Powerful domestic political forces want their domestic
industries to be competitive internationally but without large trade decits. Trifn
rst showed that it was not possible to have both cheap sources of capital from
19
Buttonwood transactions represent preannounced meetings where a buyer with cash buys Bit-
coins from a seller that has the relevant information on a smart phone.
160 R.D. Porter and W. Rousse
abroad and positive trade balances. So, as Chinas trade surplus with the United
States has grown to be large, its international holdings have become more and more
concentrated in dollars. As a result, China has become increasingly wary about
having so many of its reserves in the U.S. dollars. In particular, they have looked
askance at the nonstandard U.S monetary policies that have been undertaken in the
aftermath of the nancial crisis.
In short, many Chinese are unable to diversify away from the yuan as much as
they might like. Given the binding constraints on their ability to maneuver, Bitcoin
might seem to be an attractive option by loosening the repressive effects of Chinese
currency yuan management. Indeed, Chinese ofcials initially supported Bitcoin as
an alternative to the dollar, which enabled it to acquire a strong following.20 Bitcoin
provided one method of getting funds out of China with fewer hassles both for
ofcials and entrepreneurs. For the Chinese, the inherent freedom and simplicity of
Bitcoin made it attractive; see (Rabinovitch 2013).
By July 2013, there were over 100,000 active Bitcoin nodes across the globe
with about one-fth of them in China. Both the Chinese previous experience with
the digital currency Q Coin and their penchant for gambling also played important
roles in boosting the demand for Bitcoin (Popper 2015). Of course, encouraging
Bitcoin is not the same as disparaging a dollar standard. Bitcoin might be an
attractive option for rich Chinese urban residents. It could mitigate some of the
relatively restrictive Renminbi currency regime and allow them to diversify.
In any event, Chinese demand for Bitcoin grew smartly over the fall of 2013,
boosted after Baidu, the Chinese equivalent of the Google search engine, began
adopting Bitcoin for certain payments in mid-October. Interest in Bitcoin within
China, according to Google Trends, is shown in Chart 2. The rst peak occurred at
about the time of the proposed Cyprus bail-in tax and ensuing bubble-like response
of BTC over the following month. The second much larger blip took place at the
end of November when one Bitcoin surpassed the price of an ounce of gold; it
subsequently trailed off to zero by mid-2014.
Given the relatively small size of the traded amounts of BTC, it is unlikely that
the surging interest in Bitcoin threatened the Chinese currency peg. Perhaps, the
dose of freedom was too difcult to t into existing regulatory frameworks. In any
event, in December 2013 China began to reverse course and slowly clamp down on
access to Bitcoin by limiting bank access. Gradually, Chinese ofcials put more
roadblocks in the way of Bitcoin trading.
To recap, Bitcoins reached a peak of $1153 in early December 2013 before
gradually retracing a fair amount of the surge as China put more restrictions on
Bitcoin trading. From Chart 3, it appears that the surge in Google trends users
across the world fairly closely matched the run-up the Bitcoin price in 2013 and
20
Chinese interest was partly the result of deliberate governmental policy in which a
state-sponsored TV show portrayed Bitcoin in a positive light.
Reinventing Money and Lending for the Digital Age 161
Chart 2 The Google trend interest in Bitcoin within China, 1/1/13 to 4/30/15
Chart 3 Overlay plot of Google trends for Bitcoin and dollar price of BTC
162 R.D. Porter and W. Rousse
early 2014. Subsequently, apart from the Mt. Gox collapse, the Google trends index
has plateaued. Conceivably the stationary state reached by the index in mid-2014
eventually moderated the dollar price of Bitcoin, a development which we take up
in Sect. 4.
The U.S. nancial crisis ultimately reverberated to Europe. As the fallout spread,
countries on the periphery began to have difculties in rolling over their debt, which
led to a full-fledged sovereign debt crisis in Greece, which, in turn, challenged
Cypriot banks that had heavily invested in Greek sovereigns (Kambas 2013).
The crisis moved to Cyprus when the Greek government subsequently defaulted
on their debt, which pushed two large Cypriot banks into insolvency. A full-fledged
panic ensued when Cypriot bank depositors discovered that their capital-short
banks were going to be recapitalized from within. European authorities planned to
convert depositors balances (including those with full deposit insurance) and
re-label them as equity ownership claims on the recapitalized banks. Specically,
on March 16, 2013, depositors woke up to such a plan: a one-off bank deposit levy
of 6.7 % for insured deposits and 9.9 % for balances above 100,000 on all
domestic bank accounts at two Cypriot banks. Not surprisingly, the announcement
shook nancial markets.21 And, indeed, the fallout continues to roil markets as
further policy repercussions continue to put burdens on depositors rst before
taxpayers.22
Immediately, many in Cyprus and elsewhere began to take a fresh look at the
opportunities for avoiding bail-in taxes by holding Bitcoins as a defensive
maneuver. Almost instantaneously, interest in Bitcoin jumped in a variety of
locations, including Argentina, China, Cyprus, and Russia (Chart 4). Speculators,
perceiving the new supply-demand conguration, promptly bid up the Bitcoin
price. The implied increase in demand set against the backdrop of a highly rigid
supply curve of new coins created pushed the price up to a peak of above $200
before ebbing back over the spring. The USD price of BTC began to drift up more
steeply in February and then even more so in March when the Cyprus crisis came to
21
The ECB, IMF, and European Parliament all agreed to this plan. Finally, at the end of July the
Cypriot central bank agreed to a 47 % haircut with international creditors on deposits exceeding
100,000 in the Bank of Cyprus with the conscated funds used to recapitalize the bank.
22
About a year later, the Europeans decided to extend the Cypriot bail-in strategy for all ECB bank
failures. The G20 reached a similar conclusion at their Melbourne meetings in the fall of 2014.
A rational depositor might now worry that that deposit insurance might not afford as much
protection and thus be more willing to assume the vagaries of holding Bitcoin to avoid the
potential bail-in taxes on their bank deposits.
Reinventing Money and Lending for the Digital Age 163
Chart 4 Google searches for Bitcoin for selected countries: Argentina, China, Cyprus, and
RussiaMarch to June 2013
a boil. Part of the peak outside of Cyprus appears to be in response to the price of
Bitcoin itself, which peaked in mid-April.
Chart 5 shows the dollar price of BTC at the Winkdex index. After the bail-in tax
was announced, the price of Bitcoin immediately shot up. (The Google trends
information in Chart 4 suggests that the slightly more delayed response occurred in
China.) The Russians who were heavily invested in Cyprus clearly had a direct
interest in BTC because of their experiences in Russia and the former Soviet Union,
see (Porter and Judson 1996), but so did many others.
After the bubble burst, the BTC price nosedived but soon stabilized and
eventually appeared to strengthen over the fall. In retrospect, it should not be
surprising that such a large induced shift in demand set against the highly inelastic
ongoing Bitcoin supply function of new coins resulted in the dollar price of Bitcoin
jumping in the very short run before reversing course, i.e. the intermediate price
peak was not necessarily that sustainable in the short run.
The coins arrive mechanically as a Poisson process in lockstep with Satoshis
protocol.23 The fallback in price occurred when the demand burst ran its course so
23
A prize block is found about every ten minutes. It is a Poisson process with parameter with
chosen so that 2016 blocks are found on average every two weeks. Since the expected number of
events is proportional to the elapsed time between prizes, or ten minutes, i.e., it follows that 2016/
(2 * 7 * 24) Bitcoins are found on average in an hour.
164 R.D. Porter and W. Rousse
that incoming supply of Bitcoins can only be priced at a lower value to equilibrate
the declining flow demand with the increased flow supply. The mini blip in the
price of BTC evident in Chart 5 may align with some denitions of a nancial
bubble, but we see it as a predictable response to the after-effects of the bail-in tax.
Namely, it is the expected result from a downshift in the flow demand for Bitcoin
set against the xed Poisson supply process of new Bitcoins.
This announcement of the bail-in tax led to the outpouring of interest in Bitcoin on
Cyprus from two immigrant groups who had gone to that Island to escape monetary
and civil disruptions in their home countries, Lebanon and Russia. Both became
major deposit holders in Cypriot banks.
Russian language accesses in Wikipedia of the word Bitcoin skyrocketed by a
factor of over 2.4 from 74,380 requests in March of 2013 to 178,903 in April as the
Bitcoin price peaked at around $250 on April 9 before falling just as sharply to
about one-fourth of that the next day. But the decline was relatively short-lived, and
the currency subsequently stabilized at around $130 before advancing over the fall.
Chart 6 shows a striking correlation between the price movements around the time
of the bail-in tax and access of Bitcoin by Russian speakers.
Its unclear how much of the price swing is attributable to the Cypriot proposed
bail-in tax. A simple exploratory regression of prices or price changes on the daily
Russian-language access requests (Table 1), nds signicant coefcients on the
access requests for three different specications. Of course, these simple regressions
are hardly denitive due to their small sample size; at best they can only be
suggestive. The response could rationally extend well beyond Cyprus to other
places such as Argentina, which reportedly also had a surge of interest in Bitcoin as
a result of the Cypriot episode.24
24
A kitchen-sink regression could include downloads of the Satoshi client in various countries,
which is a clearer indication of more active interest than an encyclopedia inquiry. Also, the
behavior of existing Bitcoiners or miners would also affect the price.
Reinventing Money and Lending for the Digital Age 165
Chart 6 Closing price of BTC in dollars on Mt. Gox and Russian language Wikipedia accesses of
Bitcoin showing shows the positive correlation over rst 14 days of April 2013
In many ways, Iceland could be seen as an ideal place for a virtual currency. It had
an educated workforce who understood modern nance.
The traditional shing-based economy was altered dramatically. Financial engineering
became the preferred career path of ambitious youth, instead of the traditional
natural-resource management. Young men on the streets of Reykjavk were as likely to
166 R.D. Porter and W. Rousse
Table 2 Google trend scores Rank Country or City Google trend score
for Bitcoin from 2011 through
June 2014 1 Iceland 100
2 Estonia 94
3 United States 79
4 Netherlands 77
5 Czech Republic 76
6 Canada 75
7 Finland 73
8 Hong Kong 73
9 Cyprus 71
10 Slovenia 66
know the Black-Scholes formulas as the yields from the days salmon catch (Bagus and
Howden 2011, 12).
This initial condition may explain the heightened interest in Bitcoin evident in
Table 2. Surprisingly, the Google trend index for the term Bitcoin scored highest in
Iceland over the period from 2011 to 2014 June. Even granting a greater smattering
of nancial knowledge on the Island than elsewhere, this result still seems rather
anomalous. Why would this island nationwith a small population and closer to
Greenland than Scandinaviahave so much interest in Bitcoin than any other
location?
One possible explanation was the capital controls that were introduced in the
aftermath of the nancial crisis, Boyes (2009). When the nancial crisis hit Iceland
immediately after the Lehmann collapse in the early fall of 2008, the Central Bank
of Iceland was unable to be the lender of last resort. It had no choice but to let 90 %
of its banking system collapse (Gudmundsson and Thorgeirsson 2010) and intro-
duce controls on fund movements to avert an even larger collapse.
Also, Iceland might be a candidate for a virtual currency Boyes (2009). The
country had experienced an exceptionally erratic monetary policy for decades that
had reduced the purchasing power of the Krona relative to the dollar to less than
1/120th of what it was 40 years earlier.
Thus, the prospect of a virtual Icelandic currency as a substitute for the unstable
Krona had to have some appeal when it was announced on the Bitcoin forum on
February 2, 2014. The Icelandic MBC was called Auroracoin and based on the
Litecoin.25
Auroracoin is designed to break the shackles of the at currency nancial system in Iceland.
Iceland has been hit hard by nancial meltdown and inflation. Not only did the entire
banking system collapse in 2008, but the monetary history of Iceland is one of inflation,
devaluation, and currency controls. Auroracoin is an opportunity for Icelanders to free
themselves from currency controls and government debasement of the currency.
25
See http://auroracoin.org.
Reinventing Money and Lending for the Digital Age 167
Chart 7 Comparison of Google trends for Auroracoin and Bitcoin on Iceland, from 2011 to
4/30/15
This announcement had to be at least a partial catalyst for the extraordinary level
of interest in Google trends for the word Bitcoin evident in Table 2 and in
Chart 7.26
On March 25, 2014, 31.8 Auroracoins would be available to each inhabitant.
Half of the coins would be dropped and half mined using a Litecoin scheme. Before
the actual airdrop, a speculative frenzy propelled each existing mined coin to nearly
$96.81 (corresponding to a market cap of over one billion dollars) 3 weeks before
the launch. So while there appeared to be a considerable number of Icelanders who
were intrigued in some way by the concept, the actual take-up rate was only about
10 %. Afterward, the price of an Auroracoin continued to sink, ultimately stabi-
lizing around 20 in early June 2014.27
Thus, the Icelandic reception of Auroracoin seems rather modest relative to the
potential demand, as embodied in the ranking from the Google trends. Reportedly
there were some mechanical difculties in acquiring the coins, and convenient
wallet apps were not initially available. So the reluctance to embrace Auroracoin
may have been more a problem of execution and implementation rather than the
underlying concept. To be sure, Auroracoin might be conceptually confusing to
many Icelanders even if the coins were free for the taking.
For any new currency, there is always the question of whether there will be
partners to exchange coins if one decides to hold onto them. It is this disparity that
lies at the heart of the difference between the demand for Auroracoins and for U.S.
banknotes outside the United States. For U.S. banknotes, one knows they will trade
tomorrow at virtually the same price as today. One may be somewhat more assured
of that for Bitcoins too since theyve been around for over 6 years and have
acquired some liquidity and universality. But for Auroracoins, there was no
26
Margeirsson (2014) discusses the strong interest in Bitcoin on Iceland.
27
As of late July 2015, one Auroracoin is worth a little over 3.
168 R.D. Porter and W. Rousse
assurance that Icelanders would be able to sell their coins tomorrow at any price
close to todays price. If enough Icelanders believed the coins might soon become
worthless, they would quickly try to get rid of them. So in accord with Greshams
law, it appeared that the inhabitants decided to spend the mined coins near the peak
rather than wait.28
Could the problems that Auroracoin encountered be overcome? A more suc-
cessful initial strategy for phasing in a virtual currency might have placed a floor on
the dollar price of the currencyto support it long enough for residents to became
comfortable with it. No doubt, nding such a price might be difcult. Still, when the
Krona has been so haphazardly managed for so long, it might be worthwhile to
pursue something else. If Auroracoin is not the answer, one might imagine
something less radical, such as a floating peg to basket of Scandinavian currencies
or the Euro.
We examine raw market prices to evaluate whether Bitcoin (BTC) has the requisite
stability to be considered a reliable store of value. Compared to at currencies,
Bitcoins ability to be immune from the ravages of inflation is a big plus in some
states of the world. On the other hand, the considerable operational instabilities on
Bitcoin exchanges undoubtedly have put a damper on Bitcoins overall acceptance
rate for many newcomers.29
Given golds historical role in backing currencies, it is convenient to compare
BTC with gold. Both are scarce commodities. Historically gold has been a popular
alternative to at monies because of the inherent difculty in extracting more ore.
Bitcoin catapulted onto the worlds stage when one Bitcoin exceeded the price of
an ounce of gold. Given the increasing costs of extracting either gold or mining
Bitcoin, it is useful to compare the prices of the two mined commodities. Thus,
we will compare BTC with the exchange-traded fund, GLD, which accurately
tracks the spot price of gold. For concreteness we will focus on the recent period
from April 1st 2013 to March 31st 2015. This period captures the mini BTC price
bubble provoked by the European bail-in scheme for Cyprus as well as the dramatic
28
This possibility was anticipated by Margeirsson (2014).
29
We believe Bitcoins strength lies in the absence of any central authority of any kind. Ironically,
this decentralized structure has also arguably been its Achilles heel, as Moore and Christin have
chronicled in their study of continuing problems plaguing a number of exchanges (Moore and
Christin 2013). Well before Mt. Goxs bankruptcy in 2014, they showed that nearly half of all
Bitcoin exchanges had disappeared in the previous 3 years. We believe these are temporary
problems reflecting the newness and complexity of the technology and the naivet of the entre-
preneurs who started exchanges. These failures are to some degree implicit in the volatility of
market price quotes from Coinbase that we use in this study. But without further information, we
are not able to break them out.
Reinventing Money and Lending for the Digital Age 169
price changes induced by the vacillating policies toward Bitcoin by the Chinese
authorities.
The latter bubble raises a red flag that BTC may be too volatile to gain critical
mass as a viable private currency. Simply, if an asset is too volatile ex ante, a
number of risk-averse investors will shy away from holding it as a store of value.
As such, it may just not reach critical mass for acceptance as a viable private
currency. Thus, the feature that makes Bitcoin an attractive inflation hedgethe
strict limit of only 21 million coins that will ever be created could be counter-
balanced by excessive period-to-period price volatility. However, such a conclusion
appears premature. Over time, BTC has actually become somewhat less volatile
and, arguably, is gradually beginning to resemble other conventional inflation
hedges such as gold.
To begin our volatility investigation, the simple daily percentage change in U.S.
dollar price for both BTC and GLD are calculated and then plotted in Charts 8
and 9, respectively.
Not surprisingly, the daily percentage change in the price of BTC is more
volatile than that of GLD. However, the daily percentage change in BTC appears to
be diminishing over time, partially closing the volatility gap between the two assets.
Chart 8 illustrates that throughout most of 2014 and 2015 the huge daily price
movements of 30 % or greater that existed in 2013 vanished. So, it suggests that the
daily price volatility of BTC may be diminishing. On the other hand, Chart 9
indicates the daily percentage change in price for gold remains quite stable. Except
for a few spikes, it is rare to see a daily gold price move that exceeds 5 percent.
Digging a little deeper into the data, we compute the monthly Relative Standard
Deviations (RSD) of the prices for both series. Namely, the monthly RSD are
calculated as follows:
170 R.D. Porter and W. Rousse
s
x 2
=
N
100 = RSD %
Next we plot the 3 month moving averages of these RSDs. Then, using Excel we
simply superimpose trend lines through the 3 month moving averages. BTCs
results are illustrated on Chart 10.
This crude analysis, depicted in Chart 10 for BTC, demonstrates that the price
volatility in BTC is falling by approximately 40 basis points a month. If this trend
were to continue, BTC price volatility would be comparable to that of GLD within a
year.
Chart 10 BTCs Monthly RSD 3 Month moving average from 4/1/2013 to 3/31/2015
Reinventing Money and Lending for the Digital Age 171
Chart 11 GLDs Monthly RSD 3 Month moving average from 3/1/2005 to 3/31/2015
Since March 2005, we can extract data on the exchange-traded fund, GLD. We
will use this 121 months of data to examine the stability of GLD, Chart 11. The
trend line in Chart 11 is almost horizontal suggesting that volatility of GLD is
stable. This simple analysis suggests two things: First, the price volatility of gold is
stable. And secondly, the price volatility in BTC is falling. If this latter trend
continues, the likelihood that BTC can be used as a store of value will increase.
Most U.S. $100 s are held outside the country, many in two countries with
uneven monetary histories, Argentina and Russia; see (Treasury 2006). From that
perspective, it is tting to then compare BTC with the Argentinian Peso (ARS) and
the Russian Ruble (RUB).
The exchange rate data used in the analyses are the United States Dollar to the
Argentinian Peso (USD/ARS), and the United States Dollar to the Russian Ruble
(USD/RUB). In parallel fashion to the comparison made earlier between BTC and
GLD, we next consider the monthly RSD% of both USD/ARS and USD/RUB and
plot the 3 month moving averages of these in Charts 12 and 13 with OLS trend
lines superimposed through the averages.
The three (3) month moving average line (illustrated in Chart 12) shows a
volatility spike in the Argentinian Peso. The 3 month moving average peaked in
January of 2014. Since that spike, the moving average line of the RSD is below
where it was before the volatility spike. Thus, because the spike occurred before the
midpoint of the time series, it is not surprising the OLS linear trend line slopes
downward somewhat.
Chart 13 illustrates that later during this time period, the Russian Ruble also
experienced a volatility spike, which appears to have lasted longer. As the chart
illustrates, the three (3) month moving average line peaks in February of 2015.
Volatility of the rubble, measured by the 3 month moving average of the RSD, is
rising. According to the very crude linear OLS estimates, it is raising approximately
16 basis points a month.
172 R.D. Porter and W. Rousse
Chart 12 USD/ARS Monthly RSD 3 Month moving average from 4/1/2013 to 3/31/2015
Chart 13 USD/RUB Monthly RSD 3 Month moving average from 4/1/2013 to 3/31/2015
Obviously, it may not be sensible to imagine that such linear forecasts would
necessarily continue very long. But, what is interesting is that for a number of
reasons (beyond the scope of this chapter), volatility in these currencies appears to
change rather abruptly. Volatility is increasing in certain periods, while moving in
the opposite directions at other times. Yet, the conventional wisdom holds that at
currencies are acceptable stores of value. While that proposition is generally true, it
surely does not hold for currencies that have repeatedly experienced high bouts of
self-inflicted inflation such as Russia and Argentina; historically these currencies
have been prime candidates for using alternative store of values, such as the U.S.
Reinventing Money and Lending for the Digital Age 173
dollar, and conceivably Bitcoin some day.30 The data used in this chapter suggest
BTCs volatility, which has often been viewed as problematical, is not that different
than that from some national currencies.
In order for BTC or any other MBCs to gain critical mass, they must also retain
their value over the long haul. This capability has been one of golds talking point
since Nixon closed the gold window. Extreme price movements of cryptocurrencies
clearly limit such capability. However, if, as we have shown, Bitcoin volatility
continues to decline, it could become a more viable store of value and gain con-
siderable more adherents. And, since private currencies are networked goods, it
might gather a more signicant foothold and elongate the underlying trend depicted
in Chart 10.
But volatility is not the only characteristic that brands money as a viable store of
value. Return on investment is also important. Of the four assets we have been
considering, BTC had the highest return on investment delivered by the four assets:
Bitcoin (BTC), Gold (GLD), the Argentinian Peso (USD/ARS), and the Russian
Ruble (USD/RUB) during the period under investigation from 4/1/2013 to
3/31/2015. In fact, BTC was the only asset that increased in value over the specied
time period. In spite of its huge price spike and collapse, BTC still returned
+137.36 % to investors during this period.
30
There is growing interest in Argentina in Bitcoin, see http://www.nytimes.com/2015/05/03/
magazine/how-bitcoin-is-disrupting-argentinas-economy.html?_r=0.
31
http://www.cutimes.com/2014/08/14/peer-to-peer-lending-poised-for-more-growth-fed.
174 R.D. Porter and W. Rousse
During this period, two new U.S. rms, LendingClub and Prosper, grew to
become industry leaders in P2P lending. They opportunely entered the scene just as
the nancial crisis was unfolding. The crisis handcuffed commercial banks, which
had to restore their balance sheetsto raise equity and pay down TARP loansto
be in a position to mitigate against further shocks as the crisis continued to deepen.
So the crisis itself shielded these new P2P lenders from facing commercial bank
competition during their startup period. As a consequence, they experienced
compound double-digit annual growth by exploiting the Internet to connect to
participants at a low cost.
The LendingClub founder, Renaud Laplanche, thought that credit card compa-
nies charged extortionate interest to their consumers on unpaid balances. Given the
minuscule rate of interest earned on bank deposits then, he also thought that the
very wide spread signaled an opportunity, and LendingClub seized it.32 Remark-
ably, since its inception in 2006, over $9 billion of loans have been funded on their
platform.33 These loans not only have a lower interest rate than comparable loans
made by traditional banks, but they also pay a higher interest rate than banks. Thus,
the overall spread between borrowing and lending rates narrows, resulting in a
win-win situation for both borrowers and lenders.
LendingClubs main competitor has been Prosper Lending LLC.34 Like Lend-
ingClub, its loan origination growth rate has been fairly impressive. Since its
inception in 2006, over $3 billion has been borrowed on Prospers platform with
growth recently accelerating.35
These rms prot by using P2P technology to bring down interest rate spreads.
The Internet allows these rms to match borrowers and investors without having to
build branches and staff them.
Another advantage the P2P model has over traditional bank lending models is
that it removes the need for deposit insurance and the associated heightened reg-
ulation to curb risk-taking by prot-seeking banks. In contrast, the only risk in an
individual P2P loan stems from the full or partial default by an individual borrower.
