Financial Inclusion

Financial Inclusion and Capability Survey Report
Financial Inclusion Practice
Enhancing Financial
Capability and Inclusion
in Mozambique
A Demand-Side Assessment
August 2014
2013 International Bank for Reconstruction and Development / The World Bank
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Acknowledgements
This Financial Inclusion and Financial Capability Survey Report was prepared by a team led by Siegfried
Zottel1 (Financial Sector Specialist) from the World Banks Financial Inclusion Practice, with contributions
from Claudia Ruiz Ortega (Economist) and Sarah Yan Xu (Research Analyst).
The team is grateful to the peer reviewers of this report - Samuel Munzele Maimbo (Lead Financial Sector
Specialist), Johanna Jaeger (Financial Sector Specialist), and Aidan Coville (Economist) for their valuable
comments. Douglas Pearce (Manager, Financial Inclusion Practice), and Mazen Bouri (Senior Private
Sector Development Specialist) provided overall guidance. In addition, survey preparation support provided
by Tania Saranga (Survey Consultant) and design inputs provided by Sarah Fathallah (Analyst) are
gratefully acknowledged.
The team expresses its deepest appreciation to the Mozambican authorities, including the Banco de
Mozambique (BdM) and the National Statistical Office (INE) for their cooperation and collaboration which
made this project possible. The survey was carried out at the request of the BdM and was implemented in
close collaboration with the BdM. In particular, the team wants to extend its sincere gratitude to the
following officials and experts from BdM who provided invaluable support and strategic guidance
throughout the project: Ms. Dra. Esselina Macome (Member of the Board and Head of the Directorate of
Issuance, Payments and Accounts), Mr. Dias Macuacua (Director, Behavioral Supervision Department),
Ms. Aurora Bila (Director, Payment Systems Department), Mr. Rafael Francisco (Assistant Director,
Payment Systems Department), Mr. Emilio Rungo (Assistant Director, Behavioral Supervision Department),
Mr. Jose Alfredo Lobato Zacarias (Specialist, Behavioral Supervision Department), Ms. Carla Fernandes
(Technician, Payment Systems Department), and Ms. Bordina Muala (Technician, International Relations
Department). The teams sincere appreciation is further extended to the following INE officials and experts
for their collaboration and technical support: Mr. Arao Balate (Director, Population Census Department) and
Carlos Greva (Sampling specialist, Population Census Department).
The team would also like to express its gratitude to tude conomique Conseil (EEC Canada), a Montreal
based survey firm, which was selected to undertake this survey. We are grateful to Fares Khoury, the
president of ECC, as well as all supervisors and enumerators for their efforts and commitments to
successfully complete this survey. Finally, the team owes particular appreciation to all Mozambican women
and men who patiently responded to the survey.
The Survey Report was prepared as part of the Swiss State Secretariat for Economic Affairs (SECO) Trust
Fund on Consumer Protection and Financial Literacy and received complementary funding from the World
Bank Africa Region Vice Presidency.
The corresponding lead author can be contacted at: szottel@worldbank.org
ii
Contents
Preface .......................................................................................................................................................... 1
Key Findings .................................................................................................................................................. 2
Summary of Key Recommendations ............................................................................................................. 3
Executive Summary ....................................................................................................................................... 4
Financial Inclusion ..................................................................................................................................... 4
Recommendations ................................................................................................................................. 4
Financial Capability.................................................................................................................................... 6
Relationship between Financial Inclusion and Capability ......................................................................... 9
Financial Consumer Protection ................................................................................................................ 11
Recommendations ............................................................................................................................... 11
Background on the Mozambique Survey ..................................................................................................... 13
1. Financial Inclusion ................................................................................................................................... 15
1.1
Context ........................................................................................................................................ 15
1.2
Usage of Banks ........................................................................................................................... 17
1.3
Usage of Bank Products .............................................................................................................. 20
1.4
Usage of Nonbank Financial Institutions ...................................................................................... 23
1.5
Usage of Products of Nonbank Financial Institutions ................................................................... 25
1.6
Barriers to Formal Account Ownership ........................................................................................ 26
2. Financial Capability.................................................................................................................................. 28
2.1 Knowledge of Financial Concepts and Products................................................................................ 28
2.1.1 Knowledge of Financial Concepts ............................................................................................... 28
2.1.2 Knowledge of Financial Products ................................................................................................ 35
2.2 Financial Behavior and Attitudes ....................................................................................................... 37
3. Relationship between Financial Inclusion and Financial Capability ......................................................... 43
4. Financial Consumer Protection ................................................................................................................ 48
References .................................................................................................................................................. 53
Appendix...................................................................................................................................................... 55
iii
A.
Background on the Mozambique Survey ......................................................................................... 55
B.
Financial Inclusion ........................................................................................................................... 57
C.
Regression Tables ........................................................................................................................... 59

1.
Financial Inclusion ....................................................................................................................... 59
2.
Financial Capability...................................................................................................................... 69
iv
Figures
Figure 1: Knowledge and usage of commercial banks by location of respondent........................................ 17
Figure 2: Knowledge and usage of commercial banks by income quartile and variability of income ........... 18
Figure 3: Knowledge and usage of commercial banks by degree of media consumption ........................... 19
Figure 4: Media consumption by different sociodemographic groups .......................................................... 19
Figure 5: Bank account penetration in different regions in Mozambique ..................................................... 21
Figure 6: Percentage of Mozambicans currently holding a financial product from a bank by urban status . 21
Figure 7: Percentage of Mozambicans with a bank account by income quintiles ....................................... 22
Figure 8: Percentage of Mozambicans with bank credit by income quintiles .............................................. 22
Figure 9: Percentage of adults in urban areas with a mortgage by income quartiles .................................. 23
Figure 10: Percentage of Mozambicans that have ever used financial institutions ..................................... 24
Figure 11: Percentage of Mozambicans by the number of financial institutions that they have used ......... 24
Figure 12: Usage of financial products in rural and urban areas................................................................. 26
Figure 13: Percentage of Mozambicans with no formal accounts reporting they do not need this product . 26
Figure 14: Reasons for not having a formal account in rural and urban areas ........................................... 27
Figure 15: Distribution of financial literacy scores ....................................................................................... 31
Figure 16: Financial literacy quiz overview ................................................................................................. 32
Figure 17: Education levels of populations with low and high financial literacy scores ............................... 32
Figure 18: Reported awareness & understanding of financial terms ........................................................... 34
Figure 19: Comparison of reported understanding and financial literacy quiz results ................................. 34
Figure 20: Distribution of financial products awareness scores .................................................................. 35
Figure 21: Knowledge of financial products offered by different providers .................................................. 36
Figure 22: Percentage of Mozambicans that know about different providers by number of media used .... 37
Figure 23: Average financial capability scores ............................................................................................ 38
Figure 24: Average budgeting score by education levels in urban and rural areas ..................................... 41
Figure 25: Financial Capability in Choosing Financial Products (Left) and Being Far-sighted (Right) by
Region ......................................................................................................................................................... 41
Figure 26: Average choosing financial products score by media consumed in urban and rural areas ........ 42
Figure 27: Financial products awareness score of Mozambicans with and without formal accounts .......... 44
Figure 28: Usage of financial products by awareness of financial products score ...................................... 44
Figure 29: Financial literacy scores of Mozambicans with and without formal accounts ............................. 45
Figure 30: Usage of financial products by financial literacy score............................................................... 45
Figure 31: Financial behaviors & attitudes of Mozambicans with and without formal accounts .................. 46
Figure 32: Financial behaviors & attitudes of Mozambicans with and without different financial products .. 47
Figure 33: Usage and satisfaction rates for different financial providers ..................................................... 49
Figure 34: Commercial bank satisfaction rates by financial literacy score .................................................. 50
Figure 35: Approaches to deal with financial service provider conflicts ...................................................... 50
Figure 36: Actions taken to redress conflicts with financial service providers ............................................. 51
Figure 37: Reasons for not solving conflicts with financial service providers .............................................. 52
Figure 38: Estimated population break-down by urban/rural ...................................................................... 55

Figure 39: Estimated population break-down by different income groups .................................................. 55
Figure 40: Estimated Population Break-down by Male/Female .................................................................. 55
Figure 41: Estimated population break-down by age groups ...................................................................... 56
Figure 42: Estimated population break-down by education groups ............................................................ 56
Figure 43: Estimated division of stable/unstable income groups ................................................................ 56
Figure 44: Estimated population break-down by household size ................................................................. 56
Figure 45: Account at a formal financial institution across Sub-Saharan African countries ........................ 57
Figure 46: Loan from a financial institution in the last year across Sub-Saharan African countries ........... 58
Tables
Table 1: International comparison of knowledge of basic financial concepts (in % of adults) ..................... 29
Table 2: Cross-country comparison of different financial capability scores ................................................. 39
Table 3: Probability of knowing about commercial banks on demographic and socioeconomic factors ..... 59
Table 4: Probability of having ever used commercial banks on demographic and socioeconomic factors . 60
Table 5: Probability of having ever used commercial bank services on village factors ............................... 61
Table 6: Probability of currently having a bank account on demographic and socioeconomic factors ........ 62
Table 7: Probability of currently having a bank loan on demographic and socioeconomic factors .............. 63
Table 8: Probability of having ever used insurance services on demographic and socioeconomic factors . 64
Table 9: Probability of having ever used MFI services on demographic and socioeconomic factors ......... 65
Table 10: Probability of having ever used money changers on demographic and socioeconomic factors .. 66
Table 11: Probability of having ever used money lenders on demographic and socioeconomic factors ..... 67
Table 12: Probability of having ever had a formal account on demographic and socioeconomic factors ... 68
Table 13: Probability of financial literacy and financial product knowledge scores on village factors ......... 69
Table 14: Probability of financial literacy score on demographic and socioeconomic factors ..................... 70
Table 15: Probability of financial knowledge score on demographic and socioeconomic factors ............... 71
Table 16: Capability of covering unexpected expenses on demographic and socioeconomic factors ........ 72
Table 17: Satisfaction rate on commercial banks on demographic and socioeconomic factors.................. 73
Table 18: Probability of using financial instruments on demographic and socioeconomic factors .............. 74
Table 19: Probability of using financial instruments on financial capability scores ...................................... 75
Boxes
Box 1: The WB Financial Capability Survey in the context of the wider financial sector strategy ................ 16
Box 2: Media Consumption Overview .......................................................................................................... 19
Box 3: Financial Literacy Quiz ..................................................................................................................... 30
vi
Abbreviations and Acronyms

AFI
ASCAs
BdM
CAPI
EA
EEC
MFIs
MFSDS
NBFIs
PCA
PPS
PSUs
RTF
Alliance for Financial Inclusion

Accumulating Savings and Credit Associations
Banco de Mocambique (Bank of Mozambique)
Computer-Assisted Personal Interview
Enumeration Areas
tude conomique Conseil
Microfinance Organizations
Mozambique Financial Sector Strategy
Nonbank Financial Institutions
Principal Component Analysis
Probability Proportional to Size
Primary Sampling Units
Russia Trust Fund for Financial Literacy and Education
vii
Glossary2
Branchless Banking
The delivery of financial services outside conventional bank

branches through the use of retail agents and information and
communications technologies, such as mobile phones, to transmit
transaction details.
Community Savings
Groups
Savings and credit self-help groups such as ASCAs, OPEs,

Xitiques, and Conta Familias.
Financial Capability
The capacity to act in ones best financial interest, given

socioeconomic and environmental conditions. It encompasses
knowledge (literacy), attitudes, skills and behaviors of consumers
with respect to understanding, selecting, and using financial
services, and the ability to access financial services that fit their
needs.
Financial Inclusion
Financial Inclusion is defined as proportion of individuals who use

financial services.
Financial Institution
Any public or private institution whose main function is the provision

of financial services for its customers or members. Probably the
most important financial service provided by financial institutions is
acting as financial intermediaries.
Financial Sector
The totality of financial institutions that operate in Mozambique. This

includes credit institutions and financial companies, as well as
microfinance operators, which are under the supervision of the
Mozambican central Bank (BdM); insurance companies, which are
under the supervision of the Insurance Supervision institute / the
Ministry of Finance; the stock exchange operators, which are under
joint supervision of the BdM and the Mozambican Stock exchange;
and the pension funds.
Financial System
In this report, the definition of financial system is equivalent to the

financial sector.
Formal Financial
Institutions
Financial institutions that are licensed by and prudentially

supervised by the banking authorities in Mozambique, e.g. banks
and licensed non-bank financial institutions.
Informal Financial
Financial institutions that are not registered with or officially
Please note that this glossary is not meant to provide a legal definition of the terms used in this report. Different government
agencies and stakeholders may have specific definitions of the term for the respective purposes of statistical information,
government programs, incentive schemes, etc.
2
viii
Institutions
recognized by any government authority, e.g. unregistered money

lenders.
Key Facts Statement
A summary statement which provides consumers with simple and

standard disclosure of key contractual information of a baking
product or service, contributing to the consumers better
understanding of the product or service. Key Fact Statements also
allow consumers to easily compare offers provided by different
banks before they purchase a banking product or service.
Microfinance
Institutions
Financial institutions that target poor and low-income persons as

their main market niche.
Micro-insurance
Protection of low-income people against specific perils in exchange

for regular monetary payments (premiums) proportionate to the
likelihood and cost of the risk involved.
Money Changers
A money changer is a person who exchanges the coins or currency

of one country for that of another.
Money Lenders
A money lender is an informal lender, either person or a group

which offers small personal loans at rather high interest rates
(agiotas). This category also includes friends, relatives, and
neighbors who offer loans which need to be repaid.
Nonbank Financial
Institution
A Financial Institution that provides financial services without

meeting the legal definition of a bank, i.e. it does not hold a banking
license. Examples are microfinance institutions, insurers, etc.
Teachable Moments
Times in people's lives when they are more likely to be receptive to

new information as they can relate it directly to their own life events.
ix
Preface
Financial capability, as defined by the World Bank and in this report, is the capacity to act in ones
best financial interest, given socioeconomic and environmental conditions. It encompasses
knowledge (literacy), attitudes, skills and behavior of consumers with respect to understanding, selecting,
and using financial services, and the ability to access financial services that fit their needs (World Bank
2013d). In this report, financial inclusion is defined as the proportion of individuals that use financial
services.
Financial capability has become a policy priority for policy makers seeking to promote responsible
financial inclusion and to ensure financial stability and functioning financial markets. Today people
are required to take increasing responsibility for managing a variety of risks over the life cycle. People who
make sound financial decisions and who effectively interact with financial service providers are more likely
to achieve their financial goals, hedge again financial and economic risks, improve their households
welfare, and support economic growth. Boosting financial capability has therefore emerged as a policy
objective that complements governments financial inclusion and consumer protection agendas. To this
end, policy makers are increasingly using surveys as diagnostic tools to identify financial capability areas
that need improvement and vulnerable segments of the population which could be targeted with specific
interventions.
In response to a request of the Banco de Mocambique (BdM), the World Bank has conducted a
financial capability survey. This is a priority follow up to the Mozambique Financial Sector Strategy
(MFSDS) 2013-2022, given i) that financial literacy/capability has been identified by the BdM as a priority
area going forward, ii) the low levels of financial inclusion and the importance of financial capability in
enabling people to take up and benefit from financial products and services, and iii) the lack of
comprehensive, robust, and reliable data which has prevented policy makers so far from formulating
specific policy actions and setting quantifiable and concrete targets.
The key findings and recommendations presented in this report cover 4 main areas: 1. Financial
Inclusion, 2. Financial Capability, 3. Relationship between Financial Inclusion and Capability, and 4.
Financial Consumer Protection. The remaining chapters are structured as follows. Chapter 1 explores the
financial inclusion landscape in Mozambique. Chapter 2 gives an overview of Mozambicans levels of
financial capability, in particular about their financial knowledge, attitudes and behaviors. The relationship
between financial capability and inclusion is discussed in chapter 3. The last chapter investigates if the
products which financially included individuals use are effectively meeting their needs.
Key Findings
Summary of Key Recommendations
Financial
Inclusion
Recommendations
Introduce policies that promote a more
competitive and diverse financial sector
Promote branchless banking
Encourage banks to introduce no-frills savings
and payment accounts with nil or very low
minimum balance
Develop a comprehensive financial education
strategy or action plan, based on the results of
this financial capability survey
Use a wide range of programs, including mass

media, comic books, trusted intermediaries, etc.,
to enhance financial knowledge, and change
attitudes and behavior
Financial
Capability
Financial
Consumer
Protection
Combine
financial
capability
enhancing
interventions with other interventions, such as
text message reminders, to increase its
effectiveness
Combine financial capability-enhancing programs
with available financial products, which most
people can access, to promote beneficial
participations in the financial markets
Share this survey results with financial
institutions to help them develop tailored
products to the needs of underserved population
Require Key Fact Statements for financial
products and test consumer understanding of
disclosure material
Require financial institutions to disclose in all precontractual and contractual disclosure formats
detailed information on the internal as well as
relevant external dispute resolution mechanisms
Analyze data on consumer complaints submitted
by financial institutions periodically and use this
information as input to supervisory and
regulatory activities
Responsible
BdM
Term3
MT
BdM
BdM
MT
MT
BdM, Ministry of Finance,