Moreover, the resulting loss is conned just to the individual investor. So if the
loans are statistically independent and based on comprehensive credit scoring
model, the losses can be correctly evaluated ex ante and bounded. When individual
losses occur, as they undoubtedly will, the individual lender loses but there is no
externality. There are no cascading losses across suites of lenders, which occur in
classic banking lending crises, as cumulative borrower defaults eventual lead to a
chain of bank failures.
32
http://www.economist.com/blogs/schumpeter/2013/01/lending-club.
33
https://www.lendingclub.com/info/statistics.action.
34
http://www.lendstats.com.
35
https://www.prosper.com/.
Reinventing Money and Lending for the Digital Age 175
36
https://btcjam.com.
176 R.D. Porter and W. Rousse
available.37 However, to give a sense of the amounts, BTCJam has been the
intermediary for roughly $15 million of loans. For a start-up company, operating in
completely uncharted waters, these numbers are noteworthy. If the company were
to continue at such rapid rates, one can easily extrapolate that it could post com-
parable numbers to LendingClub and Prosper over a decade.
Perhaps the most impressive part of BTCJams lending experience is the breadth
of its reach: It has serviced 16,342 loans in 121 countries with many of the loans in
areas normally considered to be unbanked. Thus, a sizable majority of the earths
population, which remains unbanked, could be potential customers for this new
BTC lending technology. The growth possibilities would seem to be extraordinary.
The transnational scope of Bitcoin is what is impressive with BTCJam being the
rst P2P lending platform to cross national borders successfully.38 Using BTC as
the backbone for the network, BTCJam (and the other rms in this space) are
breaking down the national borders, which characterize the centralized nancial
system thats been prevalent up until now.
As a result of such lending, one might expect such P2P lending rms to enable
smaller-sized loans. Under traditional centralized lending arrangements, its often
unprotable to launch a nancial business in many areas of the world that are
mostly rural and quite poorthe preconditions for remaining unbanked. But, in
theory, the size of the loan is irrelevant to BTCJam. The majority of their costs are
xed, namely maintaining and developing the platform. They only collect a closing
cost, which is a percentage of the loan amount. So, these lenders have a strong
incentive to spread their xed costs and close as many loans as possible, which
allows them to accommodate small and short duration loans.
In fact, the data is quite consistent with this description. During its rst year of
operation, the average size of a BTCJam loan was approximately $400 to $600.
Prosper, on the other hand, had an average loan size about ten times larger, $4,800
during its rst year in business.39
Firms like BTCJam are nudging nance away from the traditional structures
involving pyramidal central controls, toward those based on the decentralization of
trust. The products being lent are BTCs. The Bitcoin Blockchain is completely open
sourced and decentralized, and if authorities permit this to continue to develop, the
possibilities are vast. Using this BTC Blockchain technology, one can imagine a
true paradigm shift in nance: an environment where the role of prot-seeking
intermediaries is reduced, and the need for any central authority is signicantly
diminished. As in all lending, there is no guarantee that investors will be repaid. But
unlike bank lending, there is no deposit insurance overhang. But failures hit indi-
vidual investors and not large banks supported by deposit insurance and a gov-
ernment backstop. Moreover, the possibility of repeat lending arrangements for
37
The problem is that the price of Bitcoin fluctuates at a relatively high frequency, and the chart
only gives the results on a monthly average basis.
38
http://www.netbanker.com/p2p_lending/.
39
http://www.netbanker.com/2013/11/btcjam_p2p_lending_via_bitcoin.html.
Reinventing Money and Lending for the Digital Age 177
successful borrowers can buoy the returns, particularly when the alternative
arrangements are unattractive.
6 Conclusions
Satoshi Nakamotos creation of the Bitcoin Blockchain has opened up several new
avenues for monetary exploration beyond the traditional realm of the nation state.
There was a huge gold rush like movement toward Bitcoin and other new
math-based currencies in 2013. This swoon began with the European imposition of
a bail-in tax on Cypriot deposits at two large banks. It exploded as the Chinese
jumped on the bandwagon but then receded amidst growing regulatory pushbacks
in China and elsewhere.
Without doubt, the creation of the Blockchain is generating whole new ways of
thinking about organizing activities through decentralized trust mechanisms rather
than traditional centralized approaches. Andreas Antonopoulos has emphasized this
theme in Antonopoulos (2014). Indeed, IBM has been exploring the Blockchain to
organize the Internet of Things (Higgins 2015).
Sufce it to say that the nation states monopoly on money design and imple-
mentation is under assault by a myriad of developments. These innovations raise
the possibility that math-based currencies could more securely and cheaply connect
the world.
We have shown that an entirely new lending mechanism like BTCJam has
brought P2P lending opportunities to poorer parts of the world. Previously, such
opportunities have only been available to residents of advanced countries in the
form of P2P lending organizations such as Lending Club. These innovations have
opened the door to Bitcoin lending on a scale that was unimaginable a decade ago.
The poor of the earth who remain unbanked now have access to rst-world lending
possibilities.
The pace at which these advances will effectively reorder nation state monetary
design is unclear. The invention of the Blockchain is upsetting enough traditional
payment means and opening up the possibility of a different kind of monetary order
harkening back, perhaps, to an earlier period when money was more private.
Finally, the current worldwide crisis in which traditional monetary policy is
virtually impotent at the zero bound of interest rates raises some questions about
how to proceed.40 Reworking regulation and monetary policy to accommodate the
manifold opportunities spawned by the Bitcoin Blockchain revolution will be
neither easy nor straightforward. But clearly the time has come to reconsider how
we pay, and bank in an ever more tightly coupled world in which distance is
receding, and the far edges may affect us at any moment.
40
Also, see http://www.bankofengland.co.uk/publications/Pages/speeches/2015/840.aspx.
178 R.D. Porter and W. Rousse
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Author Biographies
Policy, Econometrica, Economic Letters, Economic Modelling, the Journal of Economics and
Business, the Journal of Economic Dynamics and Control, the Journal of Monetary Eco-
nomics, the Journal of Money, Credit and Banking, and the Journal of Payment Strategy and
Systems. He has also contributed to several Federal Reserve System Publications including the
Federal Reserve Bulletin and the Chicago Federal Reserve Banks Economic Perspectives.
Diana C. Biggs
According to the World Bank Global Findex (2014 data), two billion people
equating to 38 % of the worlds adult populationdo not use formal nancial
services (The World Bank Group 2015). For the most part, these are poor popu-
lations who are excluded from even the most basic nancial services offerings,
specically the ability to spend, the ability to store, and the ability to invest. The
World Bank research estimates that 73 % of poor people are unbanked because of
costs, travel distances and the often burdensome requirements involved in opening
a nancial account (The World Bank Group 2015).
Financial inclusion, or inclusive nancing, is the delivery of nancial services at
affordable costs to sections of disadvantaged and low-income segments of society
(Wikipedia 2015). It is generally accepted that nancial access is the gateway to edu-
D.C. Biggs ()
Centre for Blockchain Technologies, University College London, London, UK
e-mail: diana.biggs@gmail.com
cation, health, housing and other necessities to growth and development. In addition,
access to nancial services is critical for access to economic opportunity, increases
productive investment and consumption, and contributes to womens empowerment.
Financial inclusion has today become a particular area of focus for non-bank
nancial services providers, given the under-servicing of those populations to date
from traditional banks. These non-bank offerings include nonprots and NGOs,
community-based institutions and cooperatives, telecommunications providers,
micronance institutions, post ofces and, in recent years, some nancial tech-
nology (ntech) start-ups.
Remittances, the transfer of money by migrant workers to their home countries,
exceed both ofcial development assistance and foreign direct investment (ex-
cluding China) as a source of funds for developing countries (Cook and McKay
2015). With this scope, their benets to the recipient economies are well recog-
nized, including aiding in the reduction of poverty, enhancing entrepreneurship,
access to formal nancial services, communication and information technologies,
and contributing to spending on health and education.
Overall nancial inclusion and remittances have been areas of focus for the
application of new technology, with the aim to leverage new tech in order to
improve and enhance access to such services. This chapter will examine two
technology-based solutions for providing nancial access to populations left outside
the sphere of traditional nancial services offerings, rst with an overview of
mobile money and secondly an introduction to non-bank remittance solutions
enabled by technology such as digital currency and the blockchain.
Mobile Banking can be dened as the provision and availment of banking and nancial
services with the use of mobile telecommunication devices. In the broadest sense, this
may include facilities to send and receive payments and, when provided by a traditional
nancial services provider, to conduct bank and stock market transactions, administer
accounts and to access customized information (Tiwari and Buse 2006).
The increasing interest in and proliferation of mobile banking offerings around
the world has been driven by several factors, including:
Increasing penetration of mobile phones in societies across the globe: GSMA
Intelligence estimates that the total number of active SIM connections at end
2013 was 6.3 billion (GSMA 2014).
Globalization and increasing availability of mobile services have moved it from
a luxury item to what is broadly viewed as a necessity (Tiwari et al. 2007).
1834 year olds increasingly favor new technologies to traditional services
(Canning 2013).
Rapid technological improvements in mobile devices and networks, including
increased processing power, greater battery life and dramatically improved
networking speeds.
How Non-banks are Boosting Financial Inclusion and Remittance 183
While in Western markets banks and other nancial services institutions see mobile
offerings as an expansion of their services, this chapter will focus on the opportunity
for mobile to provide nancial services to under- and unbanked populations
globally, particularly in developing markets.
To date, the majority of mobile banking offerings are centered around mobile
money programs, which allow for mobile payments, such as bills or peer-to-peer
transfers. Mobile money is already a fairly mature industry, with established
offerings in the majority of emerging economies (GSMA 2015).
For the purposes of this chapter, we follow the denition of mobile money of the
GSMAs Mobile for Development Mobile Money Programmes 2014 State of the
Industry report. Mobile money services refer to offerings which do not require a user
to be banked with any nancial institution and whose network transaction points lie
outside of traditional bank offerings, i.e. bank branches and ATMs. These services
offer an interfaces available on basic mobile phones, rather than the need for a
smartphone app. This denition does not include mobile banking services where
mobile is simply a channel for accessing traditional banking services (GSMA 2015).
Mobile money, being value held within the mobile phone, are typically offerings
of either the Mobile Network Operators (MNOs), such as Airtel with Airtel Money
or Safaricom with M-Pesa, or a collaboration between an MNO and a bank. In
certain countries, these services fall under the regulatory oversight of the nancial
services regulatory and may require licensing.
As of 2014, there were 255 mobile money services available across 89 countries
worldwide, covering over 60 % of developing markets, according to the GSMA. In
terms of adoption, there were 299 million registered mobile money accounts as of
December 2014, which represents 8 % of mobile connections in the markets
offering mobile money services, (GSMA 2015) indicating a strong growth oppor-
tunity for the usage of these services.
Geographically, usage of mobile money in Sub-Saharan Africa (SSA) surpasses
other regions, accounting for 53 % of live services globally as of December 2014
(GSMA 2015). The World Bank Groups Global Financial Inclusion Report 2014
found that 12 % of adults in SSA reported having a mobile money account. Of this,
half had both a mobile money account and an account at a nancial institution, and
half a mobile money account only. At 58 %, Kenya holds the highest share of adults
with a mobile money account, followed by Somalia, Tanzania, and Uganda with
approximately 35 % (Demirguc-Kunt et al. 2015).
In other regions, usage of mobile money remained much lower, with only three
percent of adults with a mobile money account in South Asia, 2% in Latin America and
the Caribbean, and less than one percent in all other regions (Demirguc-Kunt et al. 2015).
184 D.C. Biggs
Mobile money services allow the digital storage of funds within a mobile-based
account, which can then be used for a variety of goods and services including bill
payment, mobile top-up of pre-paid accounts, peer-to-peer transfer, bulk dis-
bursements (i.e. employee payments), merchant payments and receipt of interna-
tional remittance. At present, domestic peer-to-peer (P2P) transfers and airtime
top-ups remain the most common product offerings amongst mobile money service
providers.
The majority of mobile money services remain cash-based in some way, for
example the cashing out of remittances received from abroad via mobile money, or
cash-in funding of accounts. For this, providers rely on physical access points,
which are predominantly agent-based networks. At the end of December 2014,
there were 2.3 million mobile money agent locations globally, an increase of 45.8 %
from the previous year. Using bank branch data available from the IMF Financial
Access Survey (FAS) Database, this indicates that mobile money agent outlets
outnumber bank branches in 75 % of the 89 markets where mobile money is
available today (GSMA 2015). In addition to agent networks, micronance insti-
tutions, ATMs, bank branches, postal ofces and even petrol stations also serve as
access points for mobile money across various regions.
Mobile money brings several advantages both to the customer and the service
provider:
Improved efciencies: increased speed of payments and lower costs to send and
receive over traditional methods;
Enhanced security, monitoring, and transparency, reducing opportunity for
crime and fraud;
Allows for broader geographical coverage, removing physical barriers and
reducing time away from work and home to travel to a brick and mortar
nancial institution;
Serves as a convenient initial entry point into the formal nancial system
(Demirguc-Kunt et al. 2015), both by the introduction of such services to
customers via the mobile phone and in the collection of user data it allows,
which can then be applied to functions such as credit-scoring.
As of 2014, in 16 countries around the world the number of mobile money
accounts outnumbered the number of bank accounts (GSMA 2015). This is one
indication of how mobile money promotes nancial inclusion. With the conve-
nience and increasing accessibility of mobile phones, and the behavioural famil-
iarity of topping up a mobile phone via local agents, mobile money serves as an
enabling gateway to the access of nancial services.
How Non-banks are Boosting Financial Inclusion and Remittance 185
Mobile insurance: Mobile insurance uses the mobile phone to provide microin-
surance services to the underserved. The service must allow subscribers to manage
risks by providing a guarantee of compensation for specied loss, damage, illness,
or death.
Mobile savings: Mobile savings providers provide savings offerings via mobile
phone. These services allow subscribers to save money in an account that provides
principal security, and, in some cases, an interest rate.
Mobile credit: Mobile credit providers provide users with credit offerings via
mobile phone. The service allow subscribers to borrow a certain amount of money
that they agree to repay within a specied period of time, at an agreed amount of
interest and/or fees.
Case study: M-Shwari
M-Shwari is a paperless banking service available in Kenya, offered through
Safaricoms mobile money transfer service, M-PESA. M-Shwari offers both sav-
ings and loan products and was launched via a partnership between Safaricom and
the Commercial Bank of Africa (CBA). Building off the success of M-PESA as a
mobile money service in Kenya, M-Shwari extends this offering into savings and
credit providing the benets of traditional banking products, including interest on
deposits, deposit insurance and access to credit to unbanked populations. For their
credit offering, M-Shwari were the rst large-scale loan provider to leverage data
from mobile usage to provide input into credit decisions, by creating an initial credit
score (Cook and McKay 2015). This use of mobile data for credit-scoring decisions
is increasingly being looked at by traditional banks, credit card companies and
social entrepreneurs as a means to facilitate credit offerings to previously under-
served populations, who lack the necessary data for existing credit score methods.
Remittances refer to earnings in the form of either cash or goods sent by migrant or
overseas workers to support their families back home. The number of international
migrants living outside their country of origin was an estimated 247 million in 2013
and is expected to exceed 250 million in 2015 (World Bank 2015). Money sent
home by migrants now represents one of the largest foreign income inflows to
developing countries and in recent years have been rising steadily, although this
growth has recently slowed due to factors including the economic slowdown in
Europe and the impact of declining oil prices on the Russian economy (World Bank
2015).
The majority of remittance money, circa 8090 %, is spent on basic necessities
including food, clothing, shelter, health care and education, (IFAD Remittance
Factsheet 2009) thus playing a strong role in poverty reduction.
186 D.C. Biggs
The global average cost of sending $200 was 7.7 % in the rst quarter of 2015, with
a weighted average cost (by size of bilateral remittance flows) of 6 %, indicating
lower costs in higher volume corridors (World Bank 2015).
How Non-banks are Boosting Financial Inclusion and Remittance 187
Table 2 Total avg. remittance cost by region of the world (World Bank 2015)
Region Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2
2013 2013 2013 2013 2014 2014 2014 2014 2015 2015
East Asia & 8.97 8.88 9.00 8.28 8.52 8.38 7.92 8.12 8.13 8.11
Pacic
Europe & 6.77 6.70 6.68 6.29 6.49 6.35 6.17 6.22 6.11 6.02
Central Asia
Europe & 8.43 8.35 8.41 7.93 8.18 7.92 7.67 7.54 7.20 7.18
Central Asia
excluding Russia
Latin America & 7.77 7.28 7.26 7.02 6.21 5.57 6.02 6.03 6.14 6.78
Caribbean
Middle East & 7.81 7.83 7.61 7.80 8.32 8.29 8.25 8.63 8.41 8.21
North Africa
South Asia 7.16 7.02 7.12 6.58 6.56 6.45 5.97 5.94 5.96 5.74
Sub-Saharan 12.2 12.1 12.3 12.6 11.7 11.6 11.3 11.5 10.2 9.74
Africa
Global 9.05 8.88 8.93 8.58 8.36 8.14 7.90 7.99 7.72 7.68
With the estimated total global remittances of $586 billion for 2015 (World
Bank 2015), at the current weighted average cost of 6 %, this would mean
approximately $35 billion in fees. These fees can occur at the sender side both as an
upfront fee as well as a currency-conversion fee typically held within the exchange
rate. Smaller money transfer operators may also charge a fee to the recipient upon
collection).
As seen on the chart above, Sub-Saharan Africa remains the most expensive
region to send remittances to, at 9.74 % at Q2 2015, and the South Asia region the
least expensive at 5.74 %.
Remittance costs have been declining over time, partly due to advancements in
technology which help to drive down costs, as well as increasing competition.
Proponents of the digital currency space have been optimistic about the potential for
bitcoin, as a means of cross-border value transfer, to transform the remittances
industry.
In the remittance use case, sending money across long distances, borders, or
even across the world, bitcoin and blockchain technology offers potential benets
across the value chain over existing money transfer solutions.
As a decentralized peer-to-peer system, the bitcoin blockchain is able to replace
traditional nancial services providers for the transfer of value, leveraging a global
network of actors, called nodes which serve to process and conrm the trans-
actions 24 h a day, seven days a week. These transfer values through the system are
done in real-time, currently with a typical transaction conrmation time of
10 minutes. The system is essentially trustless, as no central authority has power
over the network, and transactions are publically and immutably recorded on a
digital ledger, the blockchain itself. All of this happens at near zero-cost, at typi-
cally only 0.0001 bitcoin (BTC) per transaction (Bitcoin Wiki 2015).
These properties represent signicant efciencies and cost-savings over tradi-
tional methods of value transfer led by nancial services institutions, by the nature
of the technology itself as well as the removal of slow and costly third parties.
How Non-banks are Boosting Financial Inclusion and Remittance 189
There are three options for the operational flow of funds in bitcoin remittance
solutions:
1. Bitcoin-only onboarding and offboarding
2. Bitcoin-only onboarding and both at and bitcoin offboarding
3. Onboarding and offboarding in both at and bitcoin
In each of these cases, the bitcoin blockchain is used for the intermediary
transfer of value and in options 2 and 3 the service provider, either at one or both
ends of the value chain, is responsible for the conversion of at to bitcoin.
On the sender side, in each option the sender typically has the option to send
value directly as bitcoin, using their own bitcoin holdings as purchased at a bitcoin
exchange, ATM or through an individual seller.
In option 3, the remittance service provider accepts another form of payment, i.e.
via credit or debit card payment, bank transfer, or cash. The service provider then
uses that payment to purchase an equivalent amount of bitcoin from their bitcoin
exchange of choice.
The bitcoin is then sent to the recipient for offboarding, handled either via the
services local entity, a local partner, or received directly as bitcoin.
Integrations between sending and receiving channels are typically done via API
calls between the systems involved.
While an informed public are growing increasingly aware of bitcoin, its use as a
currency and payment method remains relatively limited. As well, for users of
remittance solutions, trust is typically a paramount factor in selecting a provider,
and bitcoins at times negative image in the press may be a deterrent from services
which are outwardly promoting its integration. Therefore, for reasons of brand,
utility and adoption, an increasing number of service providers are using the bitcoin
blockchain merely as the rails upon which value is sent and working with partners,
including traditional payment methods and value stores, for on- and offboarding.
Traditional providers argue that the high costs of existing remittance offerings are
not simply imposed by the market out of greed or legacy transfer systems, but rather
are predominantly due to costs relating to the regulation and compliance imposed
on the industry by governments and nancial regulating bodies. Others attribute
some of this cost to the operational costs associated with the on and offboarding of
value in developing markets, where infrastructure and servicing may be limited.
The majority, if not all, bitcoin remittance solution providers subject themselves
to the same, if not greater, Know Your Customer (KYC) and Anti-Money Laun-
dering (AML) KYC and AML policy requirements as nancial institutions. This is
necessary both as a requirement by their own nancial institutions servicing them as
190 D.C. Biggs
While initially bitcoin-related companies were able to remain under the radar of
regulatory agencies, they are increasingly taking notice. For the remittance use-case
in particular, given that it involves the transfer of value from one country to another,
despite the fact that bitcoin itself may not be regulated, certain jurisdictions deem
these businesses to fall under the regulation pertaining to money transfer. In other
countries where regulatory bodies may not yet have taken a stance, many players
are choosing to actively engage with policy makers to mitigate potential issues in
the future and lobby for progressive policies around the technology.
There are several reasons regulatory bodies would want to maintain close watch
over the space, including the potential risk for money laundering, the potential risk
of circumvention of capital controls in relevant jurisdictions, and the need for
consumer protection.
192 D.C. Biggs
In the US, all businesses engaged in remittance activities, including those using
bitcoin or blockchain, must hold a Money Service Business or Money Transmitter
license. For many other countries, a Money Transfer Operator (MTO) license is
required.
As with other consumer nancial services offerings, regulators also require that
proper compliance policies and procedures, covering Know Your Customer
(KYC) and Anti-Money Laundering (AML), be in place.
The cost of these licenses and on-going compliance requirements can be quite
onerous for smaller start-ups but are a necessary cost of doing business in the space.
Volabit
SatoshiTango
Bitso
SurBTC
MondoMe
Remittances to Africa
Bitpesa
Bitsoko
Bitmari
Global/platform offerings
Align Commerce
BitX
Stellar
CoinJar
Bitrell
BlinkTrade
Pivoted or Closed offerings
Romit (pivoted to merchant payments)
Coincove (pivoted from remittance due to regulatory burdens in the US)
Beam (closed)
37Coins (closed)
Moneero (closed)
Buttercoin (closed)
Bitstake (closed)
Rebittance.org (comparison site; closed)
Coinbatch (unknown)
ArtaBit (unknown)
Peer-to-peer model
From 2014 onwards, we have seen a number of players come into the market with a
service offering of peer-to-peer remittance. Sometimes referred to as an Uber of
remittance, these players provide person to person transfers without the use of a
bank or third party intermediary. Sometimes referred to as a Human ATM net-
work, individuals can cash out money sent from other users via blockchain
technology.
Case study: Abra
Abra is a mobile phone app, available on iPhone and Android, which allows both
cash-in and cash-out via registered individuals or businesses, called Abra Tellers,
who facilitate the buying and selling of digital cash and receive a small fee, which
they themselves set, in return for the service. The mobile app is initially launching
in the US and Philippines, with more countries to follow (Abra 2015). Deposited
currency is transferred immediately to bitcoin, which is held on the individuals
194 D.C. Biggs
smartphone. By holding value in bitcoin, the company currently avoids any regu-
latory requirements for transmitting payments. To users, this use of bitcoin is
hidden.
Global/Platform offerings
In addition to consumer-facing bitcoin and blockchain-based remittance services,
two entrants in the space are designed as platforms with open APIs to serve as rails
for other businesses, non-prots and developers in the space.
One such example is Stellar. Stellar is an open source protocol for value
exchange supported by a nonprot, the Stellar Development Foundation. Servers
run a software implementation of the protocol, using the internet to connect to and
communicate with other Stellar servers and a consensus algorithm to conrm
transactions, thus forming a global value exchange network (Wikipedia 2015).
A decentralized protocol, it can be used to send and receive money in any pair of
currencies (Stellar FAQ 2015). It allows for near instant transactions and seamless
international payments at a very low cost. According to Wikipedia, two real-world
applications of the Stellar protocol include Oradian, a cloud-based banking software
company, which plans to use the Stellar network to connect micronance institu-
tions in Nigeria, and the Praekelt Foundation, which plans to integrate Stellar into
Vumi, an open-source messaging app providing young women in Sub-Saharan
Africa to save money in airtime credits.
3 Conclusion
While it is still early in the development and adoption lifecycle of both mobile
money and, to a greater extent, bitcoin and blockchain based remittance offerings,
the potential impact on the ability for nancial services to reach those without
access to traditional banking is clear. These technologies represent signicant cost
reductions, reduce the barriers of geography and enable new channels and pathways
for interoperability of services and product offerings. The growth and evolution of
these services will depend on a number of factors, including interest and adoption
by the markets they are addressing, regulatory enablement and investment, and
collaboration across both industry and policy markets, to help ensure accessibility,
ensure trust and security and reduce costs.
References
Abra: Abra announces public app launch and merchant API solution. Ratan Tata and American
Express join Series A funding round (2015) http://blog.goabra.com/2015/10/22/abra-
announces-public-app-launch-and-merchant-api-solution-ratan-tata-and-american-express-join-
series-a-funding-round/ Accessed 19 Nov 2015
Wikipedia (2015) Financial Inclusion: Wikipedia entry. https://en.wikipedia.org/wiki/Financial_
inclusion. Accessed 6 Dec 2015
How Non-banks are Boosting Financial Inclusion and Remittance 195
Author Biography
1 Introduction
We are currently witnessing the rise of a new form of distributed economy, which
emerges from the combination of digital communication infrastructures and the big
data revolution. Peer-to-peer decentralized economies and nance have the potential
to provide citizens with direct control over their activities, by removing intermedi-
ation layers and fostering inclusion. Blockchain is providing the technology to make
this happen in a secure and reliable way. Distributed systems are being constructed
around an egalitarian ethos according to which peers freely exchange goods and
information without the need of a central authority to establish trust, verify identity,
or enforce commitments. Yet, we are witnessing that many of such idealistic egal-
itarian forms of economic organization are changing their nature as they evolve. In
fact, these systems show a strong tendency to naturally evolve towards structures
where a small portion of nodes has a large influence over the whole system. This has
been for instance observed in the evolution of the mining pools in bitcoin, where the
system has evolved form a fairly egalitarian network of miners, in which individuals
were able to mine their coins at home, to highly specialized and concentrated
industrial-scale mining activities. A similar evolution has been observed in the world
wide web, which started from a distributed community of people and companies, and
evolved into a highly centralized system where. For instance, Facebook owns 1.49
billion active users proles (2015) and 99.9 % of web searches in US are run through
5 search engines only, with Google accounting for over 64 % (2015) of them. This
concentration is due to simple economic rules that demand greater efciency and
lower costs. This return-to-scale economic law introduces however new forms of
information asymmetry (Garcia 2014) and new kinds of risk related to the presence
of very large quantities of personal information held in a few places only. Within the
context of distributed systems that generate consensus with majority vote, such
tendency towards concentration can be very dangerous.
In this chapter we discuss the relation between the structure of communication
network and the functional properties of peer-to-peer systems. In particular, we
discuss the relation between level of equality between nodes in the network, and
efciency and scalability.
The chapter is structured as follows: we present in Sect. 2 a short introduction to
complex networks, and we discuss in Sect. 3 how the properties of information
spreading processes depend on the network topology. We then present in Sect. 4 an
application to bitcoin blockchain, and we study in particular how the occurrence of
blockchain forks is related with the properties of the underlying network. In Chap. 4
we present conclusions.
Networks are the most general way to represent systems made of several entities
characterized by pairwise interactions. A network is dened in terms of a set of
nodes f1, 2, . . . , Ng and a set of links fe1 , e2 , . . . , eM g, where each link connects a
pair of nodes. Nodes connected by a link are said to be neighbors, and the number
of neighbors of a node is the nodes degree. A convenient way of representing a
network is in terms of its adjacency matrix A, whose element Aij is 1 if node i is
connected to node j, and zero otherwise. Each node in a network can interact with
its neighbors, that are the nodes connected to it through links.
Scalability and Egalitarianism in Peer-to-Peer Networks 199
The Erds-Rnyi (ER) random network model was devised in the late fties, and it
represents the most popular benchmark model for networks featuring mild
heterogeneity. It consists of N nodes, and each of the NN 1 2 pairs of nodes in
the network have a xed probability p to be connected. Clearly, this formation
scheme creates, on average, a total number of pNN 1 2 links, with an average
degree of k = pN 1.
What about individual nodes? The probability that a given node i will be connected
to exactly k neighbors (in network jargon this is referred to as node i having degree
ki = k) is proportional to the probability of independently hitting k nodes (each with
probability p) and missing the other N k 1, which is a bimodal distribution:
N 1 k
Probki = k = p 1 pN k 1 . 1
k
can also show that the degree distribution of a large network is very well
approximated by a Poisson distribution
pNk pN
Pk = e . 2
k!
The above result means that both the average and the variance of the ER models
degree distribution are given by pN. All in all, these results justify the previous hint
at mild heterogeneity or, in other words, egalitarianism: in the ER model there are
no nodes that dominate the network by linking to a disproportionately large fraction
of peers, and the Poisson degree distribution (2) concentrates most of the proba-
bility within a limited set of degrees around the average.
Processes on ER networks can reach the entirety of the network by starting form
a single node in a number of steps that is proportional to the logarithm of the total
number of nodes N. This is called the small world effect. Intuitively, given that each
node has on average pN neighbors, one expects the number of nodes at a distance d
from a given node i to scale as pNd : on average, node i has pN neighbors, and so
do they and the nodes higher upstream from i. For sufciently large values of d, the
number of nodes found at distance d from i is a nite fraction of all nodes in the
network. From this consideration, one nds that the average distance between pairs
of nodes in an ER network scales as
log N log N
d . 3
logpN log k
Therefore a process evolving on the network form any given node will reach any
other node in average after a number d log N of steps.
Many real-life networks are not egalitarian, and are dominated by a small fraction of
hubs connected to a substantial fraction of nodes. In mathematical terms, this is best
described in terms of a power law, hence scale-free, distribution of the degrees, i.e.
Pk k , 4
the tail index > 0 is a very important parameter. Networks with smaller values of
have larger hubs and are less egalitarian as we shall see shortly.
Quite interestingly, modeling the topology of scale-free networks requires
describing their growth and evolution, in a way which is quite revealing about the
mechanisms leading to the emergence of dominant nodes. Such description is
provided by the Barabasi-Albert model of preferential attachment (Barabsi and
Albert 1999). Starting from a small group of nodes, the network is built by adding
nodes one at a time, and each newcomer connects to one of the already existing
Scalability and Egalitarianism in Peer-to-Peer Networks 201
nodes. In particular, the new node connects to a given node i with a degree-
dependent probability that reads
ki
ki = M , 5
j = 1 kj
where ki is node is degree, and M is the number of nodes present in the network.
The preferential attachment growth rule (5) gives a competitive advantage to nodes
that already have a high degree, in a rich-get-richer fashion. This mechanism indeed
gives rise (for large N) to a power law degree distribution (4), with a tail exponent
= 3. Exponents with values other than three can be achieved with general-
izations of the preferential attachment rule (5) (see, e.g., Paul 2000).
The egalitarianism, or lack thereof, of a network can be measured directly from its
degree sequence in terms of Gini coefcient, i.e. the most popular measure of
inequality in a population. Despite having been originally intended and still being
mostly used as a measure of wealth inequality, the Gini coefcient can be used to
assess how unevenly a generic quantity is distributed across a given population. Let
us then consider the sequence ki , i = 1, . . . , N, of degrees in a network. The Gini
index G of the sequence is dened as
i < j ki kj
G= . 6
N Ni= 1 ki
1 N k ki
i
T= log . 7
N log N i = 1 k k
In Fig. 1 we show the average behavior of the Gini and Theil indices computed
from networks with degree sequences distributed according to Eq. (4).
As Fig. 1 reveals, networks with extremely heavy tailed degree sequences
1.25 show very large Gini coefcient values G 0.65, comparable to those
202 F. Caccioli et al.
Fig. 1 Gini (blue circles) and Theil (purple squares) indices as a function of the tail exponent of
a power law distributed degree sequence (4). For each value of results are obtained by averaging
over 100 networks made of 104 nodes, with a xed average degree k = 8 (the value does not
affect the behavior of the Gini coefcient)
measured, e.g., for individual wealth distribution in those countries with the highest
observed wealth inequality levels. This reflects the strong centralization induced by
the degree distribution (5) for low values of , which generates a few hubs with ON
links, and leaves the vast majority of the nodes with a few connections only.
Increasing the tail exponent reduces centralization, which is very well captured by the
corresponding monotonic decrease of the Gini coefcient shown in Fig. 1. When the
tail exponent is large enough to ensure the convergence of the rst few moments (i.e.
3.5), the network degree distribution is de facto egalitarian, despite still being
power law, as the Gini coefcient is quite close to zero and well within ranges that are
naturally observed in systems characterized by mild heterogeneity. For instance an
Erds-Rnyi network with k = 8, as the one used in the example in Fig. 1, has a Gini
coefcient around 0.08. Similar considerations can be made from the behavior of the
Theil index, which also decays to values very close to zero for 3.5.
The presence of heavily connected hubs in scale-free networks improves the
communication between nodes by providing additional paths with respect to more
homogeneous topologies, e.g., ER networks. In fact, for 3, the average dis-
tance between nodes in scale-free networks scales logarithmically in N, as in (3),
but it is systematically smaller than that of ER networks when comparing systems
with the same average degree (see Albert and Barabsi 2002). When 2 < < 3
the distance between nodes scales as log log N and when 2 the distance
becomes a few steps only independently from the size of the network (Oxford
University Press 2010).
Facilitated communication between nodes comes at a price, as scale-free net-
works are much less resilient than their more egalitarian counterparts. Attacks
aimed at destroying hubs can have severely disruptive effects on the transport
properties. On the other hand, ER networks are more resilient to targeted attacks, as
no node (or group of nodes) is particularly central in the topology.
Scalability and Egalitarianism in Peer-to-Peer Networks 203
The topology of networks strongly affects their collective properties. For instance,
the threshold for the emergence of a giant component is very different in ER versus
scale-free networks. A network of N nodes has a giant component if the size S of its
largest connected component (a connected component is a set of nodes such that
any pair amongst them is connected by at least one path) is formed by an extensive
number of nodes, i.e. limN S N > 0. For uncorrelated networks (i.e. networks
with no correlations between degrees of neighboring nodes), it is possible to show
(2008) that a giant component is present if
k2
> 2, 8
k
where k and k 2 are the rst and second moments of the degree distribution.
From the above criterion, it follows that ER networks always have a giant com-
ponent if k > 1, whereas scale-free networks display a giant component if 3.
Similarly, it is possible to show that disease spreading processes on scale-free
networks always lead to an epidemic outbreak whenever 3, while on ER net-
works this does not happen if the rate of contagion is low enough (Pastor-Satorras
and Vespignani 2001).
In the following section, we consider a simple model of information spreading,
and we discuss how this process is affected by the structure of the network.
In the context of bitcoin (Nakamoto 2008), each node is a server that keeps a ledger
containing a record of all past transactions. Different ledgers are synchronized at
regular intervals by broadcasting a block created by one node. A block contains all
transaction that have been recorded by a node since the last block was broadcasted
and veried by all nodes in the system. When a new block, A, is found by a node,
the node will broadcast it to its neighbors, these in turn will broadcast it to their
neighbors, and so on. A conflict may arise if an alternative block B is independently
discovered by a node before the block A has reached all nodes in the system. Such a
conflict is called fork. Blockchain forks should be avoided because they effectively
amount to inconsistencies in the system. In the following, we consider the model
introduced in (Christian Decker and Roger Wattenhofer. Information propagation in
the bitcoin network. In Peer-to-Peer Computing (P2P) 2013) to show how the
structural properties of networks affect the propagation of information through the
network.
204 F. Caccioli et al.
We are interested in computing the probability that the initial block is broadcasted
to a fraction n* of nodes in the system before an alternative block is discovered.
Until no new blocks are discovered, the dynamics of the system is equivalent to that
of a Susceptible-Infected (SI) process (Alain Barrat et al. 2008). The SI model on an
Erds-Rnyi random network can be described in terms of the following rate
equation:
dnA t
= nA t1 nA t , 9
dt
nA 0et
nA t = . 10
1 + nA 0et 1
If nA 0 is the fraction of nodes that know the block A at time zero, we can
compute the time Tn* needed for block A to be broadcasted to a fraction
n* nA 0, 1 1 N of the system. This time can be computed by solving the
equation nA Tn* = n* , which gives
n* 1 nA 0
Tn* = 1 log . 11
nA 01 n*
From this equation we can compute the time needed for a block to be broad-
casted to 50 % of the nodes without alternative blocks being discovered. If we
assume the process to start from a single informed node (i.e. nA 0 = 1 N) we have
log N
T50 % . 12
From this we see that the time needed for information to be propagated in the
network increases logarithmically with the size of the network and it is inversely
proportional to = kcp0 l.1 Therefore, propagation speed can be increased by
increasing the average connectivity.
Equation (11) can be calibrated to obtain an estimate for the minimum time
Tmin 50 % needed for a block to reach 50 % in a realistic situation. A rough
estimate of Tmin 50 % can be given as follows: Let us consider N nodes that are
randomly placed on a spherical surface of radius R0 , the radius of the Earth. The
average distance between these nodes is R0 2. Since information cannot propagate
faster than light, we have that the minimum average time for a block to be prop-
agated between two nodes is R 2c and therefore the minimum time to reach 50 % of
0
R0 log N log N
Tmin 50 % = 0.033 s 13
2ck k
considering that in the blockchain there are N 6000 nodes, and k 10 we have
Tmin 50 % 30ms. From this result we note that in a network with k > log N the
average time to reach 50 % of the nodes can be faster than the time needed in
1
More in general, it is possible to show that the initial phases of the propagation process are
characterized by an exponential behavior for the fraction of informed nodes over time. This
0 k k
2
increases with a characteristic time = 1 ,with = cp
l k . Note that, for a scale-free network
with a tail exponent 2 < 3, if we consider the natural cut-off N 1 1 for the degree dis-
tribution (Sergey 2008), we nd that scales as k2 k N 1 1 for large values of N.
This would alter the dependence of T0.5 on N in Eq. (12), speeding up the propagation.
206 F. Caccioli et al.
average to reach all the neighbors of a given node. This is not a contradiction, and it
is due to the fact that the rst neighbors to be informed start broadcasting the
information to their neighbors, and, among these, those which receive the infor-
mation start broadcasting it to their neighbors, and so on.
From Eq. (11) we can also compute the probability that, given a discovering rate
, no new block is discovered before block A has been broadcasted to a fraction n*
of the system. In the continuous time limit we have that
R Tn*
N 1 nA tdt
qn* = 1 1 0 . 14
where
1 n*
f n , , nA 0 =
*
log , 16
nA 0
* N log1 17
n
=1 .
nA 0
Equations (15) and (16) can be used to characterize the performance of the network
as a function of all its structural parameters, such as its average degree and size. In
the following, we will measure the efciency of a network in terms of the proba-
bility q50 % that block A reaches 50 % of the network before block B is dis-
covered. Other metrics could be used, for instance the fork probability can be
computed from the above equations as the probability that the block A is broad-
casted to N 1 nodes before an alternative block is found.2
In Figs. 2 and 3 we show the behavior of q50 % as a function of the average
degree of the network and its size. In both cases there is very good agreement
between numerical simulations and analytical results from Eq. (17). Figure 2
highlights the role played by the networks density, as measured by the average
degree. In fact, an increase in density (at xed N) corresponds to an increase in the
average number of connections each node can exploit to broadcast a newly dis-
covered block, therefore speeding up the overall propagation process and ensuring a
fast convergence to consensus. On the other hand, very sparse networks are rather
2
Note here that the analytical equations are not dened for n* = 1.
Scalability and Egalitarianism in Peer-to-Peer Networks 207
0.9
0.8
0.7
0.6
q(50%)
0.5
0.4
0.3
0.2
0.1
0 2 4 6 8 10 12 14 16 18 20
k
In the previous section we have seen how properties such as the size of an
Erds-Rnyi network and its average degree affect the probability that a block
reaches the majority of the system before a conflict occurs. We now turn to the
208 F. Caccioli et al.
0.9
0.8
0.7
q(50%) 0.6
0.5
0.4
0.3
0.2
0.1
0
1 2 3 4
10 10 10 10
N
Fig. 3 Scalability with respect to network size: Probability of reaching 50 % of the network before
a conflict as a function of network size for a system with k = 7, = 10 3 , and nA 0 = 0.1.
Dots: results from numerical simulations. Solid line: analytical results from Eq. 17. As can be seen,
there is a very good agreement between analytical and numerical results, which show that network
expansion at xed densities, i.e. at xed average degree k, increasingly prevents the likelihood of
reaching consensus in the system
eciency ratio
block is discovered on 2.5
4 Conclusion
degree distribution. The latter implies the existence of hubs in the network, i.e.
nodes with signicantly more connections than the average degree, that are not
present in Erds-Rnyi networks. Therefore, as suggested by the Gini coefcient
associated with the degree distribution of these network ensembles, the two can be
considered as prototypical examples of egalitarian and non-egalitarian networks.
We have discussed that the difference in the degree distributions of these two
classes of networks has profound consequences on their behavior, for instance
regarding the emergence of a giant component of connected nodes, or the propa-
gation speed of signals in the network. The focus of this chapter was to understand
how the propagation of information on networks is affected by their topology. In
particular, we have considered a stylized model of block-propagation in the block-
chain. In the model, we assume that a new block has been discovered and has to be
propagated to the whole network before an alternative block is found, leading to a
conflict. Two competing processes take therefore place in the network. On one hand,
nodes that have been informed about the new block broadcast it to their neighbors, on
the other hand nodes that have not yet been informed can nd an alternative block.
We have provided an analytical formula for the probability that a conflict arises
in an Erds-Rnyi network, and we have characterized its dependence on the size of
the network and its average degree. By means of numerical simulations, we have
compared the performance of Erds-Rnyi and scale-free networks, and we have
shown that the latter perform better as the size of the network increases. This
nding suggests the existence of a trade-off between efciency and nodes equality.
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Author Biographies
Abstract In 16th century Europe, the revolution in printing technology and increasing
literacy in European cities created a positive shock to capital productivity. At the same
time, the spread of Protestantism in Northern Europe induced individuals to honour
contracts or risk exclusion from the Kingdom of God. Max Weber would argue that the
religious institution of Protestantism, by dissuading defection from agreements, had
allowed a new form of almost trustless exchange with strangers. Strict self-enforcing
religious rules restrained individuals from opportunistic behaviour thus lowering the
cost of monitoring and enforcing contracts. This led to increasing commerce and
economic growth. A better capitalized, but less strict Catholic Southern Europe was
unable to exert control and reduce contracting costs in the same way leading to less
exchange. We argue that peer to peer technologies, such as Bitcoin, Blockchains, smart
contracts, and peer-to-peer (P2P) legal platforms recall these historical evolutions. We
anticipate that these technologies will reduce the cost of contracting, specically with
regards to contract monitoring and enforcement. Trustless exchange without some of
the current intermediaries specializing in monitoring and enforcement technologies will
have a signicant impact on the nancial system and its institutional structure. Moving
beyond theory, this chapter discusses some of the major manifestations of technologies
capable to strongly decrease the cost of contracting, and it proposes a certain class of
models to explore how P2P technologies, and the concomitant reduction in transaction
costs they will cause, can be expected to affect nancial exchange.
J. Hazard
CommonAccord, Founder, Silicon Valley, San Francisco, USA
e-mail: james.g.hazard@gmail.com
O. Sclavounis ()
Oxford Internet Institute, Oxford, UK
e-mail: odysseas.sclavounis@gmail.com
H. Stieber
European Commission, Brussels, Belgium
e-mail: harald.stieber@ec.europa.eu
1 Introduction
It took some early adopters with enough faith to actually spend real money to purchase
some bitcoins to start to give it a value. Gavin Andresen, Chief Scientist at the Bitcoin
Foundation, during a keynote at Princeton University, 27 March 2014
In 16th century Europe two parallel developments were unfolding that would
help bring down the cost of contracting. The rst was the development of the
printing press and concomitant increases in literacy rates which increased the stock
of human capital. This decreased the cost of dening and monitoring property
rights. The second was the spread of various forms of Protestantism, instructing
adhering individuals to honor contractual obligations or risk exclusion from the
Kingdom of God. This had the effect of decreasing enforcement costs as agreements
became largely self-enforcing. Several centuries later, Weber argued that this
religious institution had allowed a new form of (almost) trustless exchange between
complete strangers and led to an era of international commerce creating substantial
wealth. Although both the technological and institutional developments were key to
reducing the cost of contracting, the development of a religious institution was
found to be decisive in promoting self-enforcing contracts linked to higher eco-
nomic growth rates. The decentralization of the function of monitoring and
enforcement of contracts led to greater capital productivity.
We argue that the transaction cost approach used to understand the changes in
behavior, contracting, and institutions in 1618th century Europe, can similarly be
applied to understanding current technological developments in P2P technologies.
P2P technologies such as Bitcoin and other Blockchain-enabled technologies have
changed the nature of contracting (denition, monitoring, and enforcement) espe-
cially as it relates to the enforcement function. Specically, we argue that these
technologies have the potential to drastically reduce and, more importantly,
restructure the transaction costs associated with contracting. This reduction and
restructuring of transaction costs allows for hub less contracting, signicantly
reducing counter-party risk. This chapter brings this insight to bear in understanding
the potential for change in the nancial system.
In thinking about the future of money and banking, we argue that transaction
costs could play a pivotal role with respect to new nancial technologies capacity
to dislocate or disrupt existing institutions and organizations such as cash, or uni-
versal banking. We do not argue that transaction costs are the only determining
factor. Rather we think that they are among those factors that we can actually
understand quite well ex ante, i.e. before the actual adoption of new technologies in
time and space will provide the ultimate answers.
At the start of our reflection it is necessary to analyze how successful current
nancial institutions have been in reducing transaction costs. For both money and
banks, the centralization of control seems to have played a crucial role. In the case of
money, at money has regularly led to inflation and abandon were it not for strong and
credible central control of the money supply (examples are the early Chinese
experiments with paper money or the U.S. free banking system with decentralized
creation of private moneys). Banking organizations, in their current form, have some
of the most rigid and hierarchical internal control structures in the sense of Coase
Are Transaction Costs Drivers of Financial Institutions? 215
(1937) within the universe of rms across all industry sectors. Centralization in nance
reflects the broader trend exhibited in history where centralized societies had com-
petitive advantages, notably advanced technology, in the accumulation of resources
and increase in population relative to less centralized societies (Diamond 1997).
Both cash and banks have been successful in reducing transactions costs from the
point of view of an individual transaction. Cash that is legal tender is guaranteed to
be accepted in payment of debts towards the state. This ensures the use value of
modern cash that is only a symbol or token and cannot be consumed (Kyotaki and
Wright 1989). Cash has reduced the need for parties to a transaction to spend time
and effort to inquire about the acceptability of a means of payment and store of value.
The case of banks is more complicated. On the one hand, banks are highly
sophisticated, internally diversied rms that carry out a myriad of nancial ser-
vices and transactions inside their business control structure (Diamond 1984). They
also interact with markets at many different points during this process. In the early
days of banking their positive effect on transactions costs was quite obvious as
communication and search was prohibitively expensive for an investor seeking
alternative business opportunities beyond her local area (of residence, or existing
economic activity). Banks were centralizing, matching, netting funding, and
investment already when Marco Polo returned from his excursion to China with
rst specimens of paper (at) money. They have done so ever since, and their
business model has not changed too much between the Italian banks of the 1400s
and commercial banks of the 1930s.
In the meantime, elements such as deposit insurance, lender of last resort funding
by central banks (i.e. the government just as in the case of deposit insurance), and
more recently the acknowledgement that some nancial institutions are too big to
fail have complicated the assessment (Philippon 2012; Bai et al. 2014). While the
marginal transaction may still benet from the capacity of modern banks to bundle
complicated nancial services for a client, it is less certain that the net benet for
society is positive under all circumstances. Indeed, Davies and Tracey (2014) nd
that once implicit subsidies are taken into account, economies of scale largely
disappear, i.e. a bigger balance sheet is no longer associated with lower costs of
nancial intermediation. As a starting point for our discussion we can take it for
granted that these implicit subsidies exist and are substantial.1
The development of FinTech and, more generally, P2P technologies intended to
simplify the nancial system, particularly Blockchain technology and associated smart
contracts, have the potential to reshape the costs of transacting in the nancial system.