Ministry of Education, industry
associations, consumer
associations, and other
stakeholders
stakeholders
stakeholders
BdM, industry associations,
market participants
MT
BdM
ST
BdM
ST
BdM
ST
BdM
MT
ST, short term, indicates action can be undertaken in 0-6 months. MT, medium term, indicates 6 months-1 year. LT, long term,
indicates 1+ years
3
MT
MT
MT
Executive Summary
Financial Inclusion
The financial system in Mozambique is heavily dominated by banks, but only 52 percent of
adults have ever used their products. The problem of lack of access to basic financial services is
far more pronounced in rural areas where 42 percent of the population has ever used bank products
as compared to 73 percent in urban locations. Within urban and rural communities, the data
suggests that the development level of the area matters. As compared to areas with lower
development and infrastructure levels, people are more likely to use bank services in areas with
shorter distances to bank branches and better infrastructure. Other financially excluded segments
are people living on low and fluctuating incomes.
The survey data further suggests that around a third of the population is not being reached
by any financial service providers and that a substantial overlap exists on the type of clients
targeted by banks and other providers, including MFIs. As with banks, clients of money
changers and insurance companies are concentrated at the highest income segment. In contrast,
MFI clients are not from the lowest income segment, and it is more likely for Mozambican
respondents above the median income to have used MFIs than for those below it. Only money
lender clients seem to be more likely to be less educated and from a less favorable background.
Among the financially included segments, bank accounts are the most common products. On
average, 46 percent of urban residents currently own a bank account, as compared to 19 percent of
rural dwellers. Usage of money transfer services, credit, both from formal4 and informal providers,
and insurance products is not very common. More sophisticated savings products such as
investments in stocks or private pensions are hardly used at all.
Important barriers to account ownership are lack of money, affordability and lack of financial
knowledge of financial products and services. One out of five of those without an account who
live in rural areas report that they cannot afford it. Although this number is lower for urban
populations, it is still the second most important reason for not having an account. Findings from the
survey also suggest that lack of trust and financial knowledge of financial products hinders 19 and 26
percent of urban and rural Mozambican respondents without accounts from using basic financial
services.
Recommendations
In order to close the identified gap between urban and rural populations in accessing financial
services, it is recommended to harness the potential of branchless banking. Mobile or agent banking
can dramatically reduce the costs of delivering financial services outside larger urban centers, in particular
4
This number includes credit from banks and MFIs.
in low-density and remote areas with prohibitively high costs of establishing traditional branch networks.
Policies facilitating the introduction of these lower-cost technologies, such as the development of a legal
framework, can help reach remote locations and rural populations that were previously excluded from
financial services.
Furthermore, the introduction of basic bank accounts could become an entrance door to the formal
financial system to underserved parts of the population identified through this survey. It is
suggested to encourage banks to introduce no-frills savings and payment accounts with nil or very low
minimum balance because they can enable low income segments to transfer money and to store it at a
safe place (World Bank, 2013a). However, international experience in countries such as India, the
Philippines, or South Africa shows that policies related to the introduction of such products need to be
complemented with public awareness campaigns, otherwise the uptake of these products might be very
low.
Advancing financial inclusion levels in Mozambique will also require a more competitive and
diverse financial sector to make products affordable to larger parts of the population. In
Mozambique, not only the financial sector is heavily concentrated in banks, but also, within the banking
sector the three largest banks account for 85 percent of the sectors assets (Mozambique Council of
Ministers, 2013), suggesting low competition in the sector. In line with Mozambiques Financial Sector
Development Strategy (MFSDS) and with the findings of recent research (e.g. Love and Martinez Peria,
2012), introducing policies that promote competition could encourage lower prices and make products
affordable for broader segments of the population. The substantial overlap of clients targeted by banks and
other providers further indicate the need to support the development, formalization and expansion of
Nonbank financial institutions providing microfinance and micro-insurance services to lower income
segments and rural populations.
Financial Capability
Survey results highlight that financial knowledge and awareness levels of basic financial
concepts and products are a significant challenge in Mozambique, as well as in many
countries across different income levels. Mozambican respondents demonstrate relatively high
comfort levels in solving simple numeracy tasks, compared to respondents from economies with
different income levels. However, only 28 percent of Mozambican respondents have good
understanding of compound interest and inflation, which appears to be low from a cross-country
perspective. Likewise, awareness of financial products other than those provided by banks, MFIs,
and money lenders appears to be limited.
Respondents who are the least familiar with financial products tend to live in rural areas and
on low and irregular income streams. The need to manage low and uncertain income streams is a
strong predictor of low awareness of financial products, in particular with insurance products which
would allow them to deal with bad events when they occur. Policies targeting Mozambicans with
fluctuating income may need to be of first order since 72 percent of adults in Mozambique report
having a volatile income.
An international comparison shows that Mozambican respondents are especially competent
in managing day-to-day finances, but are among the most challenged in terms of putting
money aside for future expenses and choosing appropriate financial products. While
Mozambicans demonstrate strengths in budgeting and monitoring their expenses, compared to
respondents from 9 other countries, they display relatively weaker performance in saving, putting
money aside for unexpected and old age expenses, and in particular in choosing appropriate
financial products. These results are of concern given their implications for peoples ability to smooth
consumption, to cope with economic shocks, to generate lump sums for productive investments, to
take advantage of available financial products, and ultimately for their long term wellbeing.
Despite being especially capable in a number of financial capability areas, rural dwellers and
people living on low and fluctuating incomes struggle in particular with setting aside funds
for unexpected expenses. As compared to higher income segments, the ability of low income
populations to cope with unexpected shocks seems to be limited by their scarce resources. Similarly,
people living with fluctuating incomes and rural residents have more difficulties with setting aside
funds for unexpected expenses than their respective counterpart groups. As compared to urban
populations and people with stable incomes, rural dwellers and those with varying incomes also
struggle more with budgeting, choosing financial products, and they tend to think less about the
future. Consequently, daily hardship and the constant struggle with solving immediate problems
seem to draw their attention away from their longer-term needs.
Recommendations
It is suggested that a comprehensive financial education strategy or action plan be developed
based on the results of the financial capability survey. The survey identified numerous financial
6
capability issues across various segments of the population. Further, the report suggests a number of
policy actions which could be undertaken to improve financial capabilities. In order to ensure that scarce
resources are used in the most efficient way, prioritization of certain financial capability enhancing
programs is essential. The development of a financial education strategy or action plan could help to
identify key priorities. Such priorities could be based on a number of criteria, including i) the need, ii)
desired and expected impacts, iii) costs, iv) opportunities to scale up and v) leverage on existing programs.
Both, the development of a strategy or action plan and the setting of priorities would require a wide
consultation process which includes various stakeholders from public, private and non-profit entities. This
could help to facilitate a wider consensus building about the importance of this topic and to achieve better
coordination of all stakeholders and available resources towards boosted financial capabilities in
Mozambique.
In light of overall low product awareness levels, mass media campaigns that provide information
about key features of financial products may be an effective means to increase beneficial use of
financial products. The survey results suggest that effective channels to reach populations who are the
least familiar with financial products would be mobile phones, TV, or radio (see Box 1). Awareness
campaigns can also be used to disseminate the introduction of more sophisticated products among
Mozambicans. For instance, pension products to adults not covered by public pension plans, or longer
saving products, such as investments in funds or bonds, which would benefit the development of long term
finance, such as housing finance, in Mozambique.
Innovative and interactive measures, and edutainment in particular, should be considered to reach
the adult target audience and to ensure that increased financial awareness translates into actions.
The scientific field of behavioral economics has documented a plethora of behavioral biases which can
prevent people from translating their knowledge into action. For instance, people tend to be biased towards
the status quo and to choose the default option. They may also suffer from self-control issues,
procrastination, overconfidence, or systematically underestimate the time to complete tasks (Buehler et al
2002). Recent research has shown that innovation on delivery matters. Conveying financial messages
through innovative ways such as using popular TV soap operas, films, videos or radio programs can be
quite effective, not only in improving financial knowledge but also in altering savings and borrowing
behavior (Berg and Zia 2013, Coville et al 2014). Edutainment programs are also presumed to be more
effective if messages are delivered in an engaging and entertaining manner through appealing stories that
stick to memories, and if they are repeated and reinforced over time. For instance, in Kenya, a popular
television drama, Makutano Junction, incorporated financial education messages into some of its stories.
These messages aim to encourage people to save regularly or to open a bank account, rather than to keep
money under a mattress. Other examples of the use of entertainment education for finance are Scandal! in
South Africa or Mucho Corazon in Mexico. As with other soap operas, people watch these edutainment
dramas because they identify with the characters and enjoy the stories; but in the course of watching the
shows, they benefit from the financial capability enhancing messages.
Publications can also be a useful means of conveying financial capability enhancing messages,
since each copy can be read by several people and can be retained for future reference. A diverse
range of publications can be used, including leaflets, booklets, fliers and posters. Articles in newspapers
and magazines are also important tools, especially if contained within general sections of the newspaper or
magazine, rather than in specialist financial ones. Comic books have been found to be particularly effective
in several countries, such as Kenya, India, and South Africa, where literacy levels are also low. In such
cases comic books effectively facilitate discussion within the family on topics related to financial literacy.
Furthermore, financial education can be effectively delivered through trusted organizations and
individuals with whom the target audience deals with on a regular (day-to-day) basis. Managing
one's personal finances is an important aspect of everyday living. Many organizations have an interest in
helping people to become financially knowledgeable and capable. Especially to reach remote communities
in rural areas, and groups that are hard to engage, it could be considered to collaborate with community
organizations and trusted intermediaries such as community leaders, social workers, and to support them
with resources, training or funding, if necessary.
A promising way to increase the effectiveness of financial capability enhancing programs is to
combine it with other interventions, such as the use of reminders. Rigorous impact assessments in
Boliva, Peru, and the Philippines provide evidence that coupling a financial capability enhancing
intervention with reminders via text messages is a promising way to address some behavioral biases and to
induce behavioral change (Karlan et al 2010). Since Mozambicans appear to struggle with long-term
financial decision making, periodic reminder messages could induce them to attend to the benefits and
tasks of saving regularly and putting money aside for unexpected and old expenses. These interventions
are also quite cost-effective and could be taken rapidly to national scale.
The delivery of financial capability enhancing programs should further take advantage of teachable
moments. Research shows that financial education works best when delivered to adults during teachable
moments (Yoko et al 2012). Teachable moments are times in people's lives when they are more likely to be
receptive to new information as they can relate it directly to their own life events. In terms of financial
education, key teachable moments when one may re-examine his/her personal finances include marriage,
new employment, and the launch of a new business.
Relationship between Financial Inclusion

and Capability
While Mozambican respondents who do not participate in financial markets are less aware of
the services of financial institutions, their knowledge of financial concepts is comparable to
those actively using financial products. On the one hand, this result suggests that a substantial
fraction of Mozambicans that is not being reached by financial products, nevertheless has a similar
understanding of financial concepts as respondents with established relations with financial
institutions. On the other hand, it suggests that both financially excluded Mozambicans as well as
those who are included deserve policy attention. A high number of Mozambicans who are financially
active, lack basic knowledge and skills to make sound financial decisions.
The likelihood of a less financially literate Mozambican using formal savings or credit is very
similar to the likelihood of a person with better understanding of financial concepts. However,
lack of knowledge of basic concepts does relate to usage of informal finance and savings.
Individuals with low financial literacy are more likely to use informal savings and informal credit than
individuals with higher financial literacy. Similarly, as respondents increase their awareness of
financial products they rely more on formal financial institutions.
Financial behaviors and attitudes are not notably different between those with and without a
formal account, but when comparing the financial capability scores of users of various
products, differences are more pronounced. Credit users, especially from informal sources, are
more likely to overspend, and less likely to live within their means than the average respondent.
Those who save on the other hand, regardless of whether they save formally or not, are more
disciplined in spending their money.
Recommendations
In order to enable financially included Mozambicans to benefit from the products they use, financial
knowledge and capability-enhancing programs could be combined with available financial products
most people can access. Financial education programs could be tied to existing formal accounts most
people can access and use such as at the time when they open an account or take out a loan. These
programs should not only help to close existing gaps in their customers understanding of financial
concepts but inform about the need to build up savings cushions for unexpected financial shocks and old
age expenses. However, it must be ensured that any educational materials are truly informative, clear,
impartial, and most importantly free from marketing.
BdM may consider sharing the results of this survey widely with different financial service
providers, but in particular with banks and MFIs to potentially develop products tailored to the
needs of underserved segments of the population. Since savers are more likely to control their
9
spending than non-savers, it could make good business sense for financial service providers to develop
products which meet the needs of underserved populations and help them to reach personal savings goals.
For example, savings products have design features that affect the extent of peoples use of the product,
such as commitment savings account or labeled accounts. The former consists of accounts where a certain
amount of funds is deposited and access to cash is relinquished for a period of time or until a goal has
been achieved. The latter describes accounts created with explicit savings goals, such as the
establishment or expansion of a business, a car purchase, housing, or education (World Bank 2013a).
10
Financial Consumer Protection