Moreover, the development of a P2P legal contracting system, backed by a combi-
nation of Blockchain and smart contracts can dramatically change how all the stages of
1
It is noteworthy, while we do not discuss market structure here, that implicit subsidies lead to
falling average costs in a large portion of banks' production function. On those portions new
entrants will not only face the hurdle of getting new ways of doing things accepted, but they may
actually be unable to compete with the incumbent once the latter has eliminated, after some initial
successes and growing market share of the newcomers, inefciencies that may have accumulated
over the years (Roberts 2004).
216 J. Hazard et al.
contracting would happen, and can be expected to have the potential to disrupt the
current business model of some of the most protable and established nancial ser-
vices rms including in areas such as investment banking, clearing and settlement,
accounting, auditing, etc. Such a restructuring of transaction costs by P2P technolo-
gies would recall the effects that the printing press and self-enforcing Protestantism
had on trade and economic growth in 1618th century Europe. In the present chapter,
we try to explore the potential effect of P2P nancial technologies on the nancial
system using this historical precedent to structure our mostly theoretical discussion.
Our discussion proceeds as follows:
In the Sect. 1, we review the literature on institutions reducing transaction costs
as an input for economic development. As part of this review we consider an
original Weberian contribution to this literature: Blum and Dudley (2001) suggest
that a strong negative shock to the cost of contract enforcement in the Protestant
parts of Europe between 1500 and 1750 can explain the otherwise counterintuitive
acceleration of economic growth in Northern Europe compared to a better capi-
talized Southern Europe.
In Sect. 2, we discuss how Bitcoin and Blockchain-based transaction technolo-
gies, and more generally a legal system designed for the Internet, could alter trans-
action costs. It is true that many activities attached to nancial contracts have not seen
falling transactions costs, quite the contrary: legal advice, clearing and netting of
contracts, disclosure of contractual information, auditing of contracts, legal reporting
requirements are areas where costs have stayed steady despite signicant progress in
ICTs. Some authors go even further suggesting that transaction costs per unit output
of the nancial sector have actually increased (Philippon 2012), and that using the
nancial system has become more expensive over time even if overall informational
efciency has increased over the last half century (Bai et al. 2014).
In Sect. 3, we discuss how a stepwise agent-based modeling approach could be
developed based of a model by Kiyotaki and Wright (1989) where a medium of
exchange emerges endogenously and is held in equilibrium mostly due to its
favorable impact on transactions cost. The model is simple, elegant, and a good
point of departure for thinking about nancial institutions from a transaction cost
perspective. A modeling strategy for future agent-based models could then consist
in relaxing step-by-step the strong rationality assumptions in analytically solvable
models with two or three representative agents; more granular, bottom-up
agent-based models could be particularly helpful to better understand the impact
of P2P transaction technologies.
A couple of points should also be made with respect to the analytical strategy
that is used in this chapter and how we perceive the relative roles played by
nancial rms, trust and transaction costs. Financial rms revolve around and
depend on the concept of trust.2 Trust comes in many different forms: trust in the
persistence of the status quo, trust that contracts will be honored in different con-
texts with either the third party being a frequent partner in the exchange or a
2
Dufe (2010) argues that the failure mechanics in a banking crisis are all the more non-linear
since large banks will use way beyond any point of ex-post optimal behaviour all the flexibility
they have within their groups internal control structure to protect their reputational capital.
Are Transaction Costs Drivers of Financial Institutions? 217
2 Institutional Theory
Modern economic theory has often worked with models of a frictionless world with
zero transaction costs. In reality, transaction costs are substantial, and societies have
struggled to bring these down. Ultimately, various institutions emerged (including
nancial institutions) to bring down transaction costs with differing levels of ef-
ciency. Institutions are the rules of the game in a society or, more formally, are the
humanly devised constraints that shape human interaction and they have the effect
of structuring incentives in human exchange, whether political, social or eco-
nomic (North 1990: 3). By limiting the range of human behavior they reduce
uncertainty and therefore the cost of interaction, or transaction costs. How exactly
institutions reduce these costs is very important to the ultimate efciency of insti-
tutions in providing a framework to structured exchange. This requires a look at the
nature of transaction costs and how they relate to property rights.
Property rights are key to the functioning of an economic system as they represent
the rights individuals appropriate over their own labor and the goods and services
they possess (North 1990: 33). For exchange to take place individuals potentially
218 J. Hazard et al.
interested in the asset must possess full knowledge of its valued attributes (Barzel
1997: 7). However, due to the complexity of the environment and the cognitive
limitations of individuals, it is costly to ascertain and document the actual value of
the resource. In short, there are transaction costs associated with altering and
maintaining the integrity of property rights. Formally, transaction costs are dened
as the costs associated with the transfer, capture and protection of rights (Barzel
1997: 4). If the transaction costs are too high exchanges that otherwise would be
attractive may be forsaken (Barzel 1997: 5)
There are three dimensions to transaction costs: (1) denition and manufactur-
ing, (2) monitoring and (3) enforcement of contracts. These dimensions exhibit a
close analogy to the three stages in modern nancial banking intermediation as they
roughly correspond to (1) underwriting and manufacturing of nancial instruments,
(2) monitoring and screening credit and market risks to the value of contracts, and
(3) enforcement/execution of (nancial) contracts.
Dening property rights is the rst step to exchange and is necessary to know the
value of the different attributes lumped into the good or service (North 1990: 29).
Finding the value is itself a costly process which is never perfectly dened, because
of the diminishing returns to being fully informed. In the case of certain assets, for
example personal information, establishing the exact value of the asset is made
more difcult because of its intangible nature.
Monitoring the asset is important as an individual only owns the right to a
resource to the extent to which an owners decision about how a resources will be
used actually determines the use (Alchian and Demsetz 1973: 17). If some of the
valued attributes of the asset can be exploited by others, the owner has a decreased
incentive to invest further, thus decreasing the productive capacity of the asset.
The nal part of transaction costs is enforcement which is important as a
deterrent and a means of restitution if the rights of the owner are violated.
Enforcement is of crucial importance to the operation of a stable and functional
property rights system. In the absence of fair, transparent, rule-driven and consistent
enforcement, an individual would have little reason to think that the other party to
an exchange would not renege on their contract, thus discouraging exchange.
So institutions are efcient at providing a framework for cooperation and
coordination to the extent that they are able to reduce the transaction costs asso-
ciated with either dening, monitoring, or enforcing property rights.
the property rights of one party to an exchange.3 Institutions can be separated into
two categories according to the structure of their enforcement mechanism, informal
institutions that are not sanctioned by formal mechanisms (Kasper and Streit
1998: 106) and formal institutions whose sanctions are implemented in an orga-
nized manner by some member of society (Kasper and Streit 1998: 106).
Before going on to analyze how these institutions function, it is important to note
that the denition, monitoring and especially enforcement of property rights all
display the characteristics of a public good. Public goods, as argued are typically
underprovided because of the collective action problem (Olson 1965). This is
instructive in understanding how societies evolve from being governed primarily by
informal institutions before shifting to formal institutions.
3
Martin Shubik once compared the restrictiveness of bankruptcy rules to the gas throttle of the
economy, a less restrictive bankruptcy rule allows more risk taking, but will eventually hurt overall
trust in (asset) valuations; Diamond (1984) discusses the role of bankruptcy in conjunction with
debt contracts as an effective means to enforce contracts within the nancial sector, and Myers
(1977) has argued that a growing discomfort of management to face insolvency proceedings puts
an upper bound on the rms nancial leverage.
4
As Coase (1960) famously observed, in the complete absence of transaction costs, all benecial
exchanges would take place irrespective of the allocation of property rights; this famous link
between institutions and transaction costs has certainly been one of the reasons why Coases article
is by a very large margin the most cited economic theory paper of all times.
220 J. Hazard et al.
To reduce uncertainty in trustless exchange and to capture the gains from trade in a
world of impersonal exchange [institutions] must be accompanied by some kind of
third party enforcement (North 1990: 57) to overcome the collective action problem
and ultimately provide a productive incentive structure. Moreover, societies in-
creasing complexity. naturally raise[s] the rate of return to the formalization of
constraints (North 1990: 46) which becomes increasingly easier with technological
innovations like the printing press that lower the costs of formalization.5
Formal institutions are rules that govern behavior that are credible because they
are enforced by a third party agent. Third party agents are organizations dened as
groups of individuals bound by some common purpose to achieve objectives
(North 1990: 5), which are able to overcome the problems related to collective
action by better aligning the incentives of their members. Judicial systems have
been important institutions for societies evolving over time from informal institu-
tions based on culturally transmitted rules, to formal institutions where agreements
are formalized using contracts enforced by the state. Societies that manage to
formalize agreements via third-party enforced contracts at lower costs experience
stronger economic growth.
5
In ancient Persia, reflecting very high costs of documentation on durable storage media, famously
the only written formalized agreements were peace treaties and tax rules.
Are Transaction Costs Drivers of Financial Institutions? 221
However, technology can alter the structure of transaction costs thus altering the
dynamics of the institutional matrix. The printing press, for example, decreased the
cost of information search and propagation (Eisenstein 1979); so did the Internet, and
both technologies decreased the cost of mobilization and coordination of actors, as
well. Blockchain technologies could again alter the structures of transaction costs in a
signicant way along all three dimensions discussed above. This should be expected
to have implications on the complementary nature of formal and informal institutions
that are necessary to provide strong governance whilst reducing the potential for third
party risk. Blockchain institutions provide the formalization associated with formal
institutions, with the decentralization associated with informal institutions. Norths
typology does not entirely encompass this matrix of complementary characteristics
which suggests the formation of a new type of institutionsone which could have
signicant impact on governance and, potentially, economic growth.
222 J. Hazard et al.
Blum and Dudley (2001), combining approaches from endogenous growth and
evolutionary game theory, elaborate on Webers famous argument that the
[Protestant] Reformation created the decisive momentum for economic develop-
ment in northern Europe by modifying contractual relationships among believers
(Blum and Dudley 2001: 11). Catholics believed their sins could be forgiven by a
priest which was reflected in their economic behavior by a greater number of
defections in contracts, as the cost of defection was comparatively low. In contrast,
for members of Protestant sects, the hedonic cost of defection was high (Blum and
Dudley 2001: 2) because Protestants did not believe in the Catholic sacrament of
penance effectively meaning that the cost of defection was higher. This is a good
example of how internalized rules can govern behavior and reduce transaction costs.
Much in the same vein, the issue of establishing trust in a nancial transaction
without the intervention of a central authority is in the context of an option contract
described in Christopher Marlowes version of the Dr. Faustus theme. Writing in
England at the end of the 16th century, Marlowe obliges his Dr. Faustus to pay his
dues after 24 years of almost unlimited power and goes to hell instead of accepting
the offered sacrament of penance. Marlowes Faustus, in contrast with the German
original and the much later versions by Goethe and Mann, rules out any possibility
of deviation from the established contractual terms. Thanks to Faustus
self-monitoring behavior, the contract becomes quasi self-enforcing, thus reducing
the cost of enforcement to zero. Dr. Faustus is of the opinion that formal contractual
terms matter more than the social status of the contracting parties, a revolutionary
idea at the time. As a result, the formal contract can establish trust vis--vis any
(arbitrary) third party. Marlowes option contract is nothing else but a precursor of
the self-executing smart contract that will be discussed in the next section.
can become a hub for any activity where he/she is able to add value for other par-
ticipants, while maintaining low switching costs. It is useful to mention Git at this
point, an open source distributed version control system for the creation of software. It
permits full traceability of the history of materials, flexibility to modify, and privacy of
use. In its more social uses, notably as hosted by GitHub, it allows sophisticated
participants to nd resources, evaluate reputations and collaborate, reducing the cost
of collaboration. Git has been an important factor in reducing the average size and
capitalization of technology companies. We anticipate that P2P payments and a
systemic approach to legal text will have similar impacts on banking and nance.
3.1 Bitcoin
Even though Git allows nearly frictionless collaboration it does not solve the
double-payment problem. Nor does it provide a mechanism for rewarding main-
tenance of the infrastructure. Bitcoin emerged as a uniquely innovative single-
purpose system that solves these two issues.
Bitcoin is a system that allows users to securely store and verify information
publicly in a dynamic chain of data that is distributed amongst nodes in the net-
work. The network is secured through a competitive process called mining, where
miners are incentivized to process transactions in exchange for bitcoins, a digital
token whose value has increased considerably. The system is created so that once
data is embedded into the Blockchain it becomes immutable unless the actor that
wants to change the Blockchain controls a majority of the processing power of the
network making it resistant to change (the so-called 51 % attack remains Bit-
coins greatest vulnerability). Any change to how the Bitcoin protocol operates
must be made by consensus, meaning that a majority of miners must agree on the
changes being put forwards. The technical breakdown of how the Blockchain
functions and is secured is explained in Nakamoto (2008).
Bitcoin has limitations. First, it is a special purpose protocol. While it is suc-
cessfully used to create a non-falsiable record of a broad range of events, its
ability to automate more complex transacting is very limited. Second, it can process
only a very limited number of transactions, and involves a large time latency before
an event is conrmed as permanent. Third, the incentive system depends on wasting
electrical energy to solve cryptographic puzzles. This waste of electricity is inherent
to the system; the economic incentive is based on the cost of computing. Fourth,
while the identities of persons can be masked by encryption, the validity of the
transaction depends on the record being integrated into the public record which is
shared by all participants. A breach in the mask reveals a persons transaction
history. Fifth, a change to how the Bitcoin protocol operates must be made by
consensus, meaning that a majority of miners must agree on the changes being
proposed. Bitcoins resistance to change can be seen from the ongoing debate
relating to the scalability of the network. Despite most people being in agreement
over the need for certain changes in the system to allow it to grow, certain technical
and governance issues have prevented a consensus from emerging.
224 J. Hazard et al.
The most obvious use of bitcoins is as currency. Indeed, the white paper rst
describing the Bitcoin network that was published by the gure Satoshi Nakamoto
is entitled Bitcoin: A Peer-to-Peer Electronic Cash System suggesting that this
was the intended purpose for the system. Money is meant to have three key
characteristics (1) store of value (2) unit of account and (3) medium of exchange. In
this respect, the volatility of the price of bitcoin hinders its use as a medium of
exchange although there has been modest improvement in this respect. Instead,
bitcoins are used primarily for speculative purposes for the time being. A signicant
advantage of bitcoin as cash is that individuals control their own moneys. This is an
important attribute in many societies where banking institutions are not trusted.
However, some have argued that bitcoin as money is fundamentally flawed because
of the traceability of transactions. This reduces bitcoins fungibility, an attribute that
many deem key for the function of money. In terms of existing categories, bitcoin is
clearly not a at money, but it does not correspond fully to commodity money
either; this difculty of agreeing on its attributes continues to make its regulation
cumbersome and uneven across jurisdictions which in itself is a major obstacle for
its marketability.
3.2 Blockchain
At its most fundamental level, the Bitcoin Blockchain is a shared, auditable plat-
form with formalized and unbreakable rules about how transactions must take
place. This platform is open to all the parties, cannot be censored and most
importantly has no need for any intermediary or third party to process and validate
transactions. From a theoretical standpoint, this presents an important development.
The need for third parties to provide credible enforcement has been necessary for
the formalization of contracting, but the Blockchain can partly remove the need for
a third party for many types of transactions thus changing how institutions function.
In the past year a cleavage has emerged within the Cryptocurrency community
regarding the function and value of permissioned and permissionless Block-
chains (Swanson 2015). In the context of Bitcoin, the Blockchain is the distributed
public ledger that holds a record of all the transactions that have occurred in the
network and that is secured by the miners. The Blockchain is distinct from the
tokens, bitcoins, that are used to incentivize the miners to participate in processing
transactions. This distinction between Blockchains and bitcoins has led many to
identify the Blockchain as the object of value in the network. The Bitcoin Block-
chain is permissionless in that any entity can decide to participate in the network
either as a user or as a miner. However, permissioned Blockchains have also been
developed, sometimes called private Blockchains, where the creator of the Block-
chain in question designates who can participate in the network and in what capacity.
When thinking about how Bitcoin and Blockchains could impact the nancial
system, this dichotomy between permissioned and permissionless Blockchains is
important. Although there is disagreement amongst the two camps regarding the
Are Transaction Costs Drivers of Financial Institutions? 225
merits of the different types of Blockchains, many have argued that they serve
different purposes. The Bitcoin Blockchain offers a secure ledger due to the sig-
nicant hash power expended on mining but this also makes it costly to run and
inflexible. On the other hand, permissioned Blockchains are less secure but are less
costly to run, and can provide much more flexibility in their design. Permissioned
Blockchains have been developed by various companies and several large banks are
developing their own private Blockchain solutions. One notable development is the
creation of a consortium of banks and the private Blockchain company R3Cev, with
the aim of developing private Blockchain solutions for trading, settlement and
general automation of their business processes. Another is the creation of a con-
sortium under the Linux Foundation bringing together many major actors. Pay-
ments and transacting join Linux, Git and other codes, as part the open source
dynamic. It seems likely that many different types of Blockchains will exist, with
differing characteristics according to the needs of their designers and users.
As the ecosystem matures, the use cases of Blockchains continue to increase far
beyond mere nancial applications. Blockchain solutions are being developed in
many different industries for diverse reasons ranging from fraud protection, the
lowering of transaction costs and fees, or the reduction of counterparty risk.
Examples of these development can be seen in the insurance industry, digital
content management platforms, distributed le storage, real estate or digital identity
to name but a few.
that many currently missing markets can be completed using appropriate automa-
tion (and its inherent standardization).
The combined use of the Blockchain and smart contracts creates a platform
where individuals can exchange, manufacture and execute contracts with consid-
erable sophistication and with little cost. This innovation could turn the economics
of institutions on its head.6 Such a system would combine characteristics of formal
and informal institutions. The fact that automation can provide credible commit-
ments to parties makes them resemble informal institutions in that no third party
agent is required to provide the enforcement function. On the other hand, such
systems have attributes of formal institutions, notably the formalization of con-
tractingthe denition, monitoring and enforcement of contracts. In such systems,
third party enforcement becomes largely redundant as individuals could contract
with each other on a voluntary P2P basis, with an impartial and predictable
enforcement technology taking away counterparty risk.
While many kinds of high volume transacting have been automated, and the great
majority of transacting takes place without reading a legal document, not all have
been digitized. Most transactions are covered by documents such as terms of use,
terms of sale and privacy policies which are opaque to most users and invite
abuse; all this legal documentation continues to run on a paper standard, or
unstructured data, as opposed to a digital, or algorithmic standard that can not only
be processed by machines, but allows full automation and machine interoperability.
There are also important elds of transacting which take place by exchange of word
processed documents.
Legal documents continue to suffer from enormous inefciencies in their cre-
ation, review, management and enforcement. The costs of re-creating and reviewing
legal texts are well documented (Wickelgren 2011). These inefciencies are a major
reason why the cost of contracting has remained stubbornly high more than two
decades after the start of the ICT revolution.
Word processing in the legal industry has come to be dominated by a proprietary
software solution and a complex data model. Indeed, the data model is so complex
that it has proved difcult for competitors to create tools that are fully compatible.
The networked nature of legal transacting means that most actors stick with the
dominant solution. Of course, word processing is incompatible with peer-to-peer
automation. Various efforts are being made to format legal documents in ways that
are compatible. Worse, the word-processing data model has inhibited the kind of
6
Curiously, extrapolating this potential, P2P technologies could bring us in a not too distant future
arbitrarily close to the vision of complete markets spelled out by Arrow and Hahn (1971), the
criticism of which originally led to the emergence of the institutional economics literature.
A logical circle would thus be closed.
Are Transaction Costs Drivers of Financial Institutions? 227
iterative improvement and sharing of knowledge and work that has made open
source software drafting so successful.
Common Accord is a system that has adapted the tools and methods of open source
software development to legal documents, with the aim of codifying the documents
of law into a shared code of legal transacting. These resemble wikis, can be handled
in git, and can be forked or adapted for each jurisdiction, language or industry
thus making law modular.
Contracts are roughly described as the law of the parties. Legal systems
broadly respect contracts as party-dened law and will interpret them to prevail
over background law across a broad range of issues. The expansion of contract
boilerplate over the word-processing era reflects a kind of peer-based decentral-
ization of the law which creates considerable inefciency when done as
word-processing, but can contribute to decentralization in automated transacting.
There are advantages of an open source approach to the creation of legal texts
that can even exceed those for software. Legal text is not objective or deter-
ministic. It does not run on a machine. It depends on language, culture, insti-
tutions, the quality of advocacy and decision-makers. Codication greatly reduces
uncertainty by socializing text. It can come to have shared meaning through use,
interpretation, commentary and custom. In other words, a system like Common
Accord could prove a key step in making law a common good, which because of
the reduction in transaction costs associated with its open source production could
be more inclusive, thus gaining legitimacy.
This poses the question of the economic incentives to contribute. The search for
lower transaction driving through automation happening in banks and other
nancial rms could also drive the digitization and codication of legal docu-
mentation. In addition, there is a long tradition and important institutions that
already collaborate on legal codication: regulators writing rules, institutions
dedicated to codifying the law, lawyers collaborating on model (or master) docu-
ments, or companies codifying their own practices reflecting the fact that
automation and consistency advantages of a codied approach can be captured even
by a single rm. The use that follows is viral since a rm necessarily shares its
code with its partners (Triantis 2013). For nance, there are notable possibilities
for codifying new or existing products and for codifying compliance and reporting.
For the converging peer-to-peer transacting platform, Common Accord provides
a way for legal texts and the legal system to interface with smart contracts,
extending the reach of automated transacting to the full range of legal relationships.
In this way, peer to peer transacting platforms would not only be self-enforcing
through the use of smart contracts, but also legally valid and binding.
228 J. Hazard et al.
Bitcoin has demonstrated that a transaction system does not need a hub. Whatever its
future, it is a proof that solutions exist for hubless peer-based transaction systems with
the following characteristics, (1) reliable shared records, (2) anti-double-spending and
(3) incentives for maintaining the system.
P2P transacting platforms that incorporate Blockchains, smart contracts and
open source legal text management systems could create a paradigm where con-
tracting parties no longer need to pass through intermediaries to exchange.
Blockchains would offer a secure and non corruptible platform where smart con-
tracts could be automated and agreements entered upon. An open source legal text
management protocol would ensure that these transacting platforms operate within
the remit of applicable law. Such a paradigm would benet from signicantly lower
transaction costs then exist today in the nancial system.
The nancial system and the banking system will be affected at many levels.
Peer-based payments threaten many repeat revenues. Uniform interfaces and cod-
ied documents will reduce costs and transaction cycle times. They will also
facilitate new entrants and allow customers to be more mobile. The improved
record-keeping will make banks easier to audit. Handling text as source code will
enable collective sourcing of regulatory compliance materials. It will enable reg-
ulated entities to demand consistency from regulators via shared texts.
Could we formalize these discussions in a way that would allow hypothesis testing
or simulation of the impact of different technologies on societys transactions costs
problem? Money as a social institution has been very difcult to integrate into the
mainstream neo-classical model of (complete) competitive markets.7 In the
Arrow-Hahn (1971) formulation a good without consumption value in equilibrium
is priced at zero and its stock is forced to zero as well. The model of Kyotaki and
Wright (1989), hereafter KW, is a good starting point to think about such for-
malization. In their approach the institution of money emerges as the solution to a
problem of costly search for randomly matched parties to a mutually benecial
exchange. This places their model in the realm of anonymous exchange. One the
one hand, their model contains strong assumptions about enforceability of contracts
(rule of law) and the role of the state (and hierarchically organized authority and/or
trust more generally). On the other hand, their model is kept simple from an
analytical as well as topological point of view. As a result, it blurs the distinction
between transactions costs and network effects when discussing the benets of
7
See Shubik (2001) for an excellent, non-technical overview.
Are Transaction Costs Drivers of Financial Institutions? 229
8
A KW economy with privately provided at money is inexorably driven towards its only (Nash)
equilibrium in terms of individual trading strategies where no trade will take place because all
trading partners have at money in stock to be swapped against their preferred consumption good.
KW do not discuss this point, but we mention it here as a side remark and hint towards the
discussion on the limited money supply in the case of the digital currency bitcoin.