The survey results suggest that financially illiterate respondents are more vulnerable to
encounter a conflict and to purchase and being sold products that do not meet their needs.
Respondents who struggle to understand basic financial concepts seem to be less satisfied with
bank products as compared to those with better understanding, suggesting the need for basic
protective measures to ensure that they obtain the information they need to adequately understand
the products they use. In addition, they also seem to be more vulnerable to experiencing a financial
service provider conflict.
Another interesting finding in the area of financial consumer protection is that consumers of
financial services do not widely report complaints or other type of conflicts with providers,
nor do they try to solve conflicts they encounter. Only 13 percent of the surveyed respondents
state that they experienced a conflict with a financial service provider in the past 3 years. Less than
half of those who encountered a dispute took action to try to solve it. Only 40 percent of those who
did not experience a conflict indicated that if they faced a conflict they would try to resolve the
disputes.
Regarding the actions taken to seek redress, redress systems such as BdMs team in charge
of consumer complaints handling or legal courts were not sought at all by those who
experienced a dispute. That courts were not considered at all can most likely be explained by
perceived high costs and lengthy time of proceedings. That consumers do not turn to the BdM may
be due to the fact that financial services contracts typically do not specify what a consumer should
do in the event that he or she has a complaint, and the possibility of recourse to the BdM. Lack of
trust or lack of awareness of which government authorities can be approached in the event of a
dispute are also the most frequently cited reasons for not trying to solve a conflict.
Recommendations
These findings highlight that delivering financial education is not sufficient and needs to be
complemented with measures to strengthen the financial consumer protection framework, such as
regulations in the area of consumer disclosure. It needs to be ensured that consumers are provided
with sufficient information to allow them to select financial products that are the most affordable and
suitable. Therefore, in line with the recommendations of the 2012 Diagnostic Review of Consumer
Protection and Financial Literacy 5 (CPFL), financial institutions should be required to provide a
standardized key fact statement that explains in plain language the key terms and conditions for each
product. It would be beneficial to undertake consumer testing of key fact statements in order to ensure that
The recommendations highlighted in this report on financial consumer protection are important in the context of this survey. It
should be noted that for strengthening the overall financial consumer protection framework additional measures which are
detailed in the CPFL review play an important role. The review is available at: http://responsiblefinance.worldbank.org/diagnosticreviews.
5
11
the presented information is properly understood by consumers and that the format covers all necessary
information. In addition, it is suggested that BdM uses a variety of channels to provide consumers with
comparable information on costs and terms of similar products, including internet, newspapers, community
leaders, and consumer associations (World Bank 2013c).
Financial institutions should also be required to inform their customers about their right to
complain and about their complaints handling procedures. Legal or regulatory provisions should
require financial institutions to provide customers with information on internal complaints handling
procedures. This information should not only be disclosed in their products terms and conditions but also
be visibly posted in branches and online. In addition, consumers should also be informed about formal
redress systems such as BdM or legal courts.
BdM should analyze consumer complaints statistics submitted by financial service providers and
use this information as inputs to their supervisory and regulatory activities. All financial institutions
should be obliged to share their complaints data with BdM. Based on the analysis of the consumer
complaints and inquiries, BdM could propose guidelines, instructions or conduct awareness campaigns that
address the main problems identified in such analysis.
12
Background on the Mozambique Survey

The financial capability questionnaire used for this survey has been extensively tested in the
context of low- and middle income countries. The survey instrument used is based on a questionnaire
developed with support by the Russia Financial Literacy and Education Trust Fund (RTF) and is
tailored to measure financial capability in low and middle income countries, although it can also be used
in high income countries. Extensive qualitative research techniques were used to develop this survey
instrument, including about 70 focus groups and more than 200 cognitive interviews in eight countries to
identify the concepts that are relevant in low- and middle-income settings, and to test and adapt the
questions to ensure that they are well understood and meaningful across income and education levels. The
instrument is currently used or planned to be used in 14 countries in Latin America, Africa, Middle East and
East Asia and the Pacific.
The survey instrument used allows financial capability, financial inclusion, and consumer
protection issues to be assessed and measured. Financial capability is measured by knowledge of
financial concepts and products, and by attitudes, skills and behavior related to day-to-day money
management, planning for the future, choosing financial products and staying informed. In order to jointly
analyze financial capability and inclusion, the survey instrument captures information on usage of different
kind of financial products and providers. The financial consumer protection section gathers information on
incidence of conflicts with financial service providers and levels of satisfaction with financial products
offered by different financial institutions. The survey instrument has been further customized to the policy
priorities of BdM, through adding specific questions, for example relating to usage of money lenders and
levels of satisfaction with products they provide.
The Mozambique survey is nationally representative of the financially active population and
comprises a total sample of 3,000 adults6. To fulfill the requirement of a scientifically sound survey which
allows inferences to the whole universe of financially active adults in Mozambique who are either
responsible for personal or household finances, probability sampling techniques were used to select a
sample of 3,000 adults. Thereby, the most recent 2007 Mozambique Census of Population and Housing,
kindly provided by the national statistical office (INE), was used as a sampling frame. The population was
divided into 21 strata: 11 regions (Niassa, Cabo Delgado, Nampula, Zambezia, Tete, Manica, Sofala,
Inhambane, Gaza, Maputo Provincia, and Maputo Cidade) and each region, except Maputo Cidade, was
further divided into urban and rural strata.
The sample was selected through a three stage cluster sampling. The primary sampling units (PSUs)
selected at the first stage were enumeration areas (EA) delineated for the 2007 Mozambique census which
were selected with probability proportional to size (PPS). The measure of size for each EA was based on
the number of households in the sampling frame. Following the first stage selection of EAs, a household
6
Population aged 18 and older
13
listing was conducted in the chosen EAs. In each selected PSU, a sample of 20 households was selected
from this list at the second stage, out of which 15 were targeted for surveying and 5 were reserve
households for replacement purpose only. Finally, within each selected household, eligible adults either
responsible for personal or household finances were randomly drawn by means of the Kish grid. Proper
individual weights were calculated and used in the following analysis to adjust for varying probabilities of
selection (design weights).7
Between August and December 2013, a Canadian survey firm implemented the survey using
computer-assisted personal interview methods (CAPI). tude conomique Conseil (EEC) Canada, a
Montreal based survey firm, was hired to conduct the Financial Capability Survey in Mozambique. To
ensure highest data quality and avoid common errors associated with paper-and-pencil surveys, an
electronic version of the questionnaire including consistency checks were programmed and the survey was
administered from tablet computers. Due to extensive efforts and different strategies used (e.g. training of
enumerators on refusal conversion strategies, letters which were sent in advance to inform respondents
about the surveys objectives, 5 contact attempts, etc.) the total non-response rate was less than 9 percent
of the total targeted households.
The adult population to which the results of this survey are meant to extrapolate has the following
key characteristics: A large majority of the population (69 percent) live in rural areas, while the remaining
31 percent live in urban environments (see figure 38,). Slightly more than half of the population are women
(51 percent, see figure 40). Ranking all individuals by their reported household income and dividing them
into 4 groups, a third fall in the lowest income segment (less than 4500 MZN per month), 26 percent in the
second lowest (between 4501 MZN and 6000 MZN), 24 percent in the second highest (between 6001 MZN
and 9000 MZN), and 18 percent in the highest income group (more than 9000 MZN, see figure 39). Around
42 percent of the population is younger than 35, 46 percent ages from 35 to 55, and 12 percent of the
population is older than 55 (see figure 41). In terms of the education attained, 10 percent of the population
has tertiary education; 33 percent has some or completed secondary schooling, which includes lower and
higher secondary degrees; 25 percent has completed primary schooling, while 32 percent has no schooling
(see figure 42). Only 29 percent of the population is characterized as earning stable income, while the
remaining 71 percent is facing irregular and uncertain income flows (see figure 43). The average number of
adults per household is 4, whereas an average sized household comprises 6 people. As shown figure 44 in
Appendix A, 59 percent of the respondents live in households with 4 to 6 members, around a quarter in
households comprising 7 or more members.
A sampling note is available upon request which entails detailed information about the sampling approach and the computation
of weights which have been used in the subsequent analysis.
7
14
1. Financial Inclusion
1.1 Context
Over the past two decades, Mozambique has been successfully implementing a series of reforms to
its financial system which substantially improved the sectors stability and depth. One of the most
relevant ones has been the privatization of the financial sector. Starting in 2003, the role of private banks
has gradually been increasing, currently representing about 95 percent of the total financial system assets
(Mozambique Council of Ministers, 2013). Notable financial sector reforms that have been implemented
range from regulation regarding the operation of the financial system to the establishment of units in BdM to
increase supervision and transparency in the sector. These reforms, together with stable macroeconomic
conditions, have resulted in increased financial sectors assets and a steady decline in the fraction of nonperforming loans of the system. However, financial sector growth does not necessarily translate in more
financial inclusion. If there are barriers preventing financial products to reach groups of certain
demographics, there might be scope for policy makers to work on this area.
Compared to sixteen countries of Sub-Saharan Africa, Mozambique ranks fourth in the fraction of
adults with an account at a formal financial institution8. According to 2011 Global Findex data, only in
Mauritius, South Africa and Kenya more adults have access to these accounts. The Global Findex
database further indicates that in Mozambique, Zimbabwe and Angola, on average 40 percent of adults
report having an account at a formal financial institution. However, the gap between female and male
access to formal accounts is wider in Mozambique than in Angola or Zimbabwe 9 . A similar pattern is
observed in access to formal accounts by income distribution. In Mozambique, the difference in access
between adults at the top 60 percent of the income distribution and those at the bottom is higher than in
Angola or Zimbabwe (see figure 45 in Appendix).
In terms of access to credit, 6 percent of adults in Mozambique report having a loan from a financial
institution in the past year. While the gap between genders is not large (1 percentage point), the gap
between adults at the top and the bottom of the income distribution is one of the widest of the region. 8.8
percent of the wealthiest adults have a formal loan, compared to only 1.8 percent of the poorest having
one. Only in Kenya and Mauritius this gap is wider (see figure 46 in Appendix).
In this report, financial inclusion is defined as the proportion of individuals that use financial
services. As stated in the Global Financial Development Report 2014 (World Bank, 2013a), lack of usage
of financial products does not necessarily mean lack of access. While some people may have access to
financial services at affordable prices and may decide not to use them, others may lack access because of
This indicator from the Global Findex database includes accounts at a bank, credit union, cooperative, post office, or MFI.
Mozambique, there is a 10 percentage point gap between female and male adults in access to formal accounts. 45 percent of
male adults have a formal account, while only 35.5 percent of females do. In Zimbabwe and Angola the gap between male and
female adults is of 5 and 1 percentage points respectively.
8
9In
15
constraints such as excessively high costs, or unavailability of the services due to regulatory barriers or
other factors. This chapter explores access to finance and the financial inclusion landscape in
Mozambique, acknowledging that financial inclusion and access to finance are different issues. See Box 1
on how the results of this survey link to the wider financial sector strategy.
Box 1: The WB Financial Capability Survey in the context of the wider financial sector strategy
Following a broad and inclusive preparation process, the Council of Ministers approved in
April 2013 the Mozambique Financial Sector Development Strategy (MFSDS) for 2013-2022.
The objective of the MFSDS is to promote the development of a sound, diverse, competitive, and
inclusive financial sector which provides citizens and businesses with convenient access to a range
of appropriate and high quality financial services at affordable prices. In order to increase financial
inclusion, the government has also included an emphasis on financial literacy and consumer
protection in the MFSDS. In particular, the MFSDS includes: i) rapidly expanding financial literacy for
all types of financial services to increase the publics understanding of how financial services can
improve livelihoods, and its ability to access financial services; ii) putting in place a consumer
protection framework both to protect consumers and to encourage new consumers to enter the
market.
In addition to the MFSDS, BdMs financial inclusion commitment to the Alliance for Financial
Inclusion (AFI) set out a substantial reform agenda for financial inclusion, as well as for
financial literacy and consumer protection. The BdMs commitment made at the AFI meetings in
Cape Town on September 28, 2012, was to a Financial Inclusion Strategy (or action plan) that would
cover financial inclusion, financial stability, financial literacy and consumer protection, and financial
inclusion indicators.
As an initial follow up to the MFSDS a diagnostic review of Consumer Protection and
Financial Literacy has been conducted in 2013. The review provides a detailed assessment of the
institutional, legal and regulatory framework for consumer protection in two segments of the financial
sector in Mozambique: banking and non-bank credit institutions. The review was undertaken in
response to a request received for WB technical assistance in the field of financial consumer
protection made by BdM in November 2011.
The WB Financial Capability Survey is a further priority follow up to the MFSDS, given i) that
financial literacy/capability and improving financial access has been identified by the BdM as a
priority area going forward, ii) the low levels of financial inclusion and the importance of financial
capability in enabling people to take up and benefit from financial products and services, and iii) the
lack of comprehensive, robust, and reliable data which has prevented policy makers so far from
formulating specific policy actions and setting quantifiable and concrete targets.
16
1.2 Usage of Banks

While banks dominate the financial sector in Mozambique, bank penetration is by no means
homogeneous across the country, with rural populations in particular being excluded from bank
services. Access to banks services has substantially improved over the last years, both in geographical
and in demographical terms. In geographical terms, access to bank services improved from an average of
2.9 bank branches per 10,000 km2 in 2005 to 6.6 in 2012. Likewise, in 2012 Mozambique had on average
4.1 bank branches per 100,000 adults, as compared to the year 2005, when the country average was 2.2
branches of banks per 100,000 adults. However, the most significant improvement was registered in urban
areas (BdM, 2013). In rural areas the problem of financial access is far more acute with an average of only
0.6 bank branches per 100,000 adults (Mozambique Council of Ministers, 2013). In a predominantly rural
country, this gap is substantial. These disparities are reflected in the location of adults who know and use
bank products. As figure 1 indicates, 74 percent of adults in Mozambique are familiar with the products
offered by banks but only 52 percent of them report ever having used them. When examining regional
patterns, people from urban areas are more likely to know and use bank products. Regression analysis
(see tables 3 and 4) show that even after controlling for other socioeconomic and demographic factors,
living in an urban neighborhood is strongly correlated with both the knowledge of these institutions and the
usage of their products. Within rural and urban communities, the data suggests that differences in
economic development of the area matters to explain the likelihood of using bank products. Holding
constant the urban status of a neighborhood, people are more likely to use bank services in areas with
shorter distances to MFIs branches and with better infrastructure (see table 5).
Figure 1: Knowledge and usage of commercial banks by location of respondent
Source: WB Financial Capability Survey, Mozambique 2013

Regarding usage of bank products, income is another characteristic that strongly predicts who
uses these financial institutions, even after controlling for a set of demographic and socioeconomic
factors (see table 4). As shown in figure 2, bank customers are more likely to be high and medium income.
17
Importantly, of all respondents with a fluctuating income, only 44 percent of them report having ever used
banks. This result suggests there may be scope to provide some type of financial product to protect
Mozambicans against income fluctuations and allow them to better smooth their consumption and plan their
investments, especially since 72 percent of adults in Mozambique report having a volatile income.
Figure 2: Knowledge and usage of commercial banks by income quartile and variability of income

Mozambicans who use print, broadcast or internet media at a regular basis are also more likely to
know and use bank products. According to regression analysis (see tables 3 and 4), even after holding
income and other characteristics constant, more active media consumers are substantially more likely to
know and have ever used bank services. Figure 3 presents the relation between usage and knowledge of
bank products with an index of media consumption, defined as the number of media elements frequently
used by respondents 10 . As seen in figure 3, knowledge about commercial banks and their use
monotonically increases as individuals rely on more media elements. Interestingly, the relation between the
media index and the fraction of people that have ever used banks is steeper than the relation of the index
with the proportion of Mozambicans who know about bank services. Of all Mozambican respondents who
do not use any kind of media element, while 56 percent of them know about bank services, only 25 percent
have ever used banks. On the other extreme, 94 percent of the most active media users know and have
ever used bank services. This pattern suggests that Mozambicans who are more likely to use media are
not only more informed and literate Mozambicans, but also, with more means to obtain bank products.
The types of media that respondents were asked about were newspapers (national and local), radio, TV, the internet, and
mobile phones.
10
18
Figure 3: Knowledge and usage of commercial banks by degree of media consumption11
Source: WB Financial Capability Survey, Mozambique 2013.