230 J. Hazard et al.
commodity money and at money. However, even in this simple setting, agents are
presumed to have substantial knowledge about the overall economy: KW presume
that the distribution of agents producing a particular good is known ex-ante, a stark
deviation from Adam Smiths anonymous market exchange with a spontaneous
organization of the division of labor the parameters of which are ignored by
individual participants. The stochastic process that matches agents (potential trading
partners) is also xed in the KW model, i.e. agents thereby know the structure of the
economy, they have rational expectations. On the other hand, while knowing quite
a lot, they are not given any choice in the presumed optimization (which is the
agents consumption technology) and thereby agents are trapped in the prisoners
dilemma once at money grows beyond the socially optimal amount.
Finally, and most interestingly for the discussion in this chapter, the storage
costs of the commodity moneys and of at money are given and not determined
endogenously. But what do the two types of money do in this setting after all?
Commodity money emerges endogenously; agents like to hold it because of its
marketability and its convenience (such as lower storage cost). The supply of
commodity money is limited by the amount of agents in the economy producing it.
It has no consumption value to its holder, but it has consumption value for other
agents in the economy. Now compare this to the centrally provided government at
money. Again, it has no consumption value for its holder, but nor does it have value
for any other agent. In the KW model its supply is xed, its marketability and
convenience properties are simply dened to be superior to commodity money.
To arrange our discussion and arrive at the same time at a visual representation of
our argument that transaction cost is a crucial concept in thinking about how
Internet-based technology can be expected to re-shape nancial intermediation, we
propose a simple, highly stylized modeling approach. It has a simple structure which
through iteration allows for genuine complexity to emerge. Similar modeling
approaches have been used in studying (1) the impact of additional information on
agents capacity to correctly forecast an external nancial signal, or (2) how different
forms of interaction between agents facing a similar learning/optimization problem
allow improvements of individual and group performance. Consequently, such
models have been termed learning to forecast models. They can typically be
implemented using agent-based computational modeling, or experimental economics.
Take the example of an agrarian economy where the individual agents are very
small. They produce a highly standardized product (such as corn), and because they
are small compared to the market the price established on the market is an external
signal. The production (cost) function is given as well (at least in the short run), and
hence the only variable that will determine if our agent can achieve an excess over
(production) costs is the deviation from the expected price at which she will be able
to sell her output. Early nancial technology will likely consist of a set of rules of
thumbs, or, if there are historical or seasonal patterns in the data, a slightly more
sophisticated time series model (calendars established over long periods of time and
used in agriculture are exactly that).
Are Transaction Costs Drivers of Financial Institutions? 231
Once agents start using different nancial technologies, they create track records
of how successful they were in guessing the external signal. The ensuing capacity to
consume can typically be observed by their peers. The variance that is now
observable allows for a further development of nancial technology. An agent can
exploit the variance of individual strategies and their associated consumption
streams and provide model-based forecasts of the external signal. If the
data-generating process that governs the magnitude and variance of the external
signal is sufciently stable, such a model-based analysis can outperform the rules of
thumb based on agents own experience or that of their immediate neighbors. The
agent using the statistical model may choose to provide a nancial service to other
agents but its capacity to do so is strictly limited by a number of cost factors.
The signal to be guessed could be quite frequent in this case, e.g. a broad index
of the U.S. equity market like the S&P 500. Switching costs are likely modest, but it
remains non-trivial to determine when it actually makes sense to switch the fore-
casting strategy. The example could also represent a commodity futures market
situation. Here, the cost of observing the evolution of prices takes center stage as
the market is already locking in the price of the commodity at a specic future date.
The farmer at the start of our example can now decide how much to produce and
substantially reduce (expected) costs.
corresponds to a simple swap of individual search costs with a fee for the centrally
produced forecast.
The more agents buy the rule that has produced the centrally visible stream of
consumption, the lower the fee s will become. The central agent has will not go out
of business as long as at least the initial number agents/neighbors is willing to
acquire the forecast model which denes the xed cost to be nanced which can be
thought of as the hosting costs of a website. The model enters the next round: any
agent (i) rst decides (automatically) based on the consumption threshold level and
based on the last outcome to either enter into a search or not. If the answer is no, the
model in store is used to compute the forecast and the agent will receive the resulting
stream of consumption (and may or may not make a payment to a central agent). If
the answer is yes, the agents will look to their neighbors consumption history as
well as to the Internet to see if any central agents are around. If a neighbor is more
successful, agents will enter into a conversation and spend the effort and copy the
heuristics. If none of the neighbors is more successful, agents will compare the
consumption histories of the central agents (e.g. via their websites or their con-
sumption histories recorded elsewhere). A rst selection will be to only keep the
central agents that show higher consumption. Among the latter the agents will
engage into a contractual relationship where they pay a fee that is strictly smaller
than the effort to engage with neighbors and use the centrally provided forecast.
After this decision consumption is computed and the model goes into the next round.
This rst variant of the model could be analyzed in terms of the pattern it
produces depending on the cost parameters used. There is the cost of local search;
then there is the xed cost of hosting the website of the central agent.
Another output of such a model will be a measure how social welfare compares
to individual loss due to lock-in. Social welfare can be expected to increase with the
emergence of central agents due to the benecial effects on costs. Similar to at
money in the KW model, these benets can outweigh some of the losses at the level
of individual agents as the latter stick to the centrally provided forecast too long, i.e.
the local agents switch too late.
A rst evolution of the model could lift the restriction on memory of agents.
Thanks to technology, agents can observe their entire history of consumption
(marginal storage costs are zero) and they can test alternative heuristics on the entire
history of the external signal. Longer memory can be expected to reduce volatility.
As a result, agents will look less frequently for alternative heuristics. The ex-ante
effect on social welfare and lock-in appears to be ambiguous. While longer memory
should, ceteris paribus, lead to a slower adoption of alternative heuristics (recall that
all agents start using own heuristics that are costless) including the emergence of
central agents and the use of their forecasts, once a large number of agents have
bought into centrally provided forecasts the lock-in would be more permanent as
well. In any case, lower storage costs make society more (model) conservative.
We think this model corresponds well to the rst generation of the Internet with
storage costs falling over time. What agents pay in the aggregate for local search
can be expected to fall quite dramatically over time as histories get longer and local
234 J. Hazard et al.
search will provide almost all observations for the same cost. As a consequence,
agents will spend less on strategies that look promising on the basis of a short
memory test, but do not produce sufciently different results over the longer term.
(In the aggregate convergence on the true data generating process should be faster
with longer memory.)
A third variant of the model could then relax the technological constraint on the
cost side that distinguishes the central agent from the local agent. In terms of our cost
parameters this corresponds to a situation where both the cost of local search and the
(xed) cost of setting up the central agents ofce become very small and thus very
similar in size (amazon web services base packages may differ insignicantly from
costs of an individual local search in many cases). Lock-in should be much lower in
this situation which is clearly welfare enhancing. Agents will switch strategy more
easily which is welfare enhancing; given the small difference between costs of local
and global searches only a few (very large?) central agents can be expected to prevail
over longer stretches producing a limited amount of lock-in.
Finally, in a fourth variant, one could relax the restriction on local agents in
terms of access to other agents histories and heuristics. This would then correspond
to an open data (histories), open source (heuristics), P2P nance setting. This could
correspond to the transition from the rst Internet to the relational web. Each agent
could carry out the computation that corresponds to the knowledge of a central
agent having all other agents in the economy as clients. However, there is no
lock-in. It is another corner solution to our model producing the maximum amount
of welfare in our economy. Note, however, that there is not credit in this model, no
room for a nancial cycle, asset price bubbles, etc.
How general the situation of the described agent is becoming clearer once we
reconsider the balance sheet of a typical household. The household is required to
correctly understand a number of external signals and trends such as the evolution of
life expectancy, health risks, how the market value of his educational status evolves;
moreover, a number of macroeconomic variables and trends need to monitored:
economic growth, employment and investment opportunities, and inflation. How-
ever, for our reflection it is sufcient to illustrate that households face a very complex
monitoring problem and that monitoring costs are high (Diamond 1984). On the
other hand, these monitoring costs are subject to important economies of scale and
scope. These economies form the basis of a highly diversied nancial services
industry which has banks (monetary nancial institutions) at its center.
What then if, one by one, these monitoring costs could be reduced to close to
zero? The advent of big data, advanced data analytics, abundant open data, cheap
computing power, the mobile Internet, Blockchain technologies, smart contracts
and open source management of legal text; all these factors point to the potential of
a signicant reduction in monitoring and enforcement costs. A revolution similar to
the one described by Marlowe and Weber in the context of Protestant cultures
impact on transaction costs could be under way in this case.
Are Transaction Costs Drivers of Financial Institutions? 235
5 Conclusion
This chapters theoretical discussion explored the argument that the formal insti-
tutions needed for complex contracting need third party enforcement to be credible.
The peer to peer technologies described subsequently show how monitoring and
enforcement of contracts in the context of nancial transactions could become
signicantly less costly. A peer to peer transaction system that leverages the
security of Blockchains, with the automation and self-enforcement of smart con-
tracts with the concomitant legal text interfacing with the system, would dramati-
cally lower the costs of monitoring and enforcement in nancial systems. Clearing
houses, stock markets, equity funding, insurance could all be to a certain extent
automated and operate in a peer to peer manner rather then with a central admin-
istrator. This would likely upend the nancial system as it functions today.
Financial services companies will have to reconsider their value propositions on a
fundamental level as their role as intermediaries is made redundant.
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Author Biographies
Disclaimer for Harald Stieber The views expressed in thischapter are my own and may not,
under any circumstances, beinterpreted as stating an ofcial position of the European Commission.
Understanding Modern Banking Ledgers
Through Blockchain Technologies: Future
of Transaction Processing and Smart
Contracts on the Internet of Money
Keywords Blockchain Smart contracts Banking ledgers Data integrity
Data security
Exchange clearing
G.W. Peters ()
Department of Statistical Science, University College London, London, UK
e-mail: garethpeters78@gmail.com
G.W. Peters
Department of Statistical Science, Oxford Mann Institute, Oxford University, Oxford, UK
G.W. Peters E. Panayi
Systemic Risk Center, London School of Economics, London, UK
e-mail: stathi.panayi@gmail.com
E. Panayi
Department of Computer Science, UCL, London, UK
1 Introduction
Throughout this book, the reader has observed how blockchain technologies have
enabled the creation of crypto-currencies, and their rise has been documented
widely documented.1 The use of these currencies has prompted wide discussions on
the merits (or lack thereof) of decentralisation, disintermediation,anonymity and
censorship resistance in this setting, aspects which we discuss in this chapter also.
One cannot, however, dispute their potential to disrupt areas such as the global
remittance industry, by facilitating near-instantaneous global remittance with very
low transaction fees.
In more recent times, blockchain applications have appeared to go far beyond
their rst application domains in virtual currencies, for instance they are now
important in elds such as domain registration, crowdfunding, prediction markets
and even gambling. Second generation blockchain technologies enable not only the
execution of simple transactions, but the carrying out of computation on a network,
where e.g. payments become conditional on the state of some internal or external
variables (much the same way as nancial derivatives have a payout that is a
function of an underlying nancial instrument). This is the basis for smart contract
technologies, which we shall see can be important building blocks for these new
application areas. As a consequence of these second generation technologies, a
number of developments in this eld have begun to appear which include third
party data ledgers (Devanbu et al. 2001), e-contracts/smart contracts and virtual
contracts (Buterin 2014b; Kosba et al. 2015; Swan 2015), e-assets or remote asset
title transfers (Halevi et al. 2011) and further applications, discussed in Czepluch
et al. (2015).
One can imagine that different applications require different blockchain struc-
tures or architectures, and our rst contribution is in describing the differences
(from both a theoretic and practical standpoint) between permissionless and per-
missioned blockchains in this context. As blockchains require nodes to act as
veriers for the network, permissionless blockchains allow for anyone to join as a
verier, while prior authorisation from a centralised authority or consortium is
required in a permissioned blockchain. These blockchain types therefore require
different approaches to achieving consensus, as well as incentivising verication
activity on the network. In this context, one of our contributions in discussing these
frameworks focuses on the signicance of data integrity protocols, which can be
incorporated with blockchain technologies to achieve different levels of permis-
sioning, data integrity and data security.
While the potential for smart contracts to operate on these blockchains is very
promising, it is not without its pitfalls. Notably, current blockchain structures,
1
Nakamoto (2008) introduced the rst decentralised crypto-currency called Bitcoin, and related
technology startups have already attracted more than $1 billion in funding. The currency has been
the subject of academic considerations in topics such as privacy (Reid and Harrigan 2013), security
Barber et al. (2012), regulation (Peters et al. 2014) and monetary policy (Peters et al. 2015).
Understanding Modern Banking Ledgers Through Blockchain 241
requiring the repetition of computation on all network nodes, will rapidly run into
scalability issues, and this will require consideration before mass adoption becomes
possible. Blockchain technology has the potential to revolutionize contract law and
processing via self-enforcing digital contracts, whose execution does not require
any human intervention. However, where automated smart contracts have a
real-world counterpart, one has to understand both the legal and technical rami-
cations, particularly in the case of disagreements between the two, which is what we
aim to analyze.
In addition to these innovations in nancial transactions and contract law, it is
also recognised that such technologies can contribute signicantly to other aspects
of the nancial industry, e.g. related to regulation and taxation. Importantly for this
chapter, we envisage a banking and insurance environment in which blockhain
technologies are utilised in banking ledger records and other banking and insurance
records, such as loss databases and claims record databases. In this regard, we will
discuss aspects that must be considered when developing such technologies for
banking applications, notably loss reporting, recording and provisioning in order to
be consistent with modern regulations such as Basel III/IV, Solvency II and IFRS 9.
We also discuss how blockchain technology offers the potential for the devel-
opment of new approaches to governance systems with the ability to decentralize
many processes and thereby provide perhaps more democratic inclusive
decision-making processes. Indeed there are some attempts to develop second
generation blockchain architectures that are specically designed for board rooms
and automated structuring of governance frameworks for corporations. It is
important to note what we refer to as decentralization in this context, see for
instance the denition provided in Benkler (2006).
Decentralization describes conditions under which the actions of many agents cohere and
are effective despite the fact that they do not rely on reducing the number of people whose
will counts to direct effective action.
The remainder of the chapter is structured as follows: Sect. 2 details the dif-
ferences between the permissionless and permissioned blockchain types, it
describes the advantages blockchains hold over databases and introduces smart
contracts and their possible applications. Section 3 discusses existing notions of
security, condentiality, availability and integrity and how it applies to enterprise
data, giving examples of blockchain structures which can preserve these features.
Section 4 proposes usecases for blockchain technology for government cash
management through administering Treasury Single Accounts, as well as improving
on the commercial bank ledger structures. Section 5 describes the current state of
the clearing and settlement system and proposes blockchain approaches to reduce
the inefciencies. In Sect. 7 some conclusions are drawn.
2
In the Byzantine Generals' problem, introduced by Lamport et al. (1982), a group of Byzantine
Generals are camped around an enemy city in different locations. If they all attack simultaneously,
then they have superior repower to their enemy. The problem is that they need to agree a common
battle plan, so that they attack at the same time, with the additional complication that there may be
a traitor amongst their ranks.
Understanding Modern Banking Ledgers Through Blockchain 243
blockchain are valid and never recorded more than once, enabling people to
coordinate individual transactions in a decentralized manner without the need to
rely on a trusted authority to verify and clear all transactions.
Just like many other technologies for the internet, blockchains rely on public key
cryptography to protect users from having unauthorised persons take control of
their accounts. The private and public key pairs enable people to encrypt infor-
mation to transmit to each other, where the receiving party would then be able to
determine whether the message actually originated from the right person, and
whether it had been tampered with. This is critical when one needs to communicate
to a network that a transaction between two parties has been agreed. In addition, the
presence of an ability to identify the integrity of the data is also critical for appli-
cations we will consider, as discussed further below. We dont enter into a detailed
discussion here on the basic details of crytographic properties of blockchain and its
construction via hash functions as the reader can nd this detail in other chapters in
this book. We note that detailed discussions on the different types of hash function
may be found in the overview of Carter and Wegman (1977).
We note that within the blockchain structure there is also included information
related to the digital time stamp, which records the temporal existence of a par-
ticular blockchain ledger item at a given instance in time. It could be utilised to
symbolise that a contract between two agents is initiated or completed, that
transactions of some form materialized or that payments/e-property were transferred
ownership etc. Typically a digital time stamp also contains information relating to
the hash created from the activity of securing the particular data/information entered
into the ledger. This allows time stamping to occur with an element of privacy for
the data being secured and entered on the blockchain ledger. In addition, just
recording the hash is a more parsimonious representation of the information being
secured or recorded.
There exist parties such as Time-Stamping Authorities (TSA) that can provide a
trusted third party arrangement to provide a secure and safe cold or secured live
storage of information relating to the blockchain ledger recording. This digital
notary signs with a private key for this data to be recorded and the time when this
data was communicated to the authority. Then the signature address would be sent
back to the original owner of the data. This simplied form is often performed in
blockchain technologies using more advanced approaches such as a TSA collecting
and securing in encrypted storage several agents data sets from within a xed time
period, then taking all data from this period and providing a time stamp, and
hashing all this data together via a method such as a Merkle tree, see (Merkle 1979,
1980; Devanbu et al. 2001). Then the resulting hash, for instance the root of the
Merkle tree would be hashed together with the nal hash of the previous time
period and then published in the blockchain ledger.
244 G.W. Peters and E. Panayi
There are various (often conflicting) categorisations of blockchain types, and for the
purposes of this chapter we will focus on the different types of blockchain
according to whether authorisation is required for network nodes which act as
veriers, and whether access to the blockchain data itself is public or private.3 For
the rst categorisation we have:
Permissionless blockchains, where anyone can participate in the verication
process, i.e. no prior authorisation is required and a user can contribute his/her
computational power, usually in return for a monetary reward.
Permissioned blockchains, where verication nodes are preselected by a central
authority or consortium.
For the second categorisation we have:
Public blockchains, where anyone can read and submit transactions to the
blockchain.
Private blockchains, where this permission is restricted to users within an
organisation or group of organisations.
In reality, most permissionless blockchains feature public access, while the
intention of most permissioned blockchains is to restrict data access to the company
or consortium of companies that operate the blockchain. For this reason, we col-
lapse the categorisation into two types, permissioned and permissionless block-
chains, and we elaborate the distinction between them in the following section.
3
https://blog.ethereum.org/2015/08/07/on-public-and-private-blockchains/.
Understanding Modern Banking Ledgers Through Blockchain 245
from the reference point they wished to alter to the present time. In addition, they
would have to achieve this at a faster pace than the current legitimate network
processing of new blockchain entries. Proof-of-work concepts can come in many
forms, for instance they may rely on solutions to a computationally hard problem, a
memory intensive problem or a problem that may require user interventions. To be
practically useful for a blockchain technology, such problems must be computational
challenging to solve, but efcient to verify a solution once obtained. Although these
algorithms are vital in ensuring the security of the network, they are also very costly
in terms of computation, and thus electricity usage also.
A permissionless blockchain is advantageous in that it can Swanson (2015) both
accommodate anonymous or pseudonymous actors and protect against a Sybil (i.e.
identity-forging) attack Douceur (2002). On the other hand, the incentive mecha-
nism has to be carefully developed in order to ensure that veriers are incentivised to
participate. In Bitcoin, for example, veriers receive an amount for verifying each
transaction, as well as for publishing a block of transactions. However, the latter is 2
orders of magnitude higher than the former. Since the incentive for publishing
transactions of blocks decreases according to a predened schedule, means that
veriers will at some point need to increase the amount they will require to process
individual transactions, which makes it more costly to transact in Bitcoin.
Besides Bitcoin, examples of permissionless blockchains include Ethereum,4 the
platform that is intended to provide access to smart contracts on the blockchain, as
well as offer blockchain as a service.
This is not the only possible conguration of a blockchain, however, and the
discussion is increasingly moving towards private, permissioned blockchains for
specic usecases. Permissioned blockchains have a set of trusted parties to carry out
verication, and additional veriers can be added with the agreement of the current
members or a central authority. Such a conguration is more similar to a traditional
nance setting, which operates a Know Your Business (KYB) or Know Your Client
(KYC) procedure to whitelist users that are allowed to undertake operations in a
particular space. Swanson (2015) nds that permissionless and permissioned
blockchains are fundamentally different in both their operation and the range of
activities that they enable, some of which we review here.
Permissioned blockchains are intended to be purpose-built, and can thus be
created to maintain compatibility with existing applications (nancial or otherwise).
They can be fully private (i.e. where write permissions are kept within an organi-
sation), or consortium blockchains (where the consensus process is controlled by a
pre-selected set of nodes).5 Because the actors on the network are named, the
4
https://www.ethereum.org.
5
https://blog.ethereum.org/2015/08/07/on-public-and-private-blockchains/.
246 G.W. Peters and E. Panayi
intention is that they are also legally accountable for their activity. In terms of the
transactions these blockchains handle, it will be predominantly off-chain assets
(such as digital representations of securities, at currencies and titles of ownership),
rather than on-chain assets, such as virtual currency tokens Swanson (2015).
An advantage of a permissioned blockchain is scalability. In a permissionless
blockchain, the data is stored on every computer in the network, and all nodes
verify all transactions. It is obvious that once the number of transactions increases
substantially, the users that are able to perform this type of processing and veri-
cation will decrease, leading to more centralisation. In a permissioned blockchain,
only a smaller number of preselected participants will need to operate, and if these
come from large institutions they will be able to scale their computing power in line
with the increase in number of transactions.
However, because of the smaller number of participants, it is much easier for a
group of users to collaborate and alter the rules, or revert transactions. In addition, it
is easy for them to reject transactions and in this sense it is not censorship resistant
as a permissionless blockchain would be. Examples of permissioned blockchains
include Eris,6 Hyperledger,7 Ripple8 and others.
6
https://erisindustries.com/.
7
http://hyperledger.com/.
8
https://ripple.com/.
Understanding Modern Banking Ledgers Through Blockchain 247
In terms of applications of blockchain technology, one could argue that we are still
in the exploration phase. It is prudent to be cautious about claims that this tech-
nology, particularly in its permissioned blockchain form could disrupt elds as
diverse as banking, insurance, accounting etc. In particular, it would be useful to
explore exactly what advantages blockchains have compared to well-understood
transaction recording technologies, such as databases.
9
https://erisindustries.com/components/erislegal/.
10
http://www.commonaccord.org/.
11
http://p2pfoundation.net/Legal_Framework_For_Crypto-Ledger_Transactions.
248 G.W. Peters and E. Panayi
To start with, we provide a short description about the types and capabilities of
modern databases. Depending on the nature of the data one is storing, there are ve
genres of databases (Redmond and Wilson 2012):
Relational databases, such as SQL and variants, which are based on set theory
and implemented as two-dimensional tables;
Key-value stores, which store pairs of keys and values for fast retrieval;
Columnar databases, which store data in columns, and can have more efcient
representations of sparse tables compared to relational databases;
Document databases;
Graph databases, which model data as nodes and relationships.
Databases can be centralised (residing at a single site) or distributed over many
sites and connected by a computer network. We will focus on the latter, given the
closer proximity to the blockchain concept. The objective of a distributed database
is to partition larger information retrieval and processing problems into smaller
ones, in order to be able to solve them more efciently. In such databases, a user
does not, as a general rule, need to be aware of the database network topology or the
distribution of data across the different nodes. It should also be noted that in a
distributed database, the connected nodes need not be homogeneous, in terms of the
data that they store (Elmasri and Navathe 2014).
Because of the design of these databases and the replication of data across
different nodes, such a database has several advantages (Elmasri and Navathe 2014,
p. 882):
Better reliability and availability, where localised faults do not make the system
unavailable;
Improved performance/throughput;
Easier expansion.
In every distributed database, however, there is the issue of how modications to
the databases are propagated to the various nodes that should hold that data. The
traditional approach is a master-slave relationship, where updates to a master
database are then propagated to the various slaves. However, this means that the
master database can become a bottleneck for performance. In multi-master repli-
cation12 modications can be made to any copy of the data, and then propagated to
the others. There is a problem in this case also, when two copies of the data get
modied by different write commands simultaneously.
A blockchain could be seen as a new type of distributed database which can help
prevent such conflicts. In the same way that the Bitcoin network will reject a trans-
action where the Bitcoin balance to be transferred has already been spent, a
blockchain can extend the operation of distributed databases by rejecting transactions
which, e.g. delete a row that has already been deleted by a previous transaction (where
a modication is a deletion, followed by the creation of a new row).
12
http://www.multichain.com/blog/2015/07/bitcoin-vs-blockchain-debate/.
Understanding Modern Banking Ledgers Through Blockchain 249
Companies and organizations use the data they collect to personalize services,
optimize the corporate decision making process, predict future trends and more. If
one is to consider how to incorporate such records onto a blockchain there are
fundamental issues to be considered. Within banking and nancial services, for
example, they must rst of all adhere to different adopted best practices with regard
to data condentiality, availability and integrity. These concepts are related but
distinct, and vital for data security within an organisation. We briefly discuss the
rst two, before exploring the latter in depth in the context of the blockchain.
Condentiality involves the protection of data from unauthorised disclosure,
either by direct retrieval or by indirect logical inference. Condentiality consider-
ations can also involve the possibility that information may be disclosed by legit-
imate users acting as an information channel, passing secret information to
unauthorised users. Within a blockchain, the choice of a permissioned or permis-
sionless structure will dene whether data will be made available to the public, or
only within an organisation. Permissionless blockchains also enable carrying out
transactions without the disclosure of private information. Because the operation of
these blockchains rests on public key cryptography, securing users private keys is
critical, and indeed, this is one of the main source of operational risks in this area
(Peters et al. 2014).
Ensuring high availability means that data is accessible to authorised users.
Availability is very closely related to integrity because service denial may cause or
be caused by integrity violations. In blockchains, because data is replicated across
many different nodes, availability should always be high. The catastrophic failure of
a number of nodes should not cause any availability problems, although the net-
work will experience a reduction in security proportional to the computational
power of the missing nodes.
250 G.W. Peters and E. Panayi
Maintaining the integrity of data entails its protection from invalid modication,
insertion or deletion, thereby preserving the accuracy, consistency and validity of
data over its life cycle. Ensuring this integrity is important for the recoverability and
searchability, as well as the traceability and connectivity of nancial data records.
This process usually requires a set of constraints or rules that dene the correct
states of a database or data set, and maintain correctness under operation. While the
wider area of data security is often discussed in the context of cryptography con-
siderations around blockchain technology, data integrity preservation in a block-
chain structure has received comparatively little attention.
When we discuss data integrity in this section we are referring to the accuracy
and consistency or validity of data over its life cycle. In general, when discussing
data integrity it may take one of two meanings, either referring to a state of the data
or a to a process performed relating to the data. Data integrity in the context of a
state specication denes a data set that is both valid and accurate, whereas data
integrity as a process, describes protocols adopted to preserve validity and accuracy
of a data set.
In this section we argue that blockchain technologies can be structured to be
consistent with best practices currently adopted with regard to data integrity, and
indeed such considerations are only just starting to nd their way into second
generation blockchain technologies, with projects such as Enigma in MIT, see
Zyskind et al. (2015). The rst aspect of data integrity we consider relates to the
state of the data. In this context the state specication of the blockchain data records
would be dened such that the data is valid and accurate or that the smart contracts
operating on the blockchain are valid and accurate.
The second aspect of data integrity relates to the transformation processes, which
in this case would be operating on either data recorded or linked to the blockchain
or to smart contracts operating on data on the blockchain. As with all applications in
which data is a key ingredient, the data in its raw form is often not directly utilised
for decision making and interpretation within the application. It must rst undergo a
variety of modications and be put through different internal processes to transform
the raw data forms to more usable formats that are practical for identifying rela-
tionships and facilitating informed decisions. Data integrity is then critical in
ensuring that these transformations preserve the validity of the data set. Modern
enterprises reliant on data, such as nancial institutions, need to have condence in
the validity of their data, therefore they need to ensure both the provenance of the
data and the preservation of integrity through transformation. Such transformations
may also be included as part of smart contract structures in second generation
blockchain applications.
Another way of conceptualising data integrity notions is to consider its function
in preventing data modication by unauthorized parties, and maintaining internal
and external consistency in the data set. If data is compromised then its utility to
business practice and its informative nature may rapidly diminish. There are
Understanding Modern Banking Ledgers Through Blockchain 251
numerous places where such corruptions of data integrity may arise, for instance
during replication or transfer or the execution of a smart contract that operates on a
dataset to make contractual decisions.
One can minimise such issues through the adoption of error checking methods.
In a blockchain, these methods are inbuilt. The hash of each block of transactions is
linked to the next, thus forming a chain. Transactions that are present in these
blocks cannot be altered, unless one generates all blocks from that point onwards,
which requires immense computational power. However, error checking for second
generation blockchain structures, where smart contracts contain computer code, will
be more involved.
Causes of corruption of data integrity include human error, which may or may
not be intentional, code errors, viruses/malware, hacking, and other cyber threats,
compromised hardware, such as a device or disk crash and the physical compromise
to devices. From this list we see that some of these issues with preservation of data
integrity rely on data security, whilst others are non-resolved when it comes to
security solutions. We can easily see that data integrity and data security are related,
and that data security refers to the protection of data against unauthorized access or
corruption and is necessary to ensure data integrity. Hence, we see that data security
is one of several measures which can be employed to maintain data integrity, as
unauthorized access to sensitive data can lead to corruption or modication of
records and data loss.
In addition to security considerations, it is also clear that to achieve data integrity
there is a strong case for data backup/redundancy/duplication. Practically, there are
adopted best practices that remove the other data integrity concerns, such as input
validation to preclude the entering of invalid data, error detection/data validation to
identify errors in data transmission, and security measures such as data loss pre-
vention, access control, data encryption.
We have already discussed the advantages that distributed databases bring in
resolving a number of these issues. A blockchain additionally brings cryptographic
security, a solution to the multi-master replication problem, and facilitates more
complex transactions through enabling smart contracts.
Ge et al. (2004) note the following aspects of integrity for data stored in data-
bases which we believe would similarly apply to blockchain structures and archi-
tectures, as well as to perhaps different smart contract structures that are designed to
operate on blockchain backbone networks:
Integrity and consistency should involve semantic integrity constraints which
are rules dening the correct states of the system during operation. Such
semantic constraints are present to ensure a level of automated protection
against malicious or accidental modication of data, and ensure the logical
consistency of data. Rules can be dened on the static state of the database, or
on transitions (as conditions to be veried before data is modied). In the
context of blockchains, such rules would need to be applied at different levels, to
the raw processing of data and in addition, to the functioning of smart contracts
or secondary processes/transformations on blockchain related data records.
252 G.W. Peters and E. Panayi
We provide a brief review of the concepts behind the Clark-Wilson (CW) model
which has been adopted in business and industry processes. Clark and Wilson
(1987) argued the case for consideration of control over data integrity and not just
considerations over control of disclosure. The Clark-Wilson model consists of
subject/program/object triples and rules about data and application programs. The
core of the CW model specication involves two key components: the notion of a
transaction, which is characterized by a series of operations that transition a system
from one consistent state to another consistent state; and the separation of duty (in
banking settings often forming part of governance structures).
In the case of blockchain settings, one may think the rst component denoted the
transaction as any function operating on the blockchain, such as addition of data
to the blockchain, the verication of the blockchain transactions or a smart contract
that reads or modies the blockchain state. The second component involving
separation of duty involves consideration of who may perform verication, who
may view or alter data on the blockchain or attached to the blockchain, or who may
view or execute or initiate such smart contracts.
In the CW model all data to be considered is partitioned into two sets termed
Constrained Data Items (CDIs) and Unconstrained Data Items (UDIs). Then in
addition, there are subjects which are entities that can apply transformation pro-
cesses to data items to take CDIs from one valid state to another. The term
transformational procedure makes it clear that the program has integrity-relevance
because it modies or transforms data according to a rule or procedure. In addition,
there are integrity validation procedures which conrm that all CDIs in a system
satisfy a specied integrity scope. Data that transformational procedures modify are
called CDIs because they are constrained, in the sense that only transformational
procedures may modify them and that integrity verication procedures exercise
constraints on them to ensure that they have certain properties, of which consistency
and conformance to the real world are two of the most signicant. Then UDIs
represent all other data, such as the keyed input to transformational procedures.
Given these structures, the CW model then species 6 basic rules that must be
adhered to in order to maintain integrity of a system. We provide these below, along
with a description of how these pertain to a blockchain structure.
254 G.W. Peters and E. Panayi
There must be a single written audit le that records all the transaction
processes.;
Comment: Clearly this exists in the case of blockchain. An advantage of the
blockchain is that it can provide guarantee of absence of modication. In the
context of ownership, the blockchain proves that an asset has been transferred to
somebody, and has not been transferred to somebody else subsequently.
Because transactions can only be found on the blockchain, if a transaction is not
found there, from the blockchains perspective it does not exist.13
13
Factom whitepaper, available at https://raw.githubusercontent.com/FactomProject/FactomDocs/
master/Factom_Whitepaper.pdf.
Understanding Modern Banking Ledgers Through Blockchain 255
and subjects are grouped into ordered levels of integrity. The model is designed so
that subjects may not corrupt objects in a level ranked higher than the subject, or be
corrupted by objects from a lower level than the subject. Many applications
therefore consider such models for data integrity as useful in instance for banking
classication systems, in order to prevent the untrusted modication of information
and the tainting of information at higher classication levels.
The Biba model is summarised by the following three simple components:
The subject should be able to read an object only if they have a higher or equal
security status than the object. This is known as the Simple Integrity Axiom and
stated in another manner it says that a subject at a given level of integrity must
not read an object at a lower integrity level (no read down).;
The subject should be able to write an object only if they have a lower or equal
security protocol than the object they write too. This is known as the Star
Integrity Axiom and when stated in another manner it says that a subject at a
given level of integrity must not write to any object at a higher level of integrity
(no write up).;
The nal component is the Invocation Property which states that a process from a
lower integrity level can not request higher integrity level access. In otherwords it
can only interface with subjects at an equal or lower level of integrity status.
14
http://cryptoassetscore.readthedocs.org/en/latest/integrity.html.
Understanding Modern Banking Ledgers Through Blockchain 257
access to the raw data itself. Clearly, a useful aspect for many nancial processing
applications of blockchain.
Basically, one can think of attaching Enigma to a particular type of blockchain
architecture, and deploying it to enforce on the blockchain a feature of data integrity
and privacy. It will connect to an existing blockchain and off-load private and
intensive computations to an off-chain network. All transactions are facilitated by
the blockchain, which enforces access-control based on digital signatures and
programmable permissions. In this architecture the code to be executed (such as a
smart contract etc.) is performed both on the public blockchain and on Enigma for
the private and computationally intensive components. It is argued that in this
manner, Enigma can ensure both privacy and correctness. In addition, one can
provide veried proofs of correctness on the blockchain for auditability purposes.
Unlike blockchain approaches such as those underpinning bitcoin, in which
execution in blockchains is decentralized but not distributed, meaning that every
node redundantly executes common code and maintains a common state, in
Enigma, the computational work is efciently distributed across the network.
As detailed in Zyskind et al. (2015), the off-chain network they develop in
Enigma overcomes data integrity based issues that blockchain technology alone
cannot handle as follows:
The DHT, which is accessible through the blockchain, stores references to the
data but not the data themselves. Private data is encrypted on the client-side
before storage and access-control protocols are programmed into the blockchain.
It utilises privacy-enforcing computation in Enigmas network, in order to
execute code without leaking the raw data to any of the nodes, while ensuring
correct execution. This is key in replacing current centralised solutions and
trusted overlay networks that process sensitive business logic in a way that
negates the benets of a blockchain.
In this section we discuss items that may be of relevance in the banking and
insurance sectors that could benet from the developments of blockchain tech-
nologies. Industry publications, such as the recent Euro Banking Association
report15 argue for the potential of blockchain technology to partly replace trusted
third parties, commonly employed in many roles in nance as custodians, payment
providers, poolers of risk and in insurance settings. Remember that the primary
15
Cryptotechnologies, a major IT innovation and catalyst for change, available at https://www.abe-
eba.eu/downloads/knowledge-and-research/EBA_20150511_EBA_Cryptotechnologies_a_major_
IT_innovation_v1_0.pdf.
Understanding Modern Banking Ledgers Through Blockchain 259
roles of such trusted third parties is to provide functionality such as: validation of
trade transactions; prevention of duplicated transactions, the so-called
double-spending issue; recording of transactions in the event of disputes over
contract settlements or deliverables etc.; and acting as agents on behalf of associates
or members. The blockchain can provide alternative solutions to full these roles
through the provision of a veriable public record of all transactions which is
distributed and can be decentralised in its administration.
In thinking about the possibilities of blockchain functionality within the banking
sector, there are a range of different potential avenues to explore that move beyond
the typical discussion on remittance services. Banking systems are large and
complex, including a range of features such as back-end bookkeeping systems,
which record customer account details, transaction processing systems, such as cash
machine networks, all the way through to trading and sales, over the counter trades
and interbank money transfer systems. Today, we are however unaware of any
papers that go beyond this high level discussion and detail exactly how and what
form blockchain technology may provide benet in these aspects in banking
settings.
In this work we will aim to provide a greater detail to these possible applications
of blockchain technology. In particular we will discuss things related primarily to a
few important unexplored areas:
Government cash management the central bank and treasury accounts in par-
ticular the Treasure Single Account (TSA) of (Pessoa and Williams 2013);
automation, decentralised and distributed banking ledgers;
automated and distributed Over The Counter (OTC) contracts/products and
clearing and settlement;
automated client account reconciliations; and
automated, distributed loss data reporting.
One of the potential incentives for nancial institutions, banks, insurers and
banking regulators for the development of distributed blockchain technologies for
these types of applications involves the reduction of overhead and costs associated
with audit and regulation. In addition, more automation and efciency in transaction
processing, clearing and reconciliation can help to reduce counterparty credit risks.
Before entering into specic examples, we outline some core features that
blockchain approaches share which can be both benecial and detrimental. These
require careful consideration when developing the applications to be discussed, as
we have seen in previous discussions above on data integrity preservation.
Immutability of itemized components in the blockchain. A blockchain is
effectively a distributed transaction database or ledger that is immutable, in that
data stored in the blockchain cannot be changed, i.e. deleted or modied.
However, some versions of blockchain frameworks are starting to emerge that
alter the perception of immutability, such as the Enigma project discussed
above. This approaches the irreversibility of the standard blockchain framework
by only allowing access to data for secure computations in reversible and
260 G.W. Peters and E. Panayi
controllable manners. In particular they also ensure that no one but the original
data owner(s) ever see the raw data.
Transparency of information presented on the blockchain. Many blockchains
being created are publicly accessible by anyone with an internet connection and
are replicated countless times on participating nodes in the network, though
private versions or restricted blockchain networks are emerging also, as dis-
cussed previously. The question is to what extent the application requires private
versus public components. In modern regulatory changes on banking and
nancial institutions there are numerous competing constraints which emphasize
both the importance of nancial disclosure, such as Pillar III of Basel III banking
regulations, requiring nancial institutions to demonstrate transparency in their
reporting and their relationship with regulators, and on the other side there are
also duciary duties that institutions maintain in upholding data privacy on
behalf of their customers. Therefore, alternative approaches to private versus
publick blockchain networks are also being explored where instead the data on a
public ledger may have different levels of data integrity structure protocols
which implement possibilities such as encryption of data stored in blockchains,
see project Enigma for example (Zyskind et al. 2015).
16
Note: the technical note is not representing the direct views of the IMF.
Understanding Modern Banking Ledgers Through Blockchain 261
basic step of ensuring that all cash received for projects operated or approved by
government functions is available in a timely fashion for carrying out governments
expenditure programs and making payments as required. It is particularly in this
feature that we argue that blockchain architectures would benet this application
domain.
In this regard, a TSA is a single checking account for government funds from
domestic revenue and some foreign funds (together called treasury funds) which are
deposited and from which required money can be disbursed in timely fashion. It is a
unied structure of government bank accounts that provides a consolidation of
government cash resources in a common ledger. It was proposed to act as an
essential tool for consolidating and managing governments cash resources, and in
doing so it provided a means to reduce borrowing costs. This is particularly useful
in countries with banking structures which are not well organised, fragmented and
inefcient. Many countries have successfully established such TSA structure for
their government accounts. Since the TSA structure is based on the principle of
Pessoa and Williams (2013) unity of cash and the unity of treasury, a TSA is a
bank account or a set of linked accounts through which the government transacts all
its receipts and payments. The principle of unity follows from the fungibility of all
cash irrespective of its end use.
Several case studies now exist demonstrating the potential of such TSA account
structures to improve the situation that many emerging market and low-income
countries face relating to the fragmentation of their banking systems responsible for
handling of government receipts and payments. Typically, in such countries that
have not instigated such a TSA structure, there are signicant challenges in the
banking structures since the treasury may often lack governance and may not even
possess a centralized control over the ruling governments cash resources. Conse-
quently this can result in cash being idle or unavailable when required to fund core
infrastructure projects or expenditure programs for development of the economy. It
also extenuates the debt for such countries since the available cash for expenditures
is laying idle for extended periods in numerous bank accounts that are fragmented
and dispersed over different spending agencies, while in the meantime the gov-
ernment will be borrowing additional funds and increasing debt in order to mis-
takenly fund such projects and execute its budget plans.
As detailed in Pessoa and Williams (2013) if a countrys government has such
inefciencies by lacking effective control over its cash resources there can be
numerous consequences:
Idle cash balances in bank accounts often fail to earn market-related
remuneration.
The government, being unaware of these resources, incurs unnecessary bor-
rowing costs on raising funds to cover a perceived cash shortage.
Idle government cash balances in the commercial banking sector are not idle for
the banks themselves, and can be used to extend credit. Draining this extra
liquidity through open market operations also imposes costs on the central bank.
262 G.W. Peters and E. Panayi
Clearly such inefciencies can be improved with an automated trusted third party
system such as that offered by some permission style blockchain technologies
working as a ledger for such accounts under the auspice of a TSA structure.
Furthermore, one can argue for the TSA type structure since such a nancial
pool example is a concept that segregates two important aspects of this process, the
separation of the nance function and the service delivery functions of sector ofces
and departments of regions, cantons and zones. We have seen that establishing such
a feature in a blockchain would require application of data integrity functions. In
concept such segregation of duties, is important as it allows public bodies to focus on
their core responsibilities whilst nancial execution such as control of cash, pay-
ments, accounting, reporting can be handled on their behalf by a pool of profes-
sionals or as we propose here, the automation by a privacy preserving, permissioned,
distributed blockchain structure. Clearly in such a structure, public bodies still dene
and authorise their budgets and expenditures within these budgets.
Here we recall the denition provided in Pessoa and Williams (2013) for a complete
TSA structure which they argue has three core components:
1. Unication of the governments banking structure which will enable the treasury
to have oversight of government cash flows in and out of these bank accounts
and fungibility of all cash resources. Note particularly in a blockchain type
extension can include a real-time electronic banking component and can also be
private but remove the need for a single central oversight component in a
government, instead replacing it with a distributed verication system.
2. In traditional TSA structures there would be no other government agency
operating bank accounts outside the oversight of the treasury. In general the
design of the TSA and access to the TSA will depend on the banking structures
in place in a given country. In this regard, there are numerous different block-
chain architectures that will be suitable for the blockchain version of the TSA.
3. All government cash resources, both budgetary and extra-budgetary, should be
included in the consolidated TSA account and the cash balance in the TSA
main account is maintained at a level sufcient to meet the daily operational
requirements of the government (sometimes together with an optional contin-
gency, or buffer/reserve to meet unexpected scal volatility). (Pessoa and
Williams 2013). Such features could be automated in blockchain versions of
such an account through smart contract structures running on the blockchain
TSA ledger. The minimum accounts that should be included in the TSA should
cover all central government entities and their transactions. These include:
Note in a standard TSA banking structure there are numerous possibilities relating
to where the TSA account should be maintained. That is in which institution, in
most cases it is argued that the Central bank of the country may be the appropriate
venue for such an account. However, all cases require a trusted third party to
administer and provide governance and oversight of this critical consolidated
account. One potential advantage of a TSA account placed under a blockchain
structure with access through private key permissions and smart contracts is that
when it is placed under a private network, there would not need to be a single point
of administration, it would be a trusted closed network which has been effectively
decentralized. We argue that this could have the potential to remove issues that may
arise with governance and oversight when entrusting such key accounts to one
single institution, especially in a fragmented banking and institutional structure.
In addition, as noted in Pessoa and Williams (2013), one can establish the TSA
banking structure with ledger sub-accounts in a single banking institution (not
necessarily a central bank), and can accommodate external zero balance accounts
(ZBAs) in a number of commercial banks. This can still be achieved in a blockchain
framework in several different architectures. One of which may involve separate
ZBAs maintained as internal blockchain ledgers in each commercial bank in the
network, followed by a linking of these blockchains to the main TSA blockchain
264 G.W. Peters and E. Panayi
ledger account, with links being executed for transactions based on smart contract
technology.
There are two main categories for architecture for a TSA banking account which
align well with different architectural decisions for the blockchain version of the
TSA, these involve either a centralized or a distributed architecture. In the cen-
tralized structure, all revenue and expenditures of the government are on a single
ledger which is administered by a single trusted third party such as the central bank,
whereas, in the distributed TSA structure there will be a hierarchy of organizational
structures each with their own separate transaction accounts in the banking system,
but still a single TSA account that contains all balances by close of business each
day. As detailed in Pessoa and Williams (2013), the Sweedish TSA structure
involves zero balance accounts in the central bank which are authorised by the
minister for nance and available for individual spending agencies. In this case,
money is transferred from the TSA to such accounts for payment of authorised
project expenditures as required. All these accounts are cleared/reconciled with the
TSA account daily.
In addition to understanding the network structure and components of the TSA
account, there is also the aspect of revenue collection, remittance, payments and
processing under the TSA account to be discussed and to consider how blockchain
technology can facilitate the functioning, automation and decentralization of such
important components. In traditional TSA structures there are two possibilities as
detailed in (Pessoa and Williams 2013, Section II Part A) where they describe either
centralized transaction processing or decentralized approaches. Under the block-
chain version of such a TSA structure, all transactions processing and remittance
could be performed in a decentralized manner which would not require oversight of
a particular trusted third party network member, as all transaction processing would
be automated on the blockchain.
Futhermore, such automation of these processes into the blockchain structure
would be more efcient and less costly than existing practices. Currently the best
practice adopted for TSA account processing is to utilise the commercial banking
network. That is, it is common to contract the commercial banks for revenue
collection purposes, these commercial banks transfer revenues collected to the TSA
main account daily (so as to avoid float or need of imprest cash amounts). As noted
in Pessoa and Williams (2013) such a system, though widely utilised, involves a
remuneration system which is not transparent and does not clearly indicate the
cost of revenue collection services provided by banks. The banks use the free float
to invest in interest-bearing securities. This process clearly distorts the TSA
structure and concept.
In this manner one could argue that the blockchain version of the TSA account
structure can further reduce costs associated with remittance services and revenue
collection services currently charged to the government on a xed contractual basis.
It is currently the case that such remittance services, when provided in a blockchain
structure such as in the bitcoin network, can be orders of magnitude cheaper than
those offered by traditional remittance providers in nancial services industries.
Understanding Modern Banking Ledgers Through Blockchain 265
1. Bank Loans which are reported in the Notes Payable account and are to be
utilised for short, medium or long term nancing and typically asset backed. The
Notes Payable Ledgers record outstanding notes and include aspects such as
the identier for the note, its holder, its maturity and current interest rate, and the
original and current balance.
2. Bond Issuances are summarized in the Bonds Payable balance sheet item and
specic details of each issuance are detailed in a journal entry record for each
with individual separate long-term liability accounts. Such issuances allow
nancial institutions to obtain medium and long term capital, but they create a
contractual obligation to pay a xed amount of interest at specied intervals in
the future.
3. Stock Issues are recorded as par or stated value for issued shares in Common
Stock and Preferred Stock account ledger. Typically, a corporation will use
different Capital Stock accounts for each class of stock.
Apart from the debt and equity capital recording ledgers, there are also other key
ledgers to consider such as the Property and Systems records. These keep track of
all depreciating property, plant and equipment. Typically it would involve the
recording of three primary types of transactions which include:
1. Acquisition of property where an institution would use buildings and equipment
to generate revenue;
2. Depreciation of property, plant and equipment;
3. Disposition of property.
To complete the third key component of nancial reporting systems we also
mention the basic idea of the Journal Entry and Financial Reporting Systems where
institutions are able to record transaction in the general ledger using three types of
accounting entries that summarize High-Volume transactions such as sales and
purchases, Low-Volume transactions such as changes in debt and equity capital in
order to remove depreciating property etc., and closing entries.