Box 2: Media Consumption Overview
While mobile phones, TV and radio are widely used in Mozambique, the penetration of print
media and internet is biased towards more affluent, urban and highly educated segments of
the population. Figure 4 reveals that even those at the bottom of the pyramid widely use TV and
mobile phones. For instance, compared to 70 percent of urban dwellers, 58 percent of rural residents
regularly watch TV. Mobile phones are even more popular, with penetration rates of 69 percent in
rural areas as compared to 76 percent in urban areas. Similar differences in mobile phone usage
can be observed between lowest and highest income earners and people with lowest and those with
highest educational attainment. Print media and internet show most variation across different
segments of the population and are hardly used at all by those with low educational attainment, rural
dwellers, and people living on low and fluctuating incomes.
Figure 4: Media consumption by different sociodemographic groups
11
Media consumption index refers to the number of media sources regularly used by respondents.
19

Media consumption index refers to the number of media sources regularly used by respondents.
1.3 Usage of Bank Products

Among the range of products and services banks offer in Mozambique, the most commonly used
products are bank accounts, followed by loans. As seen in figure 6, substantial disparities in the usage
of bank products arise between urban and rural areas. In urban areas, 46 percent of Mozambicans
currently have a deposit, saving or checking account with a bank, whereas in rural areas, this percentage
drops to 19 percent. Despite this gap between urban and rural populations, figure 5 reveals notable
regional differences in bank account usage. While the account penetration in southern provinces of
Maputo, Gaza, and Inhambane averages 56 percent, only 21 percent of adults living in the northern
provinces of Nampula, Niassa, and Capo Delgado have a bank account. The lowest account penetration is
found in the central provinces of Sofala, Manica, Tete, and Zambezia, where only 16 percent of the
population has an account with a bank. Disparities in the fraction of Mozambicans using bank loans can
also be observed between urban and rural living environments. Only about 15 percent of adults in urban
areas currently have a loan with a bank, compared to 7 percent in rural areas.
20
Figure 5: Bank account penetration in different regions in Mozambique

Figure 6: Percentage of Mozambicans currently holding a financial product from a bank by urban
status

Regression analysis suggests that Mozambican respondents are substantially more likely to have
bank accounts and bank loans at higher levels of income, even after controlling for community
characteristics such as urban status, and other socio-demographic factors (see tables 6 and 7). As figures
7 and 8 show, both in urban and rural places, the use of bank accounts and credit loans is concentrated
among the group of Mozambicans at the wealthiest income levels, particularly from urban areas. The
regression analysis on the probability of having a bank account suggests that the development and
infrastructure level of the community helps explain where bank accounts are concentrated. People are
more likely to use bank services in areas with shorter distances to bank branches and with better water
21
supply. While more developed communities also have the expected positive relation on the probability of
having a bank loan, these are not statistically different from zero.
Figure 7: Percentage of Mozambicans with a bank account by income quintiles

Figure 8: Percentage of Mozambicans with bank credit by income quintiles

Regarding long-term finance, mortgages are rarely used by Mozambican adults, even in urban
areas less than 5 percent of people report currently having one (see figure 9). According to the
MFSDS, the lack of mortgage products offered by banks has resulted in a major shortage of affordable and
adequate homes in urban areas of Mozambique (Mozambique Council of Ministers, 2013). The lack of
finance for the acquisition of houses is driven by several factors, including supply-side issues such as
limited coverage. The great majority of mortgages are provided for properties in the capital city of Maputo,
in neighboring Matola, and in surrounding suburbs, with hardly any provided in other parts of the country.
Demand-side constraints such as the lack of minimum amount of savings and prohibitive high costs for
housing finance, on the other hand explain why, as seen in figure 9, mortgages in urban areas are
22
significantly concentrated among the wealthiest individuals. In urban areas, while 10 percent of adults in the
fourth quartile of the income distribution have housing loans, only 4 percent of those in the third quartile
have a mortgage.
Figure 9: Percentage of adults in urban areas with a mortgage by income quartiles
1.4 Usage of Nonbank Financial Institutions

The financial system in Mozambique is heavily dominated by banks, but 48 percent of adults have
never used their products. Banks however, constitute the most common financial provider of the country,
followed by money lenders and microfinance institutions (MFIs), with 41 and 37 percent of adults having
used these. Interestingly, bank users are more likely to have used products from other types of financial
providers than non-bank users (see figure 10). Mozambicans that have never used bank products are also
less likely to have purchased products and services provided by MFIs, insurance companies, money
changers and even money lenders. Out of the 48 percent of the adult population that has never used
banks, only 20 percent has used MFIs and less than 10 percent has used insurance products or money
changers. In contrast, out of the 52 percent of the population of bank users, more than half has used MFIs
or money lenders, and about 30 percent has used insurance products and money changers (see figure 10).
Furthermore, even though on average Mozambican respondents have used at least one financial
provider, this number masks significant differences. While 19 percent of adults have used at least
three different financial institutions, more than a third of the population has never used any financial
provider12 (see figure 11). The data suggest two patterns. First, an important fraction of the population in
Mozambique does not use financial institutions, either because they choose not to or because they find it
difficult to do so. Second, while bank users may be more active in the financial market than non-bank
users, banks and other financial institutions may also be targeting similar clients, and those who are
excluded from banks are not being reached by other financial providers.
12
The financial providers that are included in this statistic are banks, insurance companies, MFIs and money changers.
23
Figure 10: Percentage of Mozambicans that have ever used financial institutions

Figure 11: Percentage of Mozambicans by the number of financial institutions that they have used

The data suggests substantial overlap on the type of clients targeted by banks and by certain
financial institutions in Mozambique, such as insurance companies, money changers and to some
extent, MFIs. Regression analysis shows that income, access to media and community characteristics are
the factors that best predict who the users of different financial providers are (see table 8 table 11 ). As
with banks, clients of money changers and insurance companies are concentrated at the top of the income
distribution. In contrast, MFI clients are not from the lowest income levels, but it is more likely for
Mozambicans above the median income to have used MFIs than for adults below it. Different from the other
financial providers, clients of money lenders are not associated with higher income. If anything, money
lender clients are more likely to be less educated and from a less favorable background.
Interestingly, individuals with fluctuating income are less likely to have ever used the products of
insurance companies or of any other financial institution. This result suggests there is room for
policies to target this population, who currently do not use any financial instrument to protect against
volatile income.
24
In terms of geographic characteristics of clients, banks, insurance companies and money changers
concentrate their services among urban clients from better-off communities. By contrast, clients of
MFIs are more likely to be both from urban and peri-urban communities rather than inner city
neighborhoods. Not surprisingly, time of commute matters - distance to the closest MFI branch is negatively
associated with the likelihood of using these institutions. Mozambicans that use money lenders are more
likely to be from areas with less infrastructure and lower population, and where the commute to the closest
bank branch takes longer.
1.5 Usage of Products of Nonbank Financial

Institutions
Financial providers in Mozambique offer a range of services that span from investment products to
pension plans, insurance, wire transfers, etc. (see figure 12). The type of saving products Mozambicans
currently use also varies substantially between urban and rural areas (panel 1 of figure 12). People in urban
areas are compared to rural dwellers more likely to save in formal institutions or to use community based
savings methods13. Even though it is less likely for rural adults to save formally, 47 percent of both rural and
urban Mozambicans report saving at home. This suggests that relative to urban areas, in rural areas there
may be various barriers that prevent people to save at formal institutions.
More sophisticated saving products, such as pensions or investment in stocks are not very
common among the population. Private pensions are only used by 1 and 4 percent of rural and urban
adults, which is consistent with the fact that only few private pension companies exist in Mozambique
(Mozambique Council of Ministers, 2013). Similarly, Mozambiques stock market is in its early development,
with only 3 percent of urban Mozambicans reporting having invested in stocks, bonds or funds.
As with savings, usage of credit- both from formal and informal providers-, insurance products and
money transfer services is higher in urban areas (panels 2, 3 and 4 of figure 12). This may partially
reflect that urban Mozambicans have a higher demand for financial products, but also that low penetration
of financial institutions in rural areas translates in lower usage of their services.
13Community
based savings methods refer to ASCAs (Accumulating Savings and Credit Associations), OPEs, Xitiques, and
Conta Familias.
25
Figure 12: Usage of financial products in rural and urban areas
1.6 Barriers to Formal Account Ownership

Whereas 29 percent of urban Mozambicans do not have basic formal accounts, in rural areas, 58
percent of adults lack one. While lack of formal accounts does not necessarily mean lack of access, only
5 percent of urban residents who lack accounts state that they do not need these products (see figure 13).
Much less, only 1 percent of rural dwellers without account report that they do not need one.
Figure 13: Percentage of Mozambicans with no formal accounts reporting they do not need this
product
26
The most important reason reported for not having an account is that people do not have enough
money to use them. The Financial Capability Survey asked respondents without a formal account to
report why they do not have an account at a financial institution. As figure 14 indicates, the most common
reason in urban areas is that Mozambicans do not have enough money to use them. Regression analysis
(see table 12) indicates that it is more likely for adults living in inner cities and lower education to state this
reason. Other relevant reasons mentioned by urban respondents include that formal accounts are too
expensive and interestingly, that they are too far away. The same reasons were mentioned by respondents
in rural areas, but relative to their urban neighbors, rural respondents complain more about accounts being
too far away and too expensive.
Another important barrier to formal account ownership is affordability, which is a much greater
barrier in rural areas. Fixed fees and costs of opening and maintaining an account can make small
transactions unaffordable for large segments of the population. As can be seen in figure 14, 20 percent of
those without an account who live in rural areas report that they cannot afford it. Although this number is
lower for urban populations, it is still the second most important reason for not having an account. High
costs and fees most likely reflect lack of competition as well as underdeveloped physical and institutional
infrastructure.
Taken together, even 19 and 26 percent of urban and rural respondents without formal accounts
state that they do not know how to open them or that they do not trust them. The national average of
those without formal account who reportedly do not know how to open an account or lack trust in them is 25
percent. These results suggest that financial illiteracy may be a significant barrier in the financial market of
the country, and that information campaigns that familiarize Mozambicans with financial products may be
one approach towards financial inclusion.
Figure 14: Reasons for not having a formal account in rural and urban areas
27
2. Financial Capability
Financial Capability is the internal capacity to act in ones best financial interest, given socioeconomic
environmental conditions. It therefore encompasses the knowledge, attitudes, skills, and behaviors of
consumers with regard to managing their resources and understanding, selecting, and make use of
financial services that fit their needs.
2.1 Knowledge of Financial Concepts and Products

The recent global financial crisis has highlighted the importance of financial knowledge and skills
(financial literacy) for peoples ability to take sound financial decisions and to benefit from the
financial services they use. It is a well-accepted hypothesis that limitations in consumers ability to fully
understand the financial products and risks they had taken on, contributed significantly to the worst
financial crises since the great depression (Geradi et al. 2010; Klapper et al. 2012). Due to increased
availability of credit in Mozambique, the continuous growth of microfinance, and the development of
branchless banking networks, financial products and services are becoming available to populations which
have been formerly disconnected from the formal financial system. While these developments provide
benefits, they also bear risks which may be unfamiliar to existing and new customers. To be able to benefit
from these new opportunities without being exposed to undue risks, a certain level of financial knowledge
and skills is required.
In addition, limited financial knowledge can constrain the take up of financial products and
services. While lack of money, affordability and long distances were the most cited reasons for not having
an account, 25 percent of Mozambicans without a formal account state that they do not know how to open
an account or that they do not trust these products. This chapter explores demand side constraints in
uptake and beneficial use of financial services. In particular, it tries to identify gaps in financial knowledge
that need policy attention as well as vulnerable groups that display limited knowledge and understanding of
financial concepts and products.
2.1.1 Knowledge of Financial Concepts

Financial knowledge levels of fundamental concepts are a significant challenge in Mozambique, as
well as in many countries across different income levels. Table 1 shows for 21 countries the proportion
of adults with understanding of basic concepts such as inflation, simple and compound interest and who
are able to perform simple divisions. While survey respondents from Mozambique demonstrate relatively
high comfort levels in solving simple numeracy tasks, compared to respondents from economies with
different income levels, main areas for improvement, such as understanding of the working of compound
interest and what inflation is, appear to be more of a challenge from a cross-country perspective.
28
Table 1: International comparison of knowledge of basic financial concepts (in % of adults)
Country
Year
Inflation
Albania
Armenia
Colombia
Czech Republic
Estonia
Germany
Hungary
Ireland
Lebanon
Malaysia
Mexico
Mongolia
Mozambique
Norway
Peru
Poland
South Africa
Turkey
Tajikistan
United Kingdom
Uruguay
2011
2010
2012
2010
2010
2010
2010
2010
2012
2010
2012
2012
2013
2010
2010
2010
2010
2012
2012
2010
2012
61
83
69
80
86
61
78
58
69
62
55
39
28
87
63
77
49
46
17
61
82
Simple
Interest
40
53
19
60
64
64
61
76
66
54
30
69
78
75
40
60
44
28
35
61
50
Compound
Interest
10
18
26
32
31
47
46
29
23
30
31
58
28
54
14
27
21
18
56
37
N/A
Simple
division
89
86
86
93
93
84
96
93
88
93
80
97
93
61
90
91
79
84
97
76
86
Source: WB Financial Capability Surveys and OECD National Financial Literacy and Inclusion Surveys
To assess respondents financial knowledge and their basic numeracy skills, 7 questions were
added to the 2013 Mozambique Financial Capability Survey, covering basic calculus and financial
concepts such as interest rates, inflation, compound interest, risk diversification, and the main purpose of
insurance products. These questions have been asked because they capture financial concepts and skills
which are widely considered as being crucial for informed savings and borrowing decisions as well as for
being able to manage risks more effectively and or to take advantage of investment opportunities. We
construct a financial literacy index based on the number of correct responses provided by each survey
participant to the seven financial literacy questions. This index ranges from 0 to 7, whereby 0 indicates
respondents who struggle the most with correctly answering any of these questions, while a score of 7
indicates survey participants with good understanding of fundamental financial concepts and the ability to
perform simple mathematical calculations.
29
Box 3: Financial Literacy Quiz
Question 1 Imagine that five brothers are given a gift of 10,000 MZN. If the brothers have to divide
the money equally, how much does each one get?
Question 2 Now, imagine that the five brothers have to wait for one year to get their part of the
10,000MZN and inflation stays at 10%. In one years time will they be able to buy:
More with their share of money than they could today
The same amount
Less than they could buy today
It depends on the types of things that they want to buy (do not read out this option)
Question 3 Suppose you put 10,000 MZN into a savings account with a guaranteed interest rate of
2% per year. You dont make any further payments into this account and you dont withdraw any
money. How much would be in the account at the end of the first year, once the interest payment is
made?
Question 4 How much would be in the account at the end of five years? Would it be:
More than 11,000 MZN
Exactly 11,000 MZN
Less than 11,000 MZN
It is impossible to tell from the information given
Question 5 Lets assume that you saw a TV-set of the same model on sales in two different shops.
The initial retail price of it was 10,000 MZN. One shop offered a discount of 1,500 MZN, while the
other one offered a 10% discount. Which one is a better bargain, a discount of 1,500 MZN of 10%?
A discount of 1,500 MZN
They are the same
A 10% discount
Question 6 Which of the following statements best describes the primary purpose of insurance
products?
To accumulate savings
To protect against risks
To make payments or send money
Other
Question 7 Suppose you have money to invest. Is it safer to buy stocks of just one company or to
buy stocks of many companies?
Buy stocks of one company
Buy stocks of many companies
30
The survey results suggest that on average respondents were able to correctly answer 3.7 out of 7
questions on financial literacy. As shown in figure 15, the majority of survey participants were able to
provide between 3 and 5 (around two thirds of the sample) correct answers. Giving correct responses to 6
or more questions seemed, however, to be a challenging task which was only achieved by around 9
percent, while only slightly more than 1 percent was able to provide correct responses to all 7 financial
literacy questions. A more concerning finding is, that a significant proportion of respondents, around one
fifth (18 percent), was not able to provide more than 2 correct answers, while 9 percent of the sample
struggled in answering more than 1 financial literacy question correctly.
Figure 15: Distribution of financial literacy scores