In the standard ledger systems described above different governance structures
may be put in place to resolve potential accounting malpractice and fraud from
arising. This is typically achieved by separating responsibilities for the double entry
process, otherwise known as dual control systems or decentralized responsibility.
These are typically enactments of different data integrity processes as described
previously.
We note that with the development of blockchain ledger technologies and smart
contracts, many of these processes and ledgers/accounting books just described
which make up the nancial accounting system can be automated through a
blockchain structure. Such blockchains could take many forms, they could be either
distributed within an organisation or even available as a public ledger (perhaps with
some form of encryption for private data) that is shared between institutions, reg-
ulators and government agencies undertaking oversight, taxation etc.
In developing blockchain ledgers, one will need to consider how often to con-
sider constructing hash entries, i.e. how often to aggregate data together before
268 G.W. Peters and E. Panayi
adding a hash entry to the blockchain ledger, as described in the previous overview
section. In the context of banking ledgers, this will probably depend on the types of
data being placed on the ledger, for instance, one may consider such data as divided
into the following components. Transaction data is one source of data that must be
considered, it is the records of information about each transaction and it is expected
to change regularly as transactions progress and are completed. Other less frequent
data includes aspects of standing or reference or meta data which is typically for all
practical purposes permanent and includes names and addresses, descriptions and
prices of products. We would suggest that the blockchain hashing for such nancial
records and ledger creation should follow a combination of both batch processing
and in some applications real-time processing.
There are a few developments of second generation blockchain ledgers being
developed for such banking ledger processing. For instance Balanc317 is a new
blockchain technology being developed based on smart contracts and a blockchain
architecture with the purpose of performing accounting ledger processing, in this
case as a triple entry system, rather than the double entry systems described above. It
is argued that the non-repudiability and comprehensive audibility of the blockchain
can be utilised to guarantee the integrity of accounting records. The blockchain
architecture in this case utilises a range of different products for data integrity and
security, they include EtherSign combined with an IPFS decentralized data storage
platform and smart contracts enacted through Ethereum blockchain. In this way this
account ledger is able to construct, store, manage, and digitally sign documents. The
admissible documents in this system include features such as self-enforcing smart
contracts like employment contracts or invoices, or traditional text agreements.
Invoicing through smart contracts automatically processes and records payments.
Before exploring other applications of blockchain, it is worth to observe that the
immutability of the blockchain record when automated for transactions must be
carefully considered in some cases. For instance, the issue of loss provisioning in
the ledger of a banking institution must be carefully considered. We briefly com-
ment on this below.
After the 2008 nancial crisis that affected the world wide banking sector there
were signicant changes to banking regulations, insurance regulations and
accounting standards. In particular the regulation we mention in this section that
must be carefully considered in blockchain ledger applications in banks is that of
the provisioning accounting standard now known as IFRS 9 Financial Instruments
17
https://consensys.net/ventures/spokes/.
Understanding Modern Banking Ledgers Through Blockchain 269
18
http://www.ifrs.org/current-projects/iasb-projects/nancial-instruments-a-replacement-of-ias-39-
nancial-instruments-recognitio/Pages/Financial-Instruments-Replacement-of-IAS-39.aspx.
270 G.W. Peters and E. Panayi
automated via a smart contract structure, see page 7 process model for such clas-
sication automation.19
In addition, the smart contract implementation would need to be developed
under IFRS 9 compliance to apply two criteria to determine how nancial assets
should be classied and measured: the entitys business model for managing the
nancial assets and the contractual cash flow characteristics of the nancial asset. It
should be noted that unless an asset being classied meets both test requirements,
then it will be recorded on the blockchain banking ledger in terms of fair value
reporting in the prot and loss. If the asset passes the contractual cash flows test, the
business model assessment determines how the instrument is classied. For
instance, if the instrument is being held to collect contractual cash flows only then it
is classied as amortized cost. However, if the instrument is to both collect con-
tractual cash flows and potentially sell the asset, it is reported at fair value through
other comprehensive income (FVOCI). Further background on the requirements of
the IFRS 9 provisioning standards that blockchain ledgers and processing must
adhere to can be found at IASB documents, http://www.ifrs.org.
In addition to the role of blockchain in banking ledgers, blockchain and smart
contracts may also be utilised for other roles, such as the clearing and settlement
processes. We briefly outline the role of settlement processes in the following
section.
A banking area which has been hampered by the inefciencies of traditional pro-
cesses is that of settlement of nancial assets. Major markets such as the US,
Canada and Japan still have a 3-day settlement cycle (T + 3) in place, while the
EU, Hong Kong and South Korea have moved to T + 2. This delay in settlement
drives a number of risks, which we will discuss in the following section.
In order to understand how blockchain technology could potentially enter into
this eld, it is useful to overview the lifecycle of a trade. Firstly, a buyer comes to an
agreement with a seller for the purchase of a security. What follows then is referred
to as clearing, when the two counterparties update their accounts and arrange for the
transfer of the security and the associated money. This process entails20:
Trade valuation;
Credit monitoring;
Position management;
19
http://www.ifrs.org/current-projects/iasb-projects/nancial-instruments-a-replacement-of-ias-39-
nancial-instruments-recognitio/documents/ifrs-9-project-summary-july-2014.pdf.
20
Source: Risk management issues in central counterparty series, presentation by Priyanka Mal-
hotra at the Systemic Risk Centre at LSE.
Understanding Modern Banking Ledgers Through Blockchain 271
Member reporting;
Risk management;
Collateral management;
Netting of trades to single positions;
Tax handling;
Failure handling.
The actual exchange of the money and securities is termed settlement, and
completes the cyclethis is typically 2 or 3 days after trade execution and can
involve the services of institutions, such as custodians, transfer agents, and others
(Bliss and Steigerwald 2006). In a typical trading-clearing-settlement cycle, the
following actors are involved:
On the trading side
The investors (buyer and seller) who wish to trade.
Trading members (one for the buyer and one for the seller) through which
the investors can place their orders on the exchange.
The nancial exchange or multilateral trading facility, where the trading
members place the trades.
21
For an example of EU regulation in this area, see http://www.fca.org.uk/rms/being-regulated/
meeting-your-obligations/rm-guides/emir.
272 G.W. Peters and E. Panayi
22
BCG, Shortening the Settlement Cycle October 2012, available at http://www.dtcc.com/media/
Files/Downloads/WhitePapers/CBA_BCG_Shortening_the_Settlement_Cycle_October2012.pdf.
23
https://www.fanniemae.com/content/fact_sheet/dvp-dvf-comparison.pdf.
Understanding Modern Banking Ledgers Through Blockchain 273
operate a node to validate transactions. The investors still trade through a broker
(due to naked access regulations), but the exchange fees can be drastically
reduced.
At the clearing level. A consortium of clearing members can set up a distributed
clearing house, thus eliminating the need for a CCP. Clearing then becomes
closer to bilateral clearing, with the difference that the contract stipulations are
administered through a smart contract, and thus there is less scope for risk
management issues.
At the settlement/custodian level.
A concrete example of how the entire lifecycle of a trade would look like is as
follows: A buyer submits an order to buy a particular amount of an asset, for which
there is an equivalent selling interest, through his broker. The buyers and sellers
brokers then create a transaction for the transfer of that amount of the asset, which is
then transmitted to the distributed exchange network and veried. Once a block of
transactions is veried, it is transmitted to the decentralised clearing house, where a
new transaction is created, involving the brokers clearing members. Once this
transaction is veried in the clearing house blockchain, it is then transmitted to the
settlement system, where a new transaction is created involving the custodians or
CSDs, and the transfer of assets occurs automatically once this transaction is
conrmed.
Such a conguration would rstly increase the speed of the entire settlement
cycle from days to minutes or even seconds, where we would essentially have
continuous settlement. There are a number of industry initiatives already in the
digital asset transfer and settlement space, and we mention indicatively R3 CEV,24
Digital asset holdings,25 Symbiont,26 Chain27 and SETL.28 HitFin29 has proposed
an alternative approach from the one described here, where trades are cleared
bilaterally on a private blockchain, in less than 17 s. Besides the fast transaction
settlement and automatic settlement of contracts upon maturity, all reporting,
compliance and collateral management can be handled through the blockchain, thus
reducing backofce coss (Fig. 1).
24
http://r3cev.com.
25
http://digitalasset.com.
26
http://symbiont.io.
27
http://chain.com.
28
http://setl.io.
29
www.hitn.com.
274 G.W. Peters and E. Panayi
Fig. 1 Clearing in a centralised and decentralised ledger. Image source: The Fintech 2.0 Paper:
rebooting nancial services, available at http://www.nextra.com/nextra-downloads/newsdocs/
The%20Fintech%202%200%20Paper.PDF. In this instance, the blockchain version of clearing is a
complete decentralisation where the roles of the exchange, the clearing house and the settlement
system are no longer separated since they are combined into a single distributed blockchain
architecture. However, once could argue that for reasons governance it may be more appropriate to
consider intermediate architectures for blockchain decentralisation that still incorporates these
separations of roles, such as the ones discussed in this section
7 Conclusions
This chapter has served to rst highlight some of the recent innovations in the space
of blockchain technologies. It has outlined some important aspects of blockchain
architectures and their commonality and distinguishing features from different types
of database structures. It has then described a number of features that are vital from
a nancial application perspective, including permissioning, data integrity, data
security and data authenticity as well as important regulatory requirements relating
to account provisioning for nancial asset reporting, and the blockchain aspects that
276 G.W. Peters and E. Panayi
can help adhere to these. Then several innovative new areas of development for
second generation blockchain technologies are detailed, including central bank
treasury ledgers, retail and investment bank ledgers, trading, settlement and clearing
processes, nishing with a discussion on multi-signature Escrow services. Like all
prior disruptive technologies there will be benecial and detrimental aspects of
blockchain technologies that will need to be carefully considered prior to devel-
opment and commercialisation of the ideas presented in this chapter. However, we
believe that with the onset of the internet of money, the blockchain revolution will
play an integral part in this brave new world.
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Author Biographies
Keywords Blockchain
Bitcoin
Cryptocurrency New Institutional Eco-
nomics
Austrian Economics
Catallaxy
1 Introduction
This chapter uses economic theory to explore the implications of the blockchain
technology on the future of banking. We apply an economic analysis of blockchain
based on both new institutional economics and public choice economics (Davidson
et al. 2016). Our main focus is on the economics of why banks exist as organi-
zations (rather than a world in which all nancial transactions occurring in mar-
kets), and how banks are then impacted by technological change that affects
transaction costs. Our core argument is that blockchains are more than just a new
technology to be applied by banks in the same way that computers and the internet
have driven signicant improvements in banking technology. If we were to think
about blockchains in this wayfrom the perspective as a new technology to be
adopted and diffusedbanks would more or less remain the same. Instead, we
argue that blockchains compete with banks as organizations, enabling banking
transactions to shift out of centralized hierarchical organizations and back into
decentralized markets. Blockchains are a new institutional technologybecause of
how they affect transaction costs in nancial marketsthat will fundamentally
re-order the governance of the production of banking services. The upshot is that
while banking itself may not fundamentally change, banks might. Blockchains, we
argue, will alter the boundaries of self-organization; the question is why, and how?
The second half of this chapter explores this implication through broader
political economy lens in which banking moves out of organizations and deeper
into markets. We examine this as a form of institutional economic evolution in
which the boundary of catallaxyi.e., a self-organized economy (Hayek 1960)is
enlarged, at the margin of the banking sector. As blockchain technologies work
through bankingat the margins of measurement, monitoring, and new forms of
automated governance (e.g. smart contracts and Distributed Autonomous Organi-
zations)they will enable a deeper process of institutional evolution to begin to
unfold (MacDonald 2015b). The permisionless and non-territorial character of this
unfolding secession of banking transactionsfrom hierarchically organized banks
to spontaneously organized blockchainsreduces institutional exit costs. Such
institutional competition enables evolutionary discovery in the institutions of
banking.
We proceed as follows. Section 1 outlines the basic economics of banks as
organizations in the provision of banking services. We argue banks exist because of
the transaction costs of using markets in coordinating the supply and demand for
nancial services. Section 2 introduces the new economics of blockchain, based on
new institutional and public choice economics. This discussion is centered on
transaction cost economics and the economics of governance more broadly. Sec-
tion 3 ties these arguments together to derive a rst principles economic analysis of
the effect of blockchain technology on banking. Section 4 then explores broader
political economy implications of the institutional orders of a market economy.
Blockchains and the Boundaries of Self-organized Economies 281
Banking, nance, and payments services are among the oldest of industries. These
commercial services predate modern capitalism, even emerging before modern
governments (Ferguson 2008; Hodgson 2015). Many of the functions that banks
serve are necessarily familiar to us: the movement and production of capital
(savings, nance), and the operation of the payments system (money). That banks,
and the economic functions they perform, have existed for thousands of years, and
in all parts of the world, at all stages of economic development, suggests a robust
economic function. But what precisely is the robust economic function that banks
provide; why do banks persistently exist?
Put simply, banks provide the specialized function of securely storing liquid
capital. For effectively any storable fungible assets banks are able to utilize scale
economies associated with providing this service. These scale economies would
also suggest oligopoly or even monopoly provision in a particular geographical
region; that is, centralization. Centralizing the excess supply of capital opens the
possibility of creating a new market by lending this capital out to those with excess
demand, such that banks becomes an internal capital markets.
The economic role of banks in a market economy, like rms more generally, is
to internalize externalities; and in doing so they form subeconomies (Holmstrom
1999). Metaphorically, banks can be viewed as miniature economies: islands of
command organization in a sea of spontaneous market exchanges (Coase 1937).
Moreover, the island economies are complete with their own rules of the game
(Buchanan 1990), over which individuals (as borrowers and savers) can choose to
opt in or out. To complete the metaphor, the banking industry is not a centralized
supercontinent but an archipelago, due to the value of exit rights as an incentive
mechanism and tool to discipline the abuse of power.
It is clear, then, that beyond the physical storage of precious metals and other
nancial assets, a bank in this sense is a centralized ledger of transactions, whether
of capital or payments, which records balances between many different parties.
A bank, in the modern sense, is an internalized market: it is an organization that
functions as a platform (a two-sided market, Rochet and Tirole 2003) to match
those with excess supply of capital (savers) with those with excess demand for
capital (borrowers). Banks intermediate two sides of a market. This intermediation
is precisely what the recent wave of P2P nance endeavors to disrupt. By matching
sellers of capital (those who would otherwise make deposits in a bank) with buyers
of capital (those who would otherwise seek loans from banks) directly, the P2P
nance directly threatens banks.
Let us return to the simple economic question with which we began: why do
banks exist? That is, why are reallocations of nancial capital, including payments,
not entirely undertaken as decentralized market transactions in the form of a
two-party system, rather than in the three-party system with banks as the third party
intermediating agent? This is what P2P nance is trying to create, but it hasnt quite
got there yet. From what we have established above, these questions are equivalent
to enquiring into the value of a centralized ledger itself.
282 T.J. MacDonald et al.
The basic scheme of answer to this, we propose, uses New Institutional Eco-
nomics (NIE), also known as Transaction Cost Economics (TCE) . This area of
economics follows Nobel Laureate Ronald Coase (1937) who rst explained the
existence of rms in consequence of the transaction costs of using a market. For
someone with a surplus of capital, the transaction costs of participating in a
nancial market would usually be prohibitively expensive. To nd a borrower,
write a contract, monitor the exchange, and enforce that contract would quite
simply require huge amounts of capital, time and expertise. The owner of the
surplus capital would also be sacricing liquidity. A symmetric problem similarly
exists for the demander; how does a borrower nd a potential supplier that meets
their idiosyncratic terms? Without banks many of these mutually welfare-enhancing
exchanges would simply never take place.
This is a two-sided matching problem (Roth and Sotomayor 1992) that is greatly
facilitated by the existence of a specialized third-party acting as both a focal point
and aggregator to transform otherwise highly heterogeneous agents into liquid
capital markets. Banks achieve this through capital pooling, through aggregation and
disaggregation, information pooling, economies in monitoring, creating submarkets
with different risk-reward proles, through various specializations in writing and
enforcing contracts, and bundling nancial services. Banks create and harness
reputational incentive mechanisms that enable them to enforce contracts at lower
cost than could distributed agents because of their ability to exclude defaulting
borrowers from subsequent access to nance. A third party also enables coordination
across geographic regions through networks through economies of scale, as well as
bundling together different types of nancial services through economies of scope.
In sum, banks exist as third-party intermediating organizations because there are
substantial costsphysical costs, information costs, coordination costswith using
the market to match the supply of and demand for nancial assets (Earl and Dow
1982). Financial intermediaries such as banks have been the method for solving this
problem for many centuries. Banks have been comparatively economic efcient, so
to speak. The entrance of blockchains as crypto-secured distributed ledgers, how-
ever, disrupts these basic transaction costs of the market for nancial assets. This
then affects the economic logic and efciency margins of banks, whose entire logic
of existence derives from their comparative economic efciency compared to
markets. What, then, are the specic transaction costs margins at which blockchains
will impact upon banks? This will be the subject of Sects. 2 and 3.
called the Byzantine Generals problem) that hither-to had defeated all endeavors
to create a non-centralized peer-to-peer electronic cash system (Dourado and Brito
2014). The blockchain solves this problem using a decentralized database (or
ledger) with network-enforced processes that are based on a proof-of-work con-
sensus mechanism for updating the database (Nakamoto 2008; Franco 2014).
The blockchain is best decoupled from its connection to Bitcoin because the
economic value and disruptive potential of blockchain does not depend upon the
value and prospect of Bitcoin (Buterin 2015). Blockchains are better understood as
a new general purpose technology (Bresnahan and Trajtenberg 1995; Lipsey et al.
2005) in the form of a highly transparent, resilient and efcient distributed public
ledger (i.e., decentralized database). The general purpose technology is the block-
chain and the many applications stemming from this invention are specic inno-
vations (Pilkington 2016). The entrepreneurial problem of the blockchain is to
discover such market applications (Allen 2016), which is a considerable challenge
involving concurrent institutional innovations (i.e., in governance). This is because
in principle such a distributed ledger can be applied to disrupt any centralized
system that coordinates valuable information (Wright and De Filippi 2015; He et al.
2016; Walport 2016).
Ledgers are a very old technology. By the late twentieth century they have been
digitized, but until invention of blockchain in 2008, they always remained cen-
tralized. The ledger is a technology of accounting, of keeping track of who owns
what, and is instrumental to modern capitalism (Nussbaum 1933; Allen 2011;
Hodgson 2015). But so too is trust in the ledger, which is most effective when it is
centralized and strong, and so centralized ledgers for property titling, contracts,
money, and so on, are also critical in connecting government to modern capitalism.
Centralized solutions are expensive and have many problems, particularly in
relation to problems of trust and its abuse. Yet until very recently no effective
decentralized solution has existed. In contrast, the blockchain technology is trust-
less, meaning that it does not require third party verication (i.e., trust), but instead
uses a powerful consensus mechanism with cryptoeconomic incentives to verify
authenticity of a transaction in the database. These properties also make block-
chains safe. Security is maintained even in the presence of powerful or hostile third
parties. In a recent lead article on blockchainwhich they dubbed The trust
machineThe Economist (2015) explained that:
Ledgers that no longer need to be maintained by a companyor a governmentmay in
time spur new changes in how companies and governments work, in what is expected of
them and in what can be done without them.
There are many ways to think about the basic economics of blockchains. One
method centers on why decentralized solutions to ledgers, now technically possible,
are likely to become increasingly cost effective compared to centralized solutions.
Along this line we could model the economics of blockchain as a new technology
that is rapidly running down a learning curve, or equivalently as a technology cost
curve rapidly falling, such that it becomes increasingly competitive against the
mature technology of a centralized ledger, driving technological substitution. The
284 T.J. MacDonald et al.
platform technology (i.e., rule system) that performs this general service of
decentralization (Potts 2001).
From the Hayekian perspective then, blockchains are actually catallaxies, not
economies, for they serve not one particular end but contribute to the realization of
a number of individual objectives which no one knows in their totality. A catallaxy
is characterized by a multitude of agents living within an extended order (Hayek
1988). Blockchains are orders of economies in the same way a market order is a
catallaxy of mutually adjusting individual plans (economies). The rst remarkable
property of emergent economies built on blockchains is that they are
non-territorially unbundled (MacDonald 2015d). Second, the price system in
Hayeks conception operates at the level of a system of markets, as in a region or
nation, but a further surprising property of blockchains is that they provide a
mechanism to radically reduce the size and scale of effective catallaxies.
We can now furnish some broad outlines based upon economic theoryor what are
sometimes called pattern predictions (Hayek 1964, 1989)about the future of
how blockchains might develop in banking. Above, we identied the relevant
theory as the economics of technological dynamics, new institutional economics,
and public choice economics. Our aim here should not in any way be taken to be
equivalent or even comparable to specic identication of entrepreneurial oppor-
tunities from blockchains, nor do we seek to outline specic risks arising from their
adoption (Tasca 2015). We do not wish to be seen to underestimate the immense
entrepreneurial problem underpinning the discovery of applicable opportunities for
Blockchains and the Boundaries of Self-organized Economies 287
blockchains (Allen 2016) or the potentially immense societal impacts from systemic
diffusion of the technology (Atzori 2015; MacDonald 2015a). Rather, our framing
is limited to: how could blockchain technology impact the economic organization
of banking, and what are the relevant economic models to use in order to think
about this problem?
The rst clear point we sought to highlight was to challenge the otherwise
seemingly compelling notion that blockchain is simply a new ICT-like technology
that will be adopted into banks, thus improving the competitive efciency of banks
that adopt this technology, and harming the competitive position of banks that are
slower to adopt (Chuen 2015). The model for understanding this would be, say,
adoption of other general purpose banking technologies such as debit cards, ATMs
or internet banking. This is a dominant thesis at the time of writing among banks
who view this as a way to improve back-ofce efciency in clearing transactions
(for example consortiums such as Ripple). This, however, may be a mischarac-
terization of the nature of the blockchain technology.
What type of technology is a blockchain? As a new technology of decentral-
ization, blockchains can then be understood to be a new competitor to the central
objects that economics studies: markets. When coupled with token systems,
blockchains seem to describe institutional orders that we might reasonably call an
economy, or following Hayek (1960), a catallaxy. A blockchain is in this sense an
unusual technology in that while manifestly an information and computation
technology (an ICT)viz. a blockchain is a new technology for public databases of
digital informationblockchains are actually better understood as an institutional
or social technology for coordinating people.
What, then, is the margin of competition for blockchains? As a new general
purpose technology, there is a great deal of interest in the way in which existing
rms and industries will adopt and use blockchains. This includes consortium and
private blockchains, where restricted access protocols are used instead of trustless
cryptoeconomic incentives. But the question we have sought to focus on here,
through the lens of transaction cost economics, is not how rms and markets will
adopt and use blockchains, but rather how blockchains will compete with rms and
markets.
By adopting the Coase and Williamson perspective in which rms, markets,
relational contracts, and now also blockchains, are alternative governance institu-
tionswhose relative efciency is determined by micro-institutional transaction
cost considerationswe can understand how blockchains compete with banks,
rather than being viewed as a technology adopted by banks. This is only visible
when we view the basic analytic unit of blockchain economics as the transaction
(i.e., the executable contract). This is the fullest expression of blockchains not as a
new informational and communications technology, but as a new institutional
technology.
Blockchains, as a new institutional technology, are a cryptoeconomic mecha-
nism through which individuals can govern the difculties inherent in transacting.
There is one particular transaction difculty that has long been dealt with through a
hierarchical organization: opportunism. The presence of opportunism in many
288 T.J. MacDonald et al.
We can also examine the ability of individuals to exit their current institutional
environment using blockchains. In this view, what blockchains really do, and what
290 T.J. MacDonald et al.
we argue in this section, is radically reduce institutional exit costs. There are two
main ways blockchains reduce exit costs. The rst is through reducing the tran-
sition costs because of their permissionless nature (Thierer 2014). That is, block-
chains drastically reduce the cost of moving from one institution to another,
especially in relation to state-imposed barriers. The second is through reducing the
opportunity costs because of their non-territorial nature. That is, because block-
chains operate through the non-territorial internet, they enable agents to partially
exit their current institutions. Combining these two cost reductions we conclude that
blockchains signicantly ease individuals institutional exit to the cryptoeconomy.