One can conclude that whilst most can perform simple financial calculations, they may lack the
specific knowledge required to make sensible savings and borrowing decisions. Figure 16 reveals
that almost all respondents were able to perform simple divisions (93 percent) and around three quarters
were comfortable with simple interest rate calculations. By contrast, understanding of fundamental financial
concepts is more challenging for the majority of the sample. 43 percent of the surveyed population
understands the main purpose of insurance products. A similar proportion of the sample (42 percent)
understands that holding stocks from different companies implies less risky returns than holding stocks
from a single company). Slightly less, around 38 percent, seems to be comfortable in solving simple
numeracy task in order to identify better bargains. The most notable knowledge gaps which deserve most
policy attention are that only around a quarter of the survey participants understand the working of
compound interest (28 percent) and how inflation affects their savings (27 percent).
31
Figure 16: Financial literacy quiz overview

Figure 17: Education levels of populations with low and high financial literacy scores

Vulnerable groups who struggle the most in understanding basic financial concepts are more likely
to have low educational attainment, less likely to be formally employed, and they live further away
from the next bank branch. As shown in figure 17, survey participants who provided 2 or less correct
responses to the financial literacy quiz-type questions appear to be more likely to have lower educational
attainment than their counterpart group with better understanding of financial concepts. For instance, while
12 percent of those who achieved a score higher than 2 on the financial literacy quiz have tertiary
education, only 2 percent of those who answered 2 or less questions correctly can be found in the group
with the highest educational attainment. Similarly, those who are challenged with answering more than 2 of
the financial literacy questions correctly are also less likely to be formally employed compared to those who
32
reach higher financial literacy scores. Interestingly, proximity to banks matters too and those who live
further away from the next bank branch are more likely to struggle in understanding basic financial
concepts. Likewise, regression analysis shows (see table 13) that even after controlling for socioeconomic
and demographic factors the availability of a primary school, such as distance to school, is associated with
better understanding of financial concepts. However, the magnitude of these two infrastructural effects
appears to be rather small.
In contrast, a better understanding of financial concepts is strongly correlated with individual
characteristics such as higher education, formal employment and living in urban habitats. As may
be expected, regression analysis reveals (see table 14), that higher financial literacy scores correlate with
higher educational attainment, even after controlling for other characteristics. Likewise, the knowledge gap
between those who are formally employed and those who are not employed is significant. Compared to
rural dwellers, those who live in urban areas have significantly better understanding of financial concepts.
Notably, even though income levels are not significantly correlated with higher financial literacy scores,
income uncertainty is. Those who live on varying incomes score on average significantly higher on the
financial literacy quiz-type questions than their counterparts whose income is not subject to income
fluctuations.
Moreover, higher levels of financial knowledge relate to enabling environmental factors such as the
proximity to banks and the development level of the location people live in. The longer it takes to get
to the next bank branch, the less likely it is that survey participants are familiar with financial concepts, even
after controlling for other characteristics by means of regression analysis (see table 13). Similarly,
indicators which proxy for the socio-economic and infrastructural development of the location, such as low
criminal rates or proximity to hospitals, seem to matter for better understanding of financial concepts. As
compared to those residents who live in safe areas with basic health infrastructure, those who live in areas
with high criminal rates or larger distances to the next hospital are less likely to answer more financial
literacy questions correctly. This may be due to the influence that these socio-economic and infrastructural
factors exert on the decision of banks to open their branches in certain areas.
Areas for improvement identified through the objective financial knowledge quiz are also reflected
in participants self-assessment of their levels of awareness and understanding of financial
concepts. In order to compare the objective findings of the financial literacy quiz into the context of
subjective education needs, respondents were also asked to self-assess their awareness and
understanding of financial terms and concepts such as interest rates, insurance products, exchange rates
and inflation. As seen in figure 18, reported awareness and understanding of interest rates is wide-spread.
While only around 7 percent of the respondents stated that they have never heard about the term interest
rate, the overwhelming majority of respondents (79 percent) indicated that they have not only heard about
it, but also know what it means. The latter number is fairly close to the proportion of adults who provided a
correct answer to the quiz question on simple interest (78 percent). Similarly to the results of the financial
literacy quiz, respondents self-assessment acknowledges that they struggle to understand the main
purpose of insurance products or what inflation is.
33
The high correlation between what respondents know and what they think they know is indicative
of peoples readiness to accept their areas for improvement and thus creates demand for efficient
financial education. While most of those who stated having knowledge about financial products and terms
also answered correctly the financial knowledge quiz-type questions, a relatively small fraction of
respondents who stated that they lack understanding managed to score on the respective objective
measures (see figure 19). Notably, for the concept of inflation a wide gap between self-perceived and
actual understanding appears to exist. However, these results prove an indication that people are very well
aware of their areas for improvement which may lay the foundations and create demand for efficient
financial education programs.
Figure 18: Reported awareness & understanding of financial terms

Figure 19: Comparison of reported understanding and financial literacy quiz results
34
2.1.2 Knowledge of Financial Products

In order to assess survey participants awareness levels of financial products the financial
capability survey captured information on peoples familiarity with products offered by different
financial service providers. In particular, survey participant were asked if they are familiar with products
offered by banks, MFIs, insurance companies, community savings groups, money changers, money
lenders, and brokerage houses. We construct a financial products awareness index based on the number
of financial products known, as indicated by each survey participant. This index ranges from 0 to 7,
whereby 0 indicates respondents who are not familiar with products offered by any type of provider.
Respondents with a score of 7 on the other hand stated familiarity with products offered by the seven
providers that the survey asked about.
Figure 20: Distribution of financial products awareness scores

As far as the average number of financial products known is concerned, respondents are familiar
with products provided by 3.3 different types of providers. Figure 20 shows that around two thirds of
the sample indicated to be familiar with between 3 to 5 products, whereas around 9 percent are familiar
with financial products provided by 6, and only around 2 percent with products offered by 7 different
providers. The most concerning fact is, however, that even 22 percent are not aware of financial products
provided by any type of provider.
A deeper exploration into the type of financial products known reveals that survey participants are
mainly familiar with bank products (74 percent), followed by products offered by MFIs (71 percent)
and money lenders (64 percent). Much less, around two fifth of the sample indicated that they are familiar
with the products offered by community savings groups (43 percent) and insurance companies (38
percent). Money changers and their products are known by a third of the respondents (see figure 21),
whereas brokerage houses and their services are only known by 7 percent of the sample which can be
35
explained by the fact that the capital market in Mozambique is currently in a nascent stage, as is the case
in many countries at a similar income levels (Mozambique Council of Ministers, 2013).
Figure 21: Knowledge of financial products offered by different providers

Respondents who are the least familiar with financial products offered by different providers tend
to live in rural neighborhoods and on low and irregular income streams. The need to manage low and
erratic income flows as well as living in rural environments is a strong predictor for being less familiar with
products from a variety of financial service providers, in particular with insurance products. Insurance
products could, however, enable them to better deal with bad events when they occur. Even though the
insurance sector in Mozambique is still under-developed, this result suggests that improving awareness of
insurance is the key to increasing demand and should complement any policy actions to target this
population and to grow the market for insurance.
Another pattern which emerges is that better financial knowledge of products and services highly
correlates with the regular consumption of different types of media. Not surprisingly, people who try to
stay informed by using different types of media at a regular basis are substantially more likely than less
active media consumers to demonstrate familiarity with all types of financial products, not only bank
products (see figure 22).
36
Figure 22: Percentage of Mozambicans that know about different providers by number of media
used
2.2 Financial Behavior and Attitudes

Even if people possess the knowledge of basic financial concepts and products they may struggle
to translate it into action. To identify the role that attitudes play in individuals' financial decisions and to
see how attitudes translate into financial behavior, the survey contains questions on different aspects
(components) of financial capability that include attitudes/motivations and behaviors. This chapter gives an
overview of strengths and areas for improvements surveyed Mozambicans show regarding relevant
financial behaviors and attitudes.
In the Mozambique data set, 10 main components of financial capability can be identified, some of
which refer to behaviors, and others to attitudes or motivations. Each financial capability component is
measured through a combination of relevant questions. These are identified by using a statistical technique
called principal component analysis (PCA). PCA is a data reduction method that finds a small number of
linear combinations of those variables that explain most of the variance in the data. The method is used to
aggregate the variables that measure different nuances of the same component in order to obtain a single
indicator (or score) for that component. Each component score ranges between 0 (lowest score) and 100
(highest score).
The following eight components measure behaviors related to financial capability: budgeting, not
overspending, living within means, monitoring expenses, saving, planning for unexpected
expenses, making provisions for old age, and choosing products. More specifically, budgeting
measures the extent to which people plan how to use their money and whether they adhere to the plan; not
overspending assesses whether people refrain from spending their income on non-essentials or on things
37
they cannot afford; living within means measures the level of borrowing and whether people borrow to buy
food and other essentials; monitoring expenses measures the ability to follow planned budgets and
expenses; saving measures whether people see themselves as trying to save for the future, trying to save
for emergencies, and trying to save even if a small amount; planning for unexpected expenses indicates
whether people could cover an unexpected expense equivalent to a month's income and whether they
worry about it; making provisions for old age indicates whether people have strategies in place that allow
them to cover for expenses in old age; and choosing products indicates whether people search for
alternatives, check terms and conditions, get information before selecting financial products, and search
until they found the best products for their needs. The last score is only calculated for those who have
personally chosen a financial product in the past 5 years.
Two financial capability components refer to attitudes and motivations, such as farsightedness,
and attitude towards information. In particular, farsightedness measures whether people agree or
disagree with statements such as I live for today, The future will take care of itself, I only focus on the
short term; the measure attitudes towards information is a combination of getting information and advice
before making financial decisions, learning from others, and having many aspirations.
Figure 23: Average financial capability scores

Compared to other aspects of financial capability, survey participants show strengths in areas
related to day-to-day money management. Figure 23 shows all scores for different aspects of financial
capability in increasing order. As can be seen, the highest average score (74) is obtained for controlled
38
budgeting, followed by scores which are related to managing day-to-day finances, such as living within
means (64), not overspending (63), and monitoring expenses (61).
Financial attitudes and behaviors, on the other hand, which relate to thinking about the future, and
putting money aside for unexpected or old age expenses, seem to be a major challenge in
Mozambique. Figure 23 also reveals that compared to day-to-day money management, respondents score
on average much lower with regard to coping with unexpected shocks (45), saving regularly, even if only a
little (42), thinking of the future (40) and making provisions for old age expenses (40). These low scores are
worrying given their implications for peoples ability to smooth consumption, to cope with economic shocks,
to generate lump sums for productive investments, and ultimately for their long-term wellbeing.
The lowest score is, however, found for financial behaviors that relate to choosing financial
products and services (34). The lowest overall financial capability score indicates that consumers ability
to take advantage of available financial services may be limited. The survey results show that slightly less
than half of those who have chosen a financial product in the past 5 years were searching for information
from a range of resources or searched until they found the best product for their needs, while only 37
percent considered many alternatives before deciding which product to get.
An international comparison to survey participants in 9 countries confirms that Mozambicans
respondents are especially good in managing day-to-day finances, but are among the most
challenged in terms of putting money aside for unexpected and old age expenses and choosing
financial products. Table 2 compares the financial capability scores Mozambicans achieved in 10 different
areas to the ones of respondents in various countries in which a similar survey has been conducted. While
survey participants from Mozambique demonstrate strengths in budgeting and monitoring how they had
spent their money, they display relatively weaker performance in saving, putting money aside for
unexpended and old age expenses, and in particular in choosing financial products.
Table 2: Cross-country comparison of different financial capability scores
Country
Armenia
Colombia
Lebanon
Mexico
Mongolia
Mozambique
Nigeria
Tajikistan
Turkey
Uruguay
Controlled
budgeting
Not overspending
Monitoring
expenses
Using
information
74
80
40
52
65
74
78
81
60
71
84
79
70
70
71
63
71
94
66
84
63
36
44
41
N/A
61
48
N/A
50
48
69
80
71
72
65
56
N/A
87
69
76
39
Planning for
unexp.
expenses
64
59
73
64
N/A
45
71
N/A
68
55
Country
Armenia
Colombia
Lebanon
Mexico
Mongolia
Mozambique
Nigeria
Tajikistan
Turkey
Uruguay
Saving
Far-sightedness
46
45
40
57
62
42
55
66
30
44
28
37
55
35
60
40
N/A
84
50
35
Planning for ones

own future
100
67
71
65
N/A
40
N/A
N/A
72
60
Choosing financial
products
59
57
63
59
49
34
N/A
N/A
52
N/A
Source: WB Financial Capability Surveys

In Mozambique, low-income populations and high-income earners seem to have complementary
skills. As compared to higher income segments, low income groups are mastering the task of monitoring
their expenses and seem to be quite farsighted. However, as would be expected, their ability to cope with
unexpected shocks seems to be limited by their scarce resources. Those respondents who live on higher
incomes are more inclined to build cushions for unexpected expenses in comparison to the lowest income
group, even after controlling for other demographic and socioeconomic factors (see table 16).
Income matters not only in terms of levels, but even more if it is subject to fluctuations. Regression
analysis also show, that despite being especially good in living within their means, those with varying
incomes struggling more with setting up a budget and adhering to it, monitoring their expenses, and
choosing financial products. In addition, they tend to think less about the future and have more difficulties
with setting aside funds for unexpected expenses than their counterparts with stable incomes.
Consequently, daily hardship and the constant struggle with solving immediate problems seem to draw
their attention away from their longer-term considerations and needs.
Another important personal characteristic which correlates with higher scores in several financial
capability areas is higher education. As can be seen in figure 24, those with higher educational
attainment appear to outperform those with lower education levels in terms of budgeting. Similarly, those
with higher education levels also appear to experience less difficulties in living within their means, are more
inclined to save regularly, even if only a little, and to cover for old age expenses than their counterparts with
lower educational attainment. However, as compared to those without school, those with higher education
levels appear to be more challenged with choosing financial products which fit their needs best.
40
Figure 24: Average budgeting score by education levels in urban and rural areas

Living in an urban neighborhood seems to be an important enabler in terms of sound financialdecision taking. Residents living in rural areas display relative strengths in monitoring their expenses but
struggle more than urban dwellers in a number of areas. As compared to urban populations, rural dwellers
have more difficulties in terms of budgeting, not overspending, covering for unexpected shocks and
choosing products that meet their needs. Rural residents also seem to have a less forward-looking attitude
than their counterparts living in urban environments.
Figure 25: Financial Capability in Choosing Financial Products (Left) and Being Far-sighted
(Right) by Region