The transition from one institutional setup to anothersay from banking
organizations within nancial markets to a blockchain-based nancial system
does not occur in costless meta-institutions (Pagano and Vatiero 2015). Quite apart
from the distribution of transaction costs within competing setups, we cannot
theorise a frictionless transitional process between institutions. The process is better
thought of as subject to a kind of meta-institutional transition cost. These are
equivalent to mobility costs in the jurisdictional arbitrage setting.
States (governments) are the main arbiters of such institutional transition costs. If
states intervene in decisions to switch between institutionssay by either inhibiting
with regulation or outright prohibiting the use of blockchain and cryptographic
technologythen exit costs will be higher. This might happen because states
themselves wish to regulate or deter the exit to new institutions, for whatever
reason, or at the behest of vested interests (e.g. banking industry).
By permissionless exit we mean that there is no additional cost on top of the
meta-institutional transition cost such (e.g. a manipulated component; Twight 2004)
as would affect the transition to blockchains at the margin. The strong-form claim
often made is that due to the cryptographic nature of blockchain technology it is
resistant to state intervention and regulation, and is thus permissionless per
denition.
Aside from transition costs, we must also consider how complementary insti-
tutions affect their costs (Pagano and Vatiero 2015). When choosing between
institutional setups one must consider opportunity costs. Only when we think about
opportunity costs does the non-territorial nature of blockchain economies become
important. In territorial systems the opportunity costs relate to the sacrice of
benets of seceding from one geographical location to another.
Blockchain economies are coordinated via the internet, which is fundamentally a
non-territorial space. Individuals need not sacrice the benets of conducting
economic activities in particular locations. They can partially exit from, say, the
banking system of their current locale without having to physically move to the
location or jurisdiction of the banking system they prefer. The opportunity costs of
institutional arbitrage are small, converging on zero. Institutions follow the indi-
vidual, not the other way around. And they do so in a piecemeal or unbundled
fashion. Essentially this is the hyper-realization of globalization achieved through
ICT technology, and further accentuated by blockchain technology.
Cryptographic blockchain technology reduces institutional exit costs through the
permissionless and non-territorial character of the institutional change it engenders.
Blockchains and the Boundaries of Self-organized Economies 291
This depends on two things: (1) blockchain technology is needed to create viable exit
options; while (2) cryptographic technology is needed to keep those exit options
open. First, the viability of exit is dened as the scope of and extent to which
economic activity can be dissociated from legacy institutions and migrated to
blockchain institutions. Clearly exit cannot proceed (permissionless or otherwise)
for those activities for which there are no competing blockchain institutional options
available. Similarly, because blockchain economies are coordinated via the internet
(which is a non-territorial space) exit can be deterritorialized only to the extent that
activity can be migrated to blockchain institutions. Second, the viability of exit
depends on the extent to which cryptographic exit can create a genuine veil of
opacity between transactions and states (e.g. a veil between polity and economy). If
this is the case then exit will be permissionless in the sense that governments cannot
intervene (e.g. neither in the creation of parallel institutions or choice to exit to
them), and non-territorial because state borders will no longer demarcate
transactions.
The upshot of radically reduced institutional exit costs is greater competition; not
between organizations, markets, and institutions within the banking industry, but
between these incumbents and new blockchain based ones. Competition as an
evolutionary, knowledge-generating process is a central idea in both Austrian and
evolutionary economics (Hayek 1948; Vihanto 1992; Wohlgemuth 2008). Thus the
emergence of blockchains has stimulated a kind of meta-intuitional evolution, and
this elicits a knowledge-generating discovery process at the level of orders of
economies. With the advent of blockchains we stand to discover which institution
best governs nancial transactions: markets, rms, or blockchains?
Evolutionary theory tells us that the strength of the variation and selection
mechanismsthat is, the number of parallel experiments and the ease of citizen exit
respectivelydetermine the rate of institutional evolution. Through this lens we
can hypothesise that the mechanism of cryptosecession will intensify discovery
processes by accelerating the rate of intuitional evolution. This is because both the
selection mechanism (exit of people) and the source of variation (entrepreneurial
conjectures) are permissionless and thus heightened. Low switching costs (per-
missionless exit) strengthen the selection mechanism, while low barriers to entry
(permissionless innovation) means a more vibrant source of variation.
Parallel experimentation is a fundamental dynamic efciency scheme to enhance
and accelerate variation, innovation, and evolution (Ellerman 2014). Due to the
non-territorial character of blockchains there can be multiple orders of economies
tested at a timei.e., both legacy banking and new cryptobanking at oncea
laboratory of parallel experimentation par excellence. In much the same way that
territorially decentralized intuitional experimentation is conceptualized as labora-
tory federalism, MacDonald (2015d) describes the theory of the discovery process
292 T.J. MacDonald et al.
6 Conclusion
There are two basic economic lenses through which to view the economics of
blockchain. The rst is to view the economics of the adoption and diffusion of the
blockchain as powerful new ICT technology. Such a technology-based approach is
currently the default perspective in the nance and banking sector, viewing
blockchain as a new technology that will be adopted differentially by some banks,
leading to a further round of technological competition in the banking sector. The
conclusion to this view is to expect the same market process as we have seen with
other technologies: some banks will adapt and prosper, others will lag and collapse.
Their success will depend on their strategic choices and uses of this new technology
to drive productivity and competitive efciency.
But there is also a second economic perspective, focusing not on technology, but
on governance. This view based on economic reasoning, begins by asking what
type of technology is blockchain. The answer to that question, we have argued in
this chapter, is that blockchain is fundamentally a technology of decentralization
and is therefore better understood as a new institutional technology for coordinating
peoplei.e., for making economic transactionswhich then competes with rms
and markets. This path seeks to understand what economic transactions currently
occurring in rms or markets will shift to blockchains.
The new institutional economics and public choice economics of blockchains
emphasize disintermediation and decentralization. In a world of blockchains the
functions and operations of banking may not change, but the economic organization
of banking may shift signicantly. In this view, it is banks that will experience
fundamental shifts in their organizational boundaries, with many transactions cur-
rently governed through hierarchy, relational contracting or market transactions
shifting to the blockchain as an outworking of economic efciency over transaction
costs.
Blockchain is a technology for internal exit from incumbent institutions.
Simultaneously it is a technology for the creation of new institutions. The upshot of
this is emergent economies built on blockchains. This is a political-economic
rupture and bifurcation in which an incumbent institutional order precipitates a
constellaxya constitutionally ordered catallaxy. The relevance of the develop-
ment of blockchains for banking is that it has shifted the boundary between hier-
archical banking organizations and non-territorial, spontaneously ordered,
self-organizing economies. This transition suggests the future of banking will be
conducted in more evolvable and dynamically efcient institutions of governance.
Blockchains and the Boundaries of Self-organized Economies 293
Acknowledgments This chapter draws heavily on, and in part reproduces, material previously
published in Davidson et al. (2016), and also MacDonald (2015a).
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Author Biographies
Mihaela Ulieru
Abstract This concluding chapter offers a book synopsis. Parsing the chapters
which follow the evolution of decentralized platforms from initial attempts at peer
to peer lending and crowdfunding to new market dynamics enabled by blockchain
rooted, smart contract fueled P2P platformswe reveal the ultimate quest in
deploying this social technology for building new economies.
Keywords Synopsis
P2P platforms evolution
Social technology New
economy
Self-organizing communities
Adhocracies
Catallaxies
M. Ulieru ()
Impact Institute for the Digital Economy, Ottawa, Canada, USA
e-mail: mihaela@theimpactinstitute.org
the socio-economic nature and legal challenges brought about by the emergence
and proliferation of P2P platforms. On this basis various alternatives to the cen-
tralized approaches that rule the current nancial sectorwhich lost its legitimacy
in 2008 by not keeping its promises to its customersare exposed.
Pelizzon, Rieder and Tasca in the Chapter Classication of Crowdfunding and
P2P Lending in the Financial System give an overview of the rst P2P platforms
that enabled new market structures to emerge, such as Crowdfunding. If the
emergence of P2P platforms may somehow be related to banks being under stress as
claimed by Blaseng and Koetter in the Chapter Crowdfunding and Bank Stress,
FinTech has continued to provide cost effective platforms as an alternative to
traditional banking. In How Peer to Peer Lending and Crowdfunding drive the
FinTech Revolution in the UK Chisti explains the role of P2P lending and P2P
equity markets as the drivers of the alternative nance revolution which in the UK
is experiencing some of the highest growth rates in the world. Apart from the UK,
P2P technology-enabled platforms are speedily replacing the traditional banking
services also in Asia. In particular, Barberis and Arner in the Chapter From
Shadow Banking to P2P Lending emphasize the regulatory challenges of P2P
lending in China: the country with the largest proliferation of P2P lending platforms
in the world. The authors argue that, due to the recently increased attention received
by the shadow banking sector and the better transparency allowed by its techno-
logical readiness, the Chinese government now has a prime window of opportunity
to regulate non-bank nance in China without impeding economic growth, nor
risking a nancial security meltdown. China would effectively transform its
last-mover advantage in the eld of nancial reform into a rst-mover advantage.
Finally, the authors present their view of data-supported regulation, or RegTech.
The book continues by offering a very exciting and inquisitive incursion into the
new market dynamics brought about by the principles of decentralization and
sharing enabled by (blockchain based) P2P platforms. Although, Courtois in the
Chapter Features or Bugs: The Seven Sins of Current Bitcoin warns against a
number of pitfalls in the current implementation of the rst and largest blockchain
application so far (i.e., Bitcoin), in the Chapter Decentralized Banking: A Return
to Technocracy In the Digital Age, Hayes makes the point that digital currencies
could more securely and cheaply connect the world. The invention of the Block-
chain is opening up the possibility of a different kind of monetary order run by
inviolate mathematics, not a person or committee. Further, Gavin in the Chapter
Trustless computingthe what not the how details how these FinTech innova-
tions provide more functionality than nation state monies, at a lower cost, with
safety and security achieved without armed guards and vaults and guaranteeing
stability through attractive nite issue limits, again dictated by math rather than
being subject to pressures to inflate to escape difcult political choices.
The Chapters authored by Porter and Rousse (Reinventing Money and Lending
for the Digital Age) on crypto currencies and Biggs (The Opportunity for
Non-Banks in Financial Inclusion and Remittance) on mobile money present a
number of narratives about why those FinTech innovations may be empowering for
people, especially in historically poor and nancially underserved communities, as
well as in less developed countries:
Blockchain 2.0 and Beyond: Adhocracies 299
and the corruptible tendencies that exist in society. Unlike traditional representative
models of governance, where systems of checks and balance are exercised through
third parties, under bitcoins consensus model, accountability is distributed directly
and exercised by all in the network. With the blockchains transparency, those who
prefer prot without work will have no place to run and no place to hide. What
emerges in this innovation is a new form of social accountability (Scott 2016). On
this foundation we can envision a city network of informal street vendors running a
collective mutual insurance pool between themselves using only their smartphones
to interact with a distributed ledger system, with no central nancial institution
involved. Or a regional mutual credit systemeffectively a ledger of credits and
debitsimplemented in a decentralized blockchain form (Scott 2016).
To this extent the blockchain becomes a technology for building new economies,
as MacDonald, Allen, and Potts expose in the Chapter Blockchains and the
Boundaries of Self-Organized Economies: Predictions for the Future of Banking.
As the secure, veriable, trustless (i.e. cryptographically secure) mechanism to
record the actions upon the rules the Blockchain becomes a social technology for
whole new institutional forms of economies. More precisely the Blockchain enables
the deployment of emergent temporary catallaxies, aka economies rooted in the
very adhocracies featured in the title, and which we introduced in the beginning
of this concluding Chapter. As a foundation for social order, built on mathematical
truth as veried, rather than political force as threatened, the Blockchain becomes
a source of welfare acquired from releasing the vast captured resources we have
hitherto devoted to articially manufacturing trust into adhocracies that embody a
pure task economy where you nd your people, you make your rules, and you do
your thing.
Pioneering examples of such decentralized collaborative platforms enabling the
deployment of adhocracies include: Backfeed (http://backfeed.cc/)a
Blockchain-enabled reputation based platform aiming to eliminate intermediaries
from peer-to-peer exchanges; Sensorica (http://www.sensorica.co/)a maker plat-
form for collaborative design of specialized high end technical products, which runs
an original Value Accounting System on a Network Resource Planning back-
ground to guarantee that participants are rewarded fairly according to their respective
contributions (Turgeon et al. 2014); and Hylo (https://www.hylo.com/)a
co-creation platform catalysing communities around common intentions to bring the
right skill set and resources to the right project timely.
Future studies are needed to reveal the respective legal frameworks in which these
and other platforms operate (Dawson and Bynghall 2011), as well as the viability of
alternative governance modelscombining regulation by code, smart contracts and
social normsimplemented by these platforms on top of the legal framework, either
as a complement or a supplement to the former. Hypotheses such as those posed by
Bollier et al. (Bollier et al. 2015) regarding the deployment of collaborative entities
that issue blockchain-based sharesor crypto-equity tokensthat give the holders
ownership or membership rights in a type of decentralized cooperative, need to be
tested. How such organizations might end up looking in the real world remains to be
302 M. Ulieru
seen, but they may be an interesting new form to explore in the quest to build social
and solidarity-based nance (Scott 2016).
The ultimate quest concerns the emergence of adhocracies in a catallaxy and
their societal transformative potential, with focus on how the Blockchain tech-
nologies enable implicit trusted exchanges in an open environment. In other words:
How to enable large scale, free and systematic cooperation in a self-organizing
manner that will produce constructive social and economic dynamics? (Ulieru
2014). How can social interactions be aligned with macro-level goals and how
policies steering action towards goal achievement can emerge from such interac-
tions? (Pitt et al. 2012). The answer we hope will contribute to the creation of more
tools that facilitate the governance of online communities, and increase the inno-
vative potential and productivity of commons-based peer-production platforms.
As an infrastructure which provides societys public records repository, a rep-
resentative and participatory legal and governance system, Blockchain technology
has the potential to benet people with privacy, security and freedom of con-
veyance of datawhich clearly ranks up there with life, liberty and the pursuit of
happiness (Roszak 2016).
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Blockchain 2.0 and Beyond: Adhocracies 303
Author Biography
A scalability, 223
Adhocracy, 301, 302 Block, 99
Alternative funding, 20, 44. See also genesis, 146
Crowdfunding size, 128, 286
Anonymity, 101, 239 Blockchain, 98, 298
Attack anonymity, 239
51 % (double spending), 102, 104, 107, auditability, 258
111, 117 Blockchain 2.0, 300
Sybil, 245 escrow service, 274, 275
cyber, 147, 251 Irriversibility (Immutability) of ()
transactions, 259, 268
B killer-app, 283
Balanc3, 268 multi-sign, 274
Bank non-territorial nature, 289, 290
cloud-based, 194 permissions, 245, 258, 263
crypto , 98, 103, 109, 111, 117, 124, 126, permissionless, 244
128, 146, 147, 150, 155, 157, 158, private, 155, 224, 225, 244
165, 175, 191, 224, 239, 241, 242, public, 107, 244
246, 256, 257, 283, 289, 291, 298 settlement, 225, 241, 272
digital models, 93, 147 transparency of () transactions, 141, 260,
innovation, 56 301
stressed , 20, 24, 25, 28, 39, 42, 43
un ed, 148, 173, 176, 177, 181, 182, 185, C
191 Central banks, 122, 123, 149, 151, 215, 260
Biba models, 255 Clark-Wilson Security Policy Model, 252, 253,
Bitcoin, 148155, 157160, 162169, 265
173177, 194 Consensus, 137, 153, 223, 244
applications, 117 longest chain rule, 102, 117
bubble, 162, 163 Practical Byzantine Fault Tolerance
fork, 102, 103, 105, 198, 203 (PBFT), 147
Gold Rush syndrome, 99 Constellaxy, 285, 292
lending, 173 Credit provision
monetary policy, 103 information asymmetry, 20
off-chain () transactions, 245, 249, 258 Crowdfunding, 6
open design principle criticisms, 114 donation-based, 7, 11, 12
payments via, 158 equity based, 11
remittance, 159, 188, 189, 190192 all or nothing, 60
risk, 99, 102, 105, 109, 117, 169 in Germany, 13, 17, 18, 20, 22
in Italy, 13, 22 F
in UK, 13, 5860, 64, 66, 67, 298 Financial
lending-based, 7, 11, 12 disruption, 8
business lending, 55, 61, 63 global (nancial) crisis, 62, 73, 87, 88
consumer lending, 8, 63 inclusion, 181183
secured and unsecured, 61, 81, 154 literacy, 213
regulation, 12, 13, 22, 56, 64 services, 63, 64, 75, 181, 182, 184, 185
ISA, 62, 67 technology, 61, 63
reward based, 7, 11 FinTech, 57, 63, 68
Crypto regulation, 64
nance, 288, 289 in China, 71, 9294
law, 288 in UK, 56, 57, 68, 299
secession, 288, 289, 291 Fraud and nancial crime security, 184
Cryptocurrency, 97, 103, 109, 111, 117.
See also Digital currency H
Cryptography, 99, 114, 115, 147, 148 Hash power, 105109, 111, 112, 117
cryptographers dream, 97 displacement, 111
elliptic curve, 115
kerckhos principle, 114 I
key Intermediaries, 242, 282, 299, 301
private, 242 middleman, 56
public, 242, 249, 254 Internet, 13, 57, 11, 18, 21, 70, 71, 75, 83,
Cryptomoney, 288. See also Digital currency 85, 86, 92, 93, 125, 133137,
141146, 152, 174, 175, 177, 191,
D 194, 198, 216, 221, 222, 230, 233,
Decentralized Autnonomous Organizations 234, 242, 246, 256, 260, 276, 279,
(DAOs), 129, 280, 288. See also 287, 288, 290, 292, 299, 300
Distributed Autonomous nance, 70, 71, 75, 93
Organizations of money, 190, 276, 300
Digital currency, 15, 99, 104, 122, 124129, Web 2.0, 6
137, 160, 182, 188, 229, 300
trifn dilemma, 159 K
Digital innovation, 220, 222, 299 Kiyotaki-Wright (KW) Model, 216, 228233
Digital regulation
Argentina, 148 L
Russia, 148, 185 Legal and Regulation
UK, 13, 62, 67 Asia, 71
USA, 71, 94 compliance, 87, 189, 190
Digital services, 2, 71, 75, 93, 191 Italy, 22
Distributed-Hash Table (DHT), 257, 258 UK, 22
Distributed ledger, 282, 301. See also USA, 71, 75, 7981, 94
Blockchain Lending
peer-to-peer (P2P), 6, 810, 5564, 66,
E 6971, 74, 75, 77, 78, 8184, 86, 92,
Economic models, 284, 297 93, 146, 150, 173177
Austrian economics, 123, 126, 291 social lending, 7
catallaxy, 280, 284
collaborative commons, 5 M
new business applications, 63, 64 Math-based currency, 147, 148, 151, 152, 155,
new institutional economics, 279, 284, 292 156, 158, 159, 166, 173. See also
transaction cost economics. See New Digital Currency
Institutional Economics Mining, 98102, 104, 106109, 111113, 128,
Executable contract. See Smart contracts 152, 168, 197, 198, 223, 225
List of Concepts 307
of non-banks, 181 Venture capital, 11, 12, 18, 28, 38, 64, 65
wisdom of the crowd, 19, 42
Turing-completeness, 246 W
Wallet, 2, 129, 147, 167, 187, 188, 256, 299,
V 300
Virtual currency, 147, 159, 165, 166, 168, 245.
See also Digital Currency
List of Names/Authors Cited in the Book
O S
Olson, M., 219, 283 Sahlman, W., 18
Orphanides, A., 123 Sams, R., 101, 104
Ostrom, E., 285 Samuelson, P., 145
Sandhu, Ravi S., 255
P Sapienza, H.J., 37
Pagano, U., 290 Sargent, T., 145
Paravisini, D., 10 Scharwatt, C., 188
Pattanayak, S., 260 Schmidt, E., 3
Peebles, G., 153 Schwartz, A.A., 7
Peltzman, S., 288 Schwienbacher, A., 6, 18n1, 21
Perry, D., 105106, 106n1, 110 Scott R., Peppet, 87n91
Pessoa, M., 259, 261264 Scott, B., 288, 299, 301302
Peters, G.W., 239n1, 241, 249, 288 Sergey, N., 199, 205n1, 209
Petersen, M.A., 18, 20 Shak, Minouche, 88n100, 89nn101, 102
Philippon, T., 215216 Shubik, M., 228n7
Phillips, A., 121 Sigmund, K., 232
Pierrakis, Y., 11 Smart, N.P., 115
Pilkington, M., 282 Smithin, J., 125
Pitt, J., 302 Sotomayor, M.A.O., 281
Polasik, M., 125 Stalnaker, S., 156n17
Polleit, T., 127 Stanley, Morgan, 74n26
Pope, D.G., 9 Steigerwald, R.S., 271272
Popov, A., 21 Steil, B., 150
Popper, N., 160 Stigler, G.J., 288
Porter, R.D., 146, 158 Stiglitz, J.E., 6, 21
Potts, J., 284 Storey, D.J., 35
Puri, M., 1718, 2021, 25, 39 Streit, M., 218
Strotmann, H., 37
R Sundararajan, A., 8
Rabinovitch, S., 160 Swan, M., 175, 240, 282
Rajan, R.G., 18, 20 Swanson, T., 224, 245
Ratha, D., 186 Sweeting, R., 38
Ravina, E., 9 Swift, C.S., 36
Raviv, A., 35 Sydnor, J.R., 9
Redmond, E., 247 Szabo, Nick, 246
Reid, F., 239n1
Ren, Daniel, 70n4 T
Riding, A.L., 36 Tasca, P., 2, 154, 284
Riedl, Reinhard, 90n104 Taylor, J.B., 123, 127
Rifkin, J., 1 Testoni, M., 1112
Ritter, G., 146 Thierer, A., 289
Robb, A.M., 17, 21, 34 Thomas, Zoe, 94n113
Roberts, J., 215n1 Thorgeirsson, T., 166
Robinson, D.T., 17, 21, 34 Thurik, R., 36
Rochet, J.C., 281 Tirole, J., 281
Rodriquez, C.A., 151n15 Titman, S., 21, 35
Rogers, A., 38 Tiwari, R., 182
Rose, M.H., 6 Tobin, J., 126
Rosenfeld, M., 252 Todd, P., 107
Roszak, M., 302 Touryalai, Halah, 88n98
Roth, A.E., 281 Tracey, B., 215
Rothbard, M.N., 126 Trajtenberg, M., 282
Roxburgh, Charles, 88n100, 89nn101, 102 Triantis, G., 227
List of Names/Authors Cited in the Book 313
A G
Airtel money, 183 George Galloway, 300
AliFinance, 83 Git
ArtistShare, 6 Hub, 223, 225, 227
ASSOB, 12
Auroracoin, 149, 166168 H
HitFin, 273
B Hylo, 301
Backfeed, 301 Hyperledger, 246
Big data, 9, 57, 89, 133, 197, 234
Bitbond, 175 L
BTCJam, 175177 LendingClub, 146, 173, 174
Linux Foundation, 225
C Litecoin, 106, 112, 113, 155
CAMEL, 25, 28, 39, 41, 42
Chain, 300 M
Common Accord, 227 M-Pesa, 148, 183, 185
Consumer nance, 9, 173 M-Shwari, 185
Counterparty, 137, 186, 241, 272 Mt. Gox, 125, 154, 157, 162, 165, 168
Crowdcube, 59
O
D Omni, 137
Digital asset holdings, 273
Dogecoin, 106, 112, 113, 157 P
P2PS, 58
E Panda Firework Gruop, 83
eBay, 135, 222 Prosper, 9
English friendly societies, 7
Enigma, 250, 257259 R
Eris, 246, 247 R3CEV, 225
Ethereum, 115, 137, 245, 246, 268 RateSetter, 57, 59, 61
Ripple, 146
F
Financial Conduct Authority (FCA), 13, 64, 67 S
Fundavlog, 7 Safaricom, 183, 185
Funding Circle, 58, 6163 Security Exchange Commission (SEC), 13, 88