Noticeable differences in financial capability scores across regions can only be observed in a few
areas. As can be seen in Figure 25, those who live in southern parts of the country appear to be more
41
inclined to think about the future and demonstrate strengths in choosing financial products and services
which fit their needs best.
Better results in the area of choosing financial products, in which survey participants score lowest,
are related to greater regular consumption of different types of media. The particularly low average
scores in the area of choosing financial products among those who have personally selected a financial
product in the past 5 years raise the question which personal factors can be associated with a better
beneficial use of financial products. Figure 26 reveals that the regular use of different media types is an
important personal characteristic which highly correlates with the ability to select appropriate products,
especially in rural areas.
Figure 26: Average choosing financial products score by media consumed in urban and rural areas
42
3. Relationship between Financial Inclusion

and Financial Capability
There is little doubt that financial capability and financial inclusion influence each other. While lack
of knowledge about financial products may hinder their use, it may also be the case that as people begin
using financial services, they become more familiarized with them and knowledgeable about them, in a
learning by doing fashion. While disentangling a causal link between financial inclusion and financial
capability is beyond the scope of this report, this chapter presents an overview of who the financially
excluded in Mozambique are and how their financial capabilities compare to those financially included.
Results of the Financial Capability Survey indicate that in Mozambique, low understanding and lack
of trust are excluding a substantial fraction of adults from using basic financial products, such as
formal accounts. As outlined in chapter 1, 25 percent of Mozambicans state that they do not have a formal
account because they do not know how to open them or because they do not trust them. In rural areas,
these two reasons are more frequently mentioned than the service being too costly, the branch being too
far away, or not having enough money to use the account. In urban areas, not having enough money to use
the account is the only reason that is more common than lack of trust or knowledge about the product.
Mozambicans without formal accounts are also less aware of the services of different financial
providers, and thus, less likely to use them. According to the financial products awareness index
described in chapter 2, even after controlling for a set of factors ranging from socioeconomic, demographic
and village characteristics, awareness of financial providers is an important predictor of activity in the
financial market. Compared to those with high awareness about financial products, Mozambicans who are
less knowledgeable of the services of financial institutions are less likely to have a formal account and to
use different financial instruments - such as credit, insurance or savings- from various financial providers
(see figures 27 and 28). This however, may simply reflect that people gain awareness of financial
institutions and their products as they become more active in the financial market.
A substantial proportion, one out of five Mozambican respondents display lack of knowledge about
any of the financial products assessed in the survey. Of these, none of them has a formal account or
any other type of financial product. In contrast, Mozambicans who are more likely to know about the
services of different financial providers are consistently more active in the financial market.
43
Figure 27: Financial products awareness score of Mozambicans with and without formal accounts

Even though the usage of informal providers is high, as Mozambicans increase their awareness of
financial products they rely more on formal financial institutions. As figure 28 indicates, the fraction of
adults saving at a bank steadily increases with the awareness index. In contrast, usage of informal savings
slightly decreases. Likewise, the fraction of adults who use bank credit increases at a steeper rate than the
proportion of Mozambicans using informal finance.
Figure 28: Usage of financial products by awareness of financial products score
44
While Mozambicans who do not participate in the financial market are less aware of the services of
different financial institutions, their financial literacy level is comparable to those actively using
financial products. According to the financial literacy index discussed in chapter 2, Mozambicans with and
without formal accounts have comparable knowledge levels on basic calculus and fundamental financial
concepts (see figure 29).
Figure 29: Financial literacy scores of Mozambicans with and without formal accounts

A similar surprising finding is that the least financially literate Mozambicans are as likely to use
formal and community based savings (e.g. ASCAs) as the most literate ones (see figure 30).
However, as financial literacy increases, the likelihood of using informal savings mechanisms, such as
saving money under the mattress, declines. A similar pattern is found regarding credit. More financially
literate adults are less likely to rely in credit, especially if coming from an informal provider. On one hand,
these findings suggest that financial products are not reaching Mozambicans who in terms of financial
understanding and ability are at least as able as Mozambicans with established relations with financial
institutions. On the other hand, these patterns also indicate that policymakers need to pay attention not only
to the financially excluded population, but also to Mozambicans who despite being financially active, lack
basic financial knowledge and skills to make informed and sound decisions on their savings, loans or
insurance plans.
Figure 30: Usage of financial products by financial literacy score
45

Regarding behaviors and attitudes, they are overall not too different between those respondents
with and without a formal account. Using the same financial capability scores as described in chapter 2,
survey results suggest that Mozambicans who do not have a formal account are as likely to live within their
means, save for the future, not overspend, or plan for unexpected expenses as those with formal accounts.
However, figure 31 indicates that Mozambicans who have a formal account are marginally more likely to
monitor their expenses and obtain information and advice before making financial decisions.
Figure 31: Financial behaviors & attitudes of Mozambicans with and without formal accounts

Interesting patterns appear when examining the financial capability scores of Mozambicans who
use different financial products (tables 18 and 19 present the regression results). Those who save,
regardless of whether they save with formal providers, use community based savings methods or save at
home, are more disciplined with their spending than non-savers (see figure 32, panel A). More disciplined
Mozambicans are actually more likely to be saving in more formal places, even after controlling for a range
of socio-economic, demographic and location variables. Mozambicans who formally save at a bank are
also better in monitoring and planning their expenses (see figure 32, panel D).
The budgeting behavior and financial capability scores of credit users are substantially different
from the rest of the population. As indicated in figure 32 (panel C), Mozambicans who currently have
credit are significantly less likely to live within their means than Mozambicans without credit. This may
46
reflect that Mozambicans are using credit when their income flows are not enough to cover their expenses.
Similar to the pattern observed in savings, as Mozambicans borrow from more informal providers their
budgeting and financial capability scores decrease. Those who borrow from informal lenders are the least
likely to live within their means, and as seen in figure 32 (panel B), informal lender borrowers are also
substantially less likely to make provisions for old age and more likely to over spend.
Figure 32: Financial behaviors & attitudes of Mozambicans with and without different financial
products
47
4. Financial Consumer Protection

In addition to peoples ability to take sounds financial decisions, the recent financial crisis has
highlighted the importance of financial consumer protection to protect consumers from abusive
sale practices and to level the playing field between providers and consumers of financial services.
Financial consumer protection is about ensuring a fair interaction between providers and consumers of
financial services. A consumer protection regime is essential in counterbalancing the inherent disadvantage
of financial service consumers vis--vis the power, information, and resources of their providers. Without
basic protective measures, consumers can be challenged or may find it costly to obtain sufficient
information or adequately understand the financial products that they use.
Thus, financial consumer protection is necessary to ensure stable financial markets in Mozambique
while ensuring that expanded access benefits consumers and the overall economy. Given the
relatively low levels of financial inclusion in Mozambique, a number of initiatives are planned or already
underway to increase financial sector outreach to formally excluded populations (see Mozambique Council
of Ministers, 2013). Increased access to finance can result in substantial positive effects, both on the macro
level as well as on the level of individuals. However, it can be harmful if inexperienced consumers are not
protected against fraud or unfair business practices.
In addition, effective financial consumer protection frameworks are critical for instilling confidence
in the financial system and for promoting financial sector outreach. A high incidence of conflicts with
providers of financial services or low levels of satisfaction with financial products used could undermine the
trust in the financial system. Despite making existing consumers worse off, it can also discourage potential
new consumers to enter the market, which may partially explain why 12 percent of those without a formal
account mentioned lack of trust as the main barrier for not having an account (see chapter 1). This section
investigates if the products financially included individuals use are effectively meeting their needs. In
particular, it identifies segments which are more likely to have encountered a financial service provider
conflict in the past three years and who seem less likely to be satisfied with the products they use.
In order to measure whether products financially included individuals use are effectively meeting
their needs, the financial capability survey captured if survey participants were in general satisfied
with different types of products they ever used. More specifically, respondents were asked if they are
satisfied with products they used from by banks, MFIs, insurance companies, community savings groups,
money changers, money lenders, and brokerage houses.
Despite serving more customers than other types of providers, banks and their products seem to
meet their customers needs on a moderate level, similar to those of providers with lowest
penetration rates. While 52 percent of the population have been using bank products at some point in
their lives (see chapter 1), only 49 percent of their clients indicate to be satisfied with their products. As
shown in figure 33, which presents the satisfaction rates for different providers and orders them by their
48
level of penetration; this is a much lower satisfaction rate than the following four providers with the widest
outreach achieve. Only insurance companies and brokerage houses whose products reach a small fraction
of adults appear to have a similar proportion of customers who claim to be satisfied with the products they
offer. A potential explanation for the rather low satisfaction rate banks face may be the lack of competition
in the banking sector. This lack of competition does not only result in high costs, commissions and fees
(see World Bank 2013), but may also lower incentives to provide appropriate products that satisfy their
customers needs.
Figure 33: Usage and satisfaction rates for different financial providers

Delving deeper into the issue of low bank satisfaction rates revealed that financially illiterate
respondents are more vulnerable to purchasing and being sold products that do not meet their
needs. Those who are struggling more with understanding basic financial concepts also appear to be less
satisfied with bank products (see figure 34), even after controlling for other demographic and
socioeconomic factors (see table 17). This result suggests that those with lower financial literacy levels are
more vulnerable to selecting and being sold inappropriate or even harmful products. Consequently, they
require basic measures which help them understand costs and key terms of (bank) products they use and
protect them from misleading sale practices.
49
Figure 34: Commercial bank satisfaction rates by financial literacy score

Another interesting finding is that consumers of financial services do not widely report complaints
or other types of conflicts with providers, neither do they try to solve conflicts they encounter. As
shown in figure 35, only 13 percent of the sampled respondents state, that they experienced a conflict with
a financial service provider in the past three years. Less than half of those who encountered a dispute (47
percent) took actions to try to solve it. Only 40 percent of those who did not experience a conflict stated that
if they faced a conflict they would try to solve it.
Figure 35: Approaches to deal with financial service provider conflicts

Looking at the characteristics of those who faced a dispute, the survey results suggest that among
the groups most vulnerable to having encountered a conflict are those who struggle to understand
basic financial concepts. Scoring low on the financial literacy quiz is not only a good predictor for being
50
less satisfied with bank products as compared with those who score higher, but also for being more
vulnerable to having encountered a financial service provider conflict. Regression analysis reveal, that
holding other demographic and socioeconomic characteristics constant, factors which correlate with a
higher probability of having faced a conflict are earning stable incomes, consuming more different types of
media regularly, and living in an urban neighborhood. This is due to the fact that these characteristics are
also highly correlated with usage of products from a wide range of providers, which increases the
probability of having encountered a conflict.
Regarding the actions taken to seek redress, redress systems such as the respective regulatory
government agency or legal courts were not sought at all by those who experienced a dispute with
their financial service provider. In the event that a consumer complaint is not resolved within the financial
institutions own internal procedures, the customer has currently two possible options. One is to turn to the
BdM and its team inside of the Department for Strategic Planning, Communication and Image in charge of
consumer complaint handing and financial education; the other one is to proceed to court. Figure 36
presents the approaches followed in trying to resolve the conflict. As can be seen, the most common
approach was to submit a grievance to the company who sold the product (41 percent), followed by
approaching the service provider through friends and family (40 percent). 31 percent of the respondents
preferred to stop using the service before the contract expired. Figure 36 further reveals that neither BdM
and its team in charge of consumer complaint handling, nor legal courts were sought as systems of
redress. That courts were not considered at all can most likely be explained by perceived high costs and
lengthy time of proceedings. That consumers do not turn to the BdM may on the other hand be due to the
fact that financial services contracts typically do not specify what a consumer should do in the event that he
or she has a complaint, and the possibility of recourse to the BdM in the event that the complaint is not
resolved to the consumers satisfaction following completion of the financial institutions internal complaints
procedures (World Bank 2013c).
Figure 36: Actions taken to redress conflicts with financial service providers
51
The main reasons for not trying to solve a conflict are either lack of trust in or lack of awareness of
respective government authorities which can be approached in the event of a dispute. More than half
of those who did not take any actions to solve a dispute stated lack of trust in the effectiveness of
government authorities as main reason for their inertia (see figure 37), followed by 48 percent who
indicated that they are not aware of any government agencies they can approach for help. Around 40
percent of those who did not try to solve a conflict mentioned that they did not take any actions because
they perceive financial institutions as too powerful, while a quarter stated that the law does not adequately
protect them.
Figure 37: Reasons for not solving conflicts with financial service providers
52
References
Atkinson, Adele and Flore-Anne Messy. 2012. Measuring Financial Literacy: Results of the
OECD/International Network on Financial Education (INFE) Pilot Study. OECD Working Papers on
Finance, Insurance, and Privat Pensions, No. 15, OECD Publishing.
Banerjee, Abhijit, Esther Duflo, Rachel Glennerster, and Cynthia Kinnan. 2013. The miracle of
microfinance? Evidence from a randomized evaluation. National Bureau of Economic Research
Working Paper No. 18950.
Banco de Mocambique (BdM). 2013. Challenges to Financial Inclusion in Mozambique. A Supply-Side

Approach.
Berg, Gunhild and Bilal Zia. 2013. Financial Literacy through Mainstream Media: Evaluating the Impact
of Financial Messages in a South African Soap Opera. World Bank Working Paper, Washington, DC.
Buehler, R., Griffin, D. and Ross, M. 2002. Inside the planning fallacy: The causes and consequences
of optimistic time predictions. Pp. 250-270 in Gilovich, T., Griffin, D. and Kahneman, D.
(eds.) Heuristics and Biases: The Psychology of Intuitive Judgment. Cambridge, U.K.: Cambridge
University Press.
Demirguc-Kunt, Asli and Leora Klapper, 2012. Measuring Financial Inclusion: The Global Findex
Database. World Bank Working Paper No. 6025, Washington, DC.
Coville, Aidan, Vincenzo Di Maro, Siegfried Zottel and Felipe Alexander Dunsch. 2013. The Impact of
Financial Literacy through Feature Films: Evidence from a randomized experiment in Nigeria.
Financial Literacy & Education, Russia Trust Fund.
FinMark Trust. 2009. FinScope 2009 Mozambique Survey report.

Gerardi, Kristopher, Lorenz Goette, and Stephan Meier. 2010. Financial Literacy and
SubprimeMortgage Delinquency: Evidence from a Survey Matched to Administrative Data. Federal
Reserve Bank of Atlanta Working Paper Series 201010.
Mozambique Council of Ministers. 2013. Mozambiques Financial Sector Development Strategy 20132022.
Love, Inessa, and Maria Soledad Martinez Peria. 2012. How Bank Competition Affects Firms Access
to Finance. Policy Research Working Paper 6163, World Bank, Washington, DC.
Karlan, Dean, Margaret McConnel, Sendhil Mullainathan, and Jonathan Zinman. 2010. Getting to the
top of mind: How reminders can increase Saving. National Bureau of Economic Research Working
Paper No. 16205.
Klapper, Leora, Anna Maria Lusardi, and Georgios A. Panos. 2012. Financial Literacy and the
Financial Crisis. World Bank Working Paper No. 5980, Washington, DC.
Yoko Doi, David McKenzie and Bilal Zia. 2012. Who you train Matters: Identifying Complementary
Effects of Financial Education on Migrant Households. World Bank Working Paper No. WPS6157,
Washington, DC.
53
World Bank Group. 2013a. Global Financial Development Report 2014: Financial Inclusion. World
Bank, Washington, DC.
World Bank Group. 2013c. Mozambique: Diagnostic Review of Consumer Protection and Financial
Literacy. Volume I Key findings and Recommendations. World Bank, Washington, DC.
World Bank Group. 2013d. Financial Capability Surveys Around the World: Why Financial Capability is
important and how Surveys can help. World Bank, Washington, DC.
54
Appendix
A.
Background on the Mozambique Survey
Figure 38: Estimated population break-down by urban/rural

Figure 39: Estimated population break-down by different income groups

Figure 40: Estimated Population Break-down by Male/Female
55
Figure 41: Estimated population break-down by age groups

Figure 42: Estimated population break-down by education groups

Figure 43: Estimated division of stable/unstable income groups

Figure 44: Estimated population break-down by household size

56
B.
Financial Inclusion
Figure 45: Account at a formal financial institution across Sub-Saharan African countries
Account at a formal financial institution by gender (% age 15+)

Senegal
Sudan
Congo, Rep.
Cameroon
Gabon
Tanzania
Mauritania
Uganda
Ghana
Nigeria
Mauritius
Zimbabwe
Mozambique
Kenya
South Africa
Angola
0.0
10.0
20.0
30.0
40.0
50.0
60.0
Male
Female
70.0
80.0
90.0
100.0
90.0
100.0
Account at a formal financial institution by income (% age 15+)

Senegal
Sudan
Congo, Rep.
Cameroon
Gabon
Tanzania
Mauritania
Uganda
Ghana
Nigeria
Mauritius
Zimbabwe
Mozambique
Kenya
South Africa
Angola
0.0
10.0
20.0
30.0
40.0
By income, top 60%
50.0
60.0
70.0
80.0
By income, bottom 40%
Source: Global Financial Inclusion (Global Findex) Database, World Bank, Washington, DC,
http://www.worldbank.org/globalfindex.Demirguc-Kunt and Klapper, 2012
57
Figure 46: Loan from a financial institution in the last year across Sub-Saharan African countries
Loan from a financial institution in the past year by gender (% age 15+)
Senegal
Sudan
Congo, Rep.
Cameroon
Gabon
Tanzania
Mauritania
Uganda
Ghana
Nigeria
Mauritius
Zimbabwe
Mozambique
Kenya
South Africa
Angola
0.0
5.0
10.0
Male
15.0
20.0
25.0
Female
Loan from a financial institution in the past year by income (% age 15+)
Senegal
Sudan
Congo, Rep.
Cameroon
Gabon
Tanzania
Mauritania
Uganda
Ghana
Nigeria
Mauritius
Zimbabwe
Mozambique
Kenya
South Africa
Angola
0.0
2.0
4.0
6.0
8.0
By income, top 60%
10.0
12.0
14.0
16.0
18.0
By income, bottom 40%
Source: Global Financial Inclusion (Global Findex) Database, World Bank, Washington, DC,
http://www.worldbank.org/globalfindex.Demirguc-Kunt and Klapper, 2012
58
20.0
C.
Regression Tables
1. Financial Inclusion
Table 3: Probability of knowing about commercial banks on demographic and socioeconomic
factors
(1)
0.00951***
(0.00332)
-0.0306
(0.0708)
-0.195**
(0.0843)
-0.296**
(0.141)
-0.527***
(0.148)
0.157
(0.135)
0.198**
(0.0798)
(2)
0.00889**
(0.00370)
-0.0992
(0.0710)
-0.171*
(0.0894)
-0.187
(0.146)
-0.433***
(0.157)
0.0249
(0.138)
0.279***
(0.0877)
0.0140
(0.0806)
0.121
(0.0832)
0.292***
(0.105)
0.259
(0.164)
0.0739
(0.120)
0.0436
(0.115)
-0.109
(0.103)
0.146
(0.331)
(3)
0.00742*
(0.00377)
-0.0862
(0.0729)
-0.135
(0.0920)
-0.0621
(0.151)
-0.290*
(0.159)
-0.128
(0.142)
0.287***
(0.0892)
0.00495
(0.0826)
0.0571
(0.0856)
0.186*
(0.107)
0.277
(0.170)
0.0834
(0.121)
0.0650
(0.117)
-0.101
(0.106)
0.0480
(0.343)
0.620***
(0.0790)
Constant
0.345**
(0.146)
0.327*
(0.177)
0.248
(0.187)
(4)
0.00710*
(0.00398)
-0.127
(0.0781)
-0.143
(0.0970)
-0.0579
(0.162)
-0.292*
(0.169)
-0.252
(0.155)
0.301***
(0.0954)
0.0278
(0.0896)
0.0249
(0.0918)
0.127
(0.111)
0.405**
(0.189)
0.000803
(0.135)
0.118
(0.125)
-0.0495
(0.112)
0.0989
(0.391)
0.527***
(0.0820)
0.458***
(0.146)
0.641***
(0.152)
0.681***
(0.163)
0.774***
(0.205)
1.192***
(0.302)
1.254***
(0.401)
0.00690
(0.0223)
0.243***
(0.0791)
0.0707
(0.133)
-0.395
(0.282)
Observations
df_m
F
3,000
7
8.871
2,758
15
5.152
2,758
16
7.594
2,572
25
5.769
Age
Male
Primary school
Secondary school
Tertiary school
Read/write Portuguese
Hhd head
2nd income quantile
3rd income quantile
4th income quantile
Unemployed
Formally employed
Informally employed
Self-employed
Retired
Urban village
One media used
Two media used
Three media used
Four media used
Five media used
Six media used
HH size
1 = if income stable
Saved as a Child
59
Estimates of the probit model. Standard errors in parentheses. *** p<0.01, ** p<0.05, * p<0.1
Table 4: Probability of having ever used commercial banks on demographic and socioeconomic
factors
Age
Male
Primary school
Secondary school
Tertiary school
Hhd head
2nd income quantile
(1)
(2)
(3)
(4)
0.0105***
(0.00272)
0.0719
(0.0662)
-0.208**
(0.0831)
-0.363***
(0.129)
-0.463***
(0.150)
0.357***
(0.119)
0.0827
(0.0776)
0.0109***
(0.00311)
0.0595
(0.0676)
-0.180**
(0.0856)
-0.259*
(0.131)
-0.372**
(0.158)
0.179
(0.122)
0.163*
(0.0828)
0.0278
(0.0775)
0.343***
(0.0787)
0.682***
(0.0987)
0.100
(0.143)
0.0622
(0.114)
-0.0469
(0.113)
-0.156
(0.0945)
0.532*
(0.294)
0.00978***
(0.00314)
0.0847
(0.0701)
-0.141
(0.0856)
-0.115
(0.134)
-0.200
(0.158)
-0.00187
(0.122)
0.175**
(0.0854)
0.0184
(0.0782)
0.274***
(0.0833)
0.574***
(0.103)
0.110
(0.149)
0.0585
(0.118)
-0.0302
(0.116)
-0.158
(0.0999)
0.401
(0.317)
0.734***
(0.0753)
-0.388***
(0.119)
-0.501***
(0.161)
-0.639***
(0.169)
0.00981***
(0.00345)
0.00635
(0.0747)
-0.145
(0.0893)
-0.0993
(0.145)
-0.103
(0.178)
-0.213
(0.132)
0.244***
(0.0926)
0.114
(0.0774)
0.275***
(0.0871)
0.546***
(0.105)
0.207
(0.150)
-0.144
(0.125)
0.120
(0.124)
-0.0198
(0.105)
0.398
(0.405)
0.588***
(0.0781)
0.610***
(0.140)
0.838***
(0.155)
0.883***
(0.142)
1.112***
(0.213)
1.559***
(0.271)
1.702***
(0.390)
0.0698***
(0.0209)
0.599***
(0.0773)
-1.912***
(0.250)
3rd income quantile

4th income quantile
Unemployed
Formally employed
Informally employed
Self-employed
Retired
Urban village
One media used
Two media used
Three media used
Four media used
Five media used
Six media used
HH size
Constant
Observations
3,000
2,758
2,758
df_m
7
15
16
F
8.580
10.13
14.68
60
2,572
24
11.72
Table 5: Probability of having ever used commercial bank services on village factors
(1)
Urban location
0.541**
(0.220)
0.296
(0.222)
-0.0982
(0.213)
-0.00401*
(0.00215)
0.00212
(0.00163)
-0.00205
(0.00197)
-0.0123***
(0.00195)
-0.292*
(0.149)
0.462***
(0.163)
0.0675
(0.0953)
0.432***
(0.155)
0.175
(0.119)
0.202**
(0.102)
0.125
(0.119)
-0.0431
(0.104)
0.142
(0.135)
0.102
(0.145)
0.477*
(0.253)
Peri-urban location
Rural location
Distance in min to primary school
Distance in min to clinic/hospital
Distance in min to bank
Distance in min to MFI
Most homes have electricity inside property
Most homes have piped water inside property
Water supply a problem to some extent
Water supply is not a problem
Unemployment a problem
Life in location has not changed from five years ago
Life in location is worse than five years ago
Normal dress standards in location
Middle income location (perceived)
Low income location (perceived)
Constant
Observations
df_m
F
61
2,625
17
37.90
Table 6: Probability of currently having a bank account on demographic and socioeconomic

factors
Age
Male
Primary school
Secondary school
Tertiary school
Hhd head
2nd income quantile
(1)
(2)
(3)
(4)
0.00126
(0.00313)
0.0735
(0.0653)
-0.218**
(0.103)
-0.414***
(0.135)
-0.523***
(0.158)
0.525***
(0.117)
0.0458
(0.0798)
0.00112
(0.00327)
0.0507
(0.0694)
-0.234**
(0.102)
-0.346**
(0.136)
-0.488***
(0.158)
0.413***
(0.119)
0.0716
(0.0825)
0.00981
(0.0916)
0.316***
(0.0997)
0.675***
(0.107)
0.124
(0.148)
0.222**
(0.0946)
-0.0462
(0.100)
-0.0192
(0.0890)
0.607**
(0.245)
-0.000703
(0.00326)
0.0758
(0.0723)
-0.193*
(0.104)
-0.216
(0.141)
-0.329**
(0.165)
0.242*
(0.123)
0.0933
(0.0820)
0.00422
(0.0936)
0.255**
(0.107)
0.573***
(0.108)
0.120
(0.153)
0.220**
(0.0956)
-0.0435
(0.101)
-0.0210
(0.0924)
0.511*
(0.266)
0.714***
(0.0711)
-0.742***
(0.152)
-0.925***
(0.182)
-1.070***
(0.184)
-0.00200
(0.00344)
0.0184
(0.0802)
-0.184*
(0.111)
-0.213
(0.155)
-0.265
(0.183)
0.0715
(0.134)
0.112
(0.0898)
0.157
(0.0972)
0.321***
(0.107)
0.570***
(0.112)
0.170
(0.165)
-0.0862
(0.107)
0.107
(0.110)
0.116
(0.100)
0.381
(0.279)
0.564***
(0.0797)
-0.142
(0.155)
-0.0544
(0.146)
-0.0521
(0.148)
0.312
(0.203)
0.463**
(0.225)
1.319***
(0.340)
0.0397*
(0.0201)
0.675***
(0.0802)
-1.413***
(0.230)
3rd income quantile

4th income quantile
Unemployed
Formally employed
Informally employed
Self-employed
Retired
Urban village
One media used
Two media used
Three media used
Four media used
Five media used
Six media used
HH size
1 = if income is stable
Constant
Observations
3,000
2,758
2,758
df_m
7
15
16
F
4.633
7.872
12.57
62
2,572
24
11.25
Table 7: Probability of currently having a bank loan on demographic and socioeconomic factors
Age
Male
Primary school
Secondary school
Tertiary school
Hhd head
2nd income quantile
(1)
(2)
(3)
(4)
0.00639*
(0.00344)
0.0735
(0.0865)
-0.110
(0.106)
-0.340**
(0.148)
-0.606***
(0.168)
0.378***
(0.130)
0.120
(0.0931)
0.00474
(0.00382)
0.0363
(0.0925)
-0.108
(0.118)
-0.332**
(0.162)
-0.600***
(0.185)
0.316**
(0.141)
0.218**
(0.103)
0.0378
(0.116)
0.270**
(0.128)
0.317***
(0.112)
-0.0452
(0.176)
-0.154
(0.122)
-0.130
(0.123)
-0.212*
(0.108)
0.457*
(0.265)
0.00356
(0.00388)
0.0518
(0.0936)
-0.0852
(0.120)
-0.259
(0.168)
-0.528***
(0.185)
0.206
(0.148)
0.230**
(0.103)
0.0426
(0.120)
0.233*
(0.135)
0.235**
(0.115)
-0.0450
(0.180)
-0.172
(0.124)
-0.133
(0.125)
-0.224**
(0.110)
0.398
(0.276)
0.426***
(0.0944)
-1.652***
(0.161)
-1.568***
(0.220)
-1.642***
(0.220)
0.00293
(0.00404)
0.0465
(0.0983)
-0.0840
(0.123)
-0.304*
(0.172)
-0.526***
(0.196)
0.0932
(0.148)
0.202*
(0.115)
0.133
(0.117)
0.266**
(0.133)
0.207*
(0.115)
-0.0880
(0.207)
-0.339***
(0.122)
-0.0552
(0.135)
-0.163
(0.120)
0.388
(0.299)
0.328***
(0.107)
-0.0388
(0.157)
0.0899
(0.160)
-0.0164
(0.168)
0.326
(0.243)
0.498**
(0.221)
0.530**
(0.264)
0.0134
(0.0203)
0.437***
(0.103)
-1.855***
(0.294)
3rd income quantile

4th income quantile
Unemployed
Formally employed
Informally employed
Self-employed
Retired
Urban village
One media used
Two media used
Three media used
Four media used
Five media used
Six media used
HH size
Constant
Observations
3,000
2,758
2,758
df_m
7
15
16
F
6.305
3.929
5.677
63
2,572
24
4.807
Table 8: Probability of having ever used insurance services on demographic and socioeconomic
factors
Age
Male
Primary school
Secondary school
Tertiary school
Hhd head
2nd income quantile
(1)
(2)
(3)
(4)
0.00468
(0.00355)
0.00603
(0.0826)
-0.297***
(0.100)
-0.263*
(0.145)
-0.540***
(0.178)
0.635***
(0.118)
-0.0447
(0.0929)
0.000921
(0.00406)
0.0233
(0.0832)
-0.343***
(0.107)
-0.335**
(0.158)
-0.689***
(0.189)
0.573***
(0.130)
0.0439
(0.105)
-0.586***
(0.104)
-0.130
(0.0937)
0.275***
(0.0889)
-0.168
(0.153)
0.207*
(0.119)
-0.516***
(0.124)
-0.377***
(0.105)
0.139
(0.284)
-7.49e-05
(0.00404)
0.0348
(0.0876)
-0.310***
(0.110)
-0.246
(0.162)
-0.587***
(0.195)
0.454***
(0.134)
0.0571
(0.108)
-0.594***
(0.106)
-0.185*
(0.100)
0.189**
(0.0926)
-0.176
(0.162)
0.203
(0.124)
-0.532***
(0.127)
-0.397***
(0.110)
0.0309
(0.279)
0.505***
(0.0744)
-1.215***
(0.161)
-0.674***
(0.202)
-0.769***
(0.201)
-0.000571
(0.00381)
-0.0483
(0.0940)
-0.326***
(0.112)
-0.160
(0.172)
-0.447**
(0.207)
0.185
(0.143)
0.0925
(0.106)
-0.261**
(0.107)
-0.0923
(0.102)
0.240**
(0.0971)
-0.0616
(0.164)
-0.220
(0.140)
-0.355**
(0.147)
-0.178
(0.122)
-0.212
(0.265)
0.271***
(0.0852)
0.379
(0.244)
0.585**
(0.238)
0.757***
(0.229)
0.970***
(0.278)
1.115***
(0.253)
0.567*
(0.337)
0.0687***
(0.0180)
1.355***
(0.0710)
-2.279***
(0.340)
3rd income quantile

4th income quantile
Unemployed
Formally employed
Informally employed
Self-employed
Retired
Urban village
One media used
Two media used
Three media used
Four media used
Five media used
Six media used
HH size
Constant
Observations
3,000
2,758
2,758
df_m
7
15
16
F
9.790
13.24
15.76
64
2,572
24
25.96
Table 9: Probability of having ever used MFI services on demographic and socioeconomic factors
Age
Male
Primary school
Secondary school
Tertiary school
Hhd head
2nd income quantile
(1)
(2)
(3)
(4)
-0.000990
(0.00291)
0.132*
(0.0700)
-0.100
(0.0834)
-0.0175
(0.126)
-0.294**
(0.146)
0.113
(0.113)
-0.0900
(0.0787)
-0.00202
(0.00322)
0.110
(0.0717)
-0.0216
(0.0908)
0.0916
(0.132)
-0.244
(0.159)
-0.0161
(0.116)
0.00734
(0.0865)
-0.190**
(0.0804)
0.204**
(0.0815)
0.282***
(0.0995)
-0.229
(0.164)
-0.109
(0.131)
-0.228**
(0.111)
-0.184*
(0.0996)
0.0251
(0.265)
-0.00277
(0.00317)
0.119
(0.0731)
-0.000286
(0.0901)
0.154
(0.134)
-0.170
(0.160)
-0.0960
(0.117)
0.0140
(0.0882)
-0.196**
(0.0800)
0.171**
(0.0839)
0.223**
(0.104)
-0.233
(0.167)
-0.114
(0.136)
-0.224**
(0.113)
-0.184*
(0.101)
-0.0317
(0.264)
0.329***
(0.0728)
-0.323**
(0.132)
-0.197
(0.176)
-0.252
(0.176)
-0.00288
(0.00324)
0.0690
(0.0686)
0.0321
(0.0946)
0.235
(0.151)
-0.0232
(0.180)
-0.294**
(0.129)
0.0790
(0.0847)
-0.0763
(0.0865)
0.187**
(0.0845)
0.227**
(0.103)
-0.113
(0.163)
-0.391***
(0.135)
-0.0576
(0.112)
-0.0383
(0.106)
-0.0946
(0.263)
0.177**
(0.0680)
0.319**
(0.145)
0.478***
(0.153)
0.693***
(0.159)
0.691***
(0.188)
0.645***
(0.203)
-0.0427
(0.277)
0.0297*
(0.0179)
0.820***
(0.0672)
-1.115***
(0.262)
3rd income quantile

4th income quantile
Unemployed
Formally employed
Informally employed
Self-employed
Retired
Urban village
One media used
Two media used
Three media used
Four media used
Five media used
Six media used
HH size
Constant
Observations
3,000
2,758
2,758
df_m
7
15
16
F
2.827
3.519
4.354
65
2,572
24
10.08
Table 10: Probability of having ever used money changers on demographic and socioeconomic
factors
Age
Male
Primary school
Secondary school
Tertiary school
Hhd head
2nd income quantile
(1)
(2)
(3)
(4)
0.00814**
(0.00344)
0.0252
(0.0763)
0.0369
(0.0984)
0.0157
(0.128)
-0.219
(0.145)
0.385***
(0.112)
-0.0166
(0.0914)
0.00631*
(0.00373)
0.0216
(0.0805)
0.0451
(0.101)
0.0579
(0.129)
-0.235
(0.152)
0.296**
(0.114)
0.0470
(0.0984)
-0.153*
(0.0893)
0.0515
(0.0969)
0.353***
(0.101)
0.0272
(0.164)
-0.0118
(0.116)
-0.213*
(0.117)
-0.129
(0.0978)
0.228
(0.252)
0.00550
(0.00373)
0.0348
(0.0843)
0.0736
(0.103)
0.138
(0.131)
-0.143
(0.151)
0.194*
(0.116)
0.0578
(0.103)
-0.159*
(0.0922)
0.00525
(0.103)
0.272***
(0.103)
0.0316
(0.170)
-0.0117
(0.119)
-0.211*
(0.120)
-0.129
(0.101)
0.159
(0.257)
0.418***
(0.0790)
-1.328***
(0.162)
-1.186***
(0.202)
-1.271***
(0.203)
0.00642
(0.00393)
0.00163
(0.0813)
0.129
(0.108)
0.251*
(0.135)
-0.0186
(0.156)
-0.0713
(0.123)
0.0789
(0.0981)
0.0205
(0.0893)
0.0430
(0.103)
0.274**
(0.107)
0.115
(0.172)
-0.359***
(0.126)
-0.0709
(0.127)
0.0130
(0.107)
0.128
(0.294)
0.226**
(0.0900)
0.544***
(0.198)
0.621***
(0.191)
0.714***
(0.197)
1.108***
(0.231)
0.936***
(0.235)
1.597***
(0.300)
0.0149
(0.0194)
0.757***
(0.0858)
-2.252***
(0.334)
3rd income quantile

4th income quantile
Unemployed
Formally employed
Informally employed
Self-employed
Retired
Urban village
One media used
Two media used
Three media used
Four media used
Five media used
Six media used
HH size
Constant
Observations
3,000
2,758
2,758
df_m
7
15
16
F
4.650
3.743
6.470
66
2,572
24
11.38
Table 11: Probability of having ever used money lenders on demographic and socioeconomic
factors
Age
Male
Primary school
Secondary school
Tertiary school
Hhd head
2nd income quantile
(1)
(2)
(3)
(4)
0.00471*
(0.00284)
0.00823
(0.0692)
-0.271***
(0.0905)
-0.309**
(0.119)
-0.640***
(0.151)
0.204*
(0.106)
0.0653
(0.0793)
0.00439
(0.00302)
0.00116
(0.0726)
-0.245**
(0.100)
-0.272**
(0.131)
-0.633***
(0.160)
0.143
(0.110)
0.103
(0.0866)
-0.272***
(0.0717)
-0.0558
(0.0805)
0.0220
(0.0868)
-0.0527
(0.165)
0.117
(0.128)
-0.217**
(0.109)
-0.194**
(0.0974)
-0.313
(0.240)
0.00377
(0.00300)
0.00868
(0.0731)
-0.225**
(0.0999)
-0.211
(0.130)
-0.564***
(0.155)
0.0645
(0.107)
0.109
(0.0873)
-0.277***
(0.0714)
-0.0895
(0.0844)
-0.0375
(0.0914)
-0.0518
(0.168)
0.116
(0.131)
-0.212*
(0.110)
-0.193*
(0.0982)
-0.370
(0.241)
0.302***
(0.0706)
-0.311**
(0.129)
-0.0740
(0.166)
-0.123
(0.165)
0.00422
(0.00310)
-0.0619
(0.0684)
-0.230**
(0.108)
-0.196
(0.140)
-0.524***
(0.171)
-0.108
(0.120)
0.114
(0.0888)
-0.124
(0.0766)
-0.0773
(0.0867)
-0.109
(0.0941)
0.0854
(0.178)
-0.252*
(0.133)
-0.0402
(0.114)
-0.00959
(0.0959)
-0.483*
(0.247)
0.101
(0.0726)
0.506***
(0.146)
0.564***
(0.144)
0.565***
(0.151)
0.748***
(0.196)
1.057***
(0.212)
1.494***
(0.299)
0.0255
(0.0204)
0.993***
(0.0673)
-1.063***
(0.223)
3rd income quantile

4th income quantile
Unemployed
Formally employed
Informally employed
Self-employed
Retired
Urban village
One media used
Two media used
Three media used
Four media used
Five media used
Six media used
HH size
Constant
Observations
3,000
2,758
2,758
df_m
7
15
16
F
5.280
5.493
5.991
67
2,572
24
15.09
Table 12: Probability of having ever had a formal account on demographic and socioeconomic
factors
Age
Male
Primary school
Secondary school
Tertiary school
Hhd head
2nd income quantile
(1)
(2)
(3)
(4)
0.0130***
(0.00276)
0.0716
(0.0617)
-0.210**
(0.0862)
-0.326**
(0.129)
-0.480***
(0.150)
0.356***
(0.118)
0.0576
(0.0735)
0.0138***
(0.00337)
0.0831
(0.0656)
-0.194**
(0.0904)
-0.233*
(0.136)
-0.414***
(0.158)
0.195
(0.121)
0.0995
(0.0781)
0.0145
(0.0761)
0.318***
(0.0792)
0.551***
(0.0972)
0.202
(0.145)
0.177
(0.108)
0.00200
(0.108)
-0.103
(0.0883)
0.371
(0.278)
0.0130***
(0.00344)
0.108
(0.0681)
-0.156*
(0.0907)
-0.0911
(0.138)
-0.251
(0.158)
0.0174
(0.122)
0.110
(0.0805)
0.00581
(0.0759)
0.253***
(0.0820)
0.448***
(0.100)
0.212
(0.150)
0.173
(0.110)
0.0163
(0.107)
-0.107
(0.0908)
0.228
(0.293)
0.717***
(0.0733)
-0.513***
(0.123)
-0.661***
(0.166)
-0.806***
(0.175)
0.0136***
(0.00376)
0.0300
(0.0731)
-0.155*
(0.0934)
-0.0760
(0.154)
-0.139
(0.185)
-0.189
(0.138)
0.181**
(0.0888)
0.0954
(0.0789)
0.253***
(0.0865)
0.379***
(0.111)
0.329**
(0.154)
-0.0474
(0.113)
0.182
(0.118)
0.0452
(0.0975)
0.314
(0.368)
0.571***
(0.0770)
0.564***
(0.144)
0.813***
(0.151)
0.890***
(0.145)
1.163***
(0.204)
1.284***
(0.219)
0.0639***
(0.0185)
0.646***
(0.0801)
-2.062***
(0.256)
3rd income quantile

4th income quantile
Unemployed
Formally employed
Informally employed
Self-employed
Retired
Urban village
One media used
Two media used
Three media used
Four media used
Five media used
Six media used
HH size
Constant
3,000
2,758
2,758
7
15
16
Observations
10.03
8.656
14.25
68
2,525
23
11.23
2. Financial Capability
Table 13: Probability of financial literacy and financial product knowledge scores on village
factors
Urban location
Peri-urban location
Rural location
Distance in min to primary school
Distance in min to clinic/hospital
Distance in min to bank
Distance in min to MFI
Most homes do not have electricity inside
property
Most homes do not have piped water inside
property
Water supply is a problem to some extent
Water supply is not a problem
Unemployment is a problem to some extent
Crime is a problem to some extent
Crime is not a problem
Life in location has not changed from 5 years
ago
Life in location is worse than 5 years ago
Normal dress standards in location
Middle income location (perceived)
Low income location (perceived)
Constant
(1)
(2)
0.00816
(0.0520)
-0.0314
(0.0977)
-0.0350
(0.0546)
0.000841
(0.000597)
-0.00106***
(0.000387)
-0.00111**
(0.000515)
0.00173***
(0.000515)
0.0337
-0.0308
(0.0934)
0.118
(0.107)
-0.173*
(0.0961)
-0.00126
(0.00110)
0.00111
(0.000924)
-5.62e-05
(0.00105)
-0.00725***
(0.00109)
-0.0427
(0.0392)
-0.0247
(0.0593)
0.124
(0.0457)
0.0305
(0.0205)
-0.0220
(0.0397)
-0.0155
(0.0289)
-0.114***
(0.0264)
0.0461
(0.0321)
-0.0454*
(0.0932)
-0.0165
(0.0459)
0.0185
(0.0790)
0.0595
(0.0629)
0.0616
(0.0510)
0.197***
(0.0715)
0.0648
(0.0261)
-0.0366
(0.0426)
0.00368
(0.0234)
0.0105
(0.0333)
0.0510
(0.0385)
1.336***
(0.0512)
(0.0581)
0.0494
(0.0678)
-0.0438
(0.0471)
-0.265***
(0.0761)
-0.280***
(0.0786)
1.829***
(0.138)
Observations
2,534
df_m
19
F
6.031
Estimates of the poisson model. Standard errors in parentheses. *** p<0.01, ** p<0.05, * p<0.1
69
2,625
19
32.65
Table 14: Probability of financial literacy score on demographic and socioeconomic factors
age
male
Primary school
Secondary school
Tertiary school
Hhd head
2nd income quantile
(1)
(2)
(3)
(4)
0.00167
(0.00106)
0.0175
(0.0193)
0.0433
(0.0288)
0.141***
(0.0409)
0.252***
(0.0448)
-0.0312
(0.0380)
0.00224
(0.0271)
0.00221*
(0.00119)
0.0171
(0.0200)
0.0199
(0.0328)
0.133***
(0.0423)
0.239***
(0.0477)
-0.0155
(0.0367)
-0.0132
(0.0295)
0.0261
(0.0250)
0.0340
(0.0271)
0.0314
(0.0287)
0.0175
(0.0410)
0.104***
(0.0346)
-0.0242
(0.0319)
0.00386
(0.0258)
-0.105
(0.0982)
-0.131***
(0.0264)
0.00213*
(0.00117)
0.0179
(0.0200)
0.0221
(0.0327)
0.139***
(0.0423)
0.246***
(0.0480)
-0.0231
(0.0362)
-0.0122
(0.0294)
0.0242
(0.0249)
0.0296
(0.0267)
0.0243
(0.0278)
0.0165
(0.0412)
0.106***
(0.0346)
-0.0246
(0.0318)
0.00315
(0.0259)
-0.108
(0.0995)
-0.139***
(0.0269)
0.0364*
(0.0212)
1.172***
(0.0484)
1.159***
(0.0642)
1.156***
(0.0643)
0.00215*
(0.00117)
0.0176
(0.0201)
0.0185
(0.0327)
0.127***
(0.0421)
0.236***
(0.0470)
-0.0138
(0.0354)
-0.0145
(0.0298)
0.0228
(0.0249)
0.0287
(0.0266)
0.0169
(0.0287)
0.0169
(0.0419)
0.102***
(0.0351)
-0.0211
(0.0318)
0.00447
(0.0262)
-0.106
(0.0993)
-0.124***
(0.0277)
0.0374*
(0.0218)
0.0563*
(0.0307)
0.0566
(0.0398)
0.0158
(0.0359)
0.0332
(0.0386)
0.0410
(0.0553)
0.0699
(0.0504)
0.139*
(0.0767)
1.070***
(0.0781)
3rd income quantile

4th income quantile
Unemployed
Formally employed
Informally employed
Self-employed
Retired
Urban village
Saved as a child
One media used
Two media used
Three media used
Four media used
Five media used
Six media used
Constant
Observations
2,898
2,488
2,488
df_m
7
16
17
F
11.57
5.836
5.501
70
2,488
24
4.438
Table 15: Probability of financial knowledge score on demographic and socioeconomic factors
age
male
Primary school
Secondary school
Tertiary school
Hhd head
2nd income quantile
(1)
(2)
(3)
(4)
0.00542***
(0.00132)
0.0168
(0.0346)
-0.0919**
(0.0396)
-0.116*
(0.0598)
-0.246***
(0.0715)
0.229***
(0.0587)
0.0351
(0.0364)
0.00439***
(0.00128)
-0.00895
(0.0302)
-0.0747*
(0.0379)
-0.0176
(0.0594)
-0.184***
(0.0700)
0.0669
(0.0589)
0.0766**
(0.0312)
-0.00976
(0.0358)
0.0792**
(0.0359)
0.177***
(0.0370)
0.0548
(0.0554)
-0.144***
(0.0486)
-0.0218
(0.0487)
-0.0760*
(0.0427)
-0.110
(0.0801)
0.440***
(0.0270)
0.00385***
(0.00125)
-0.00391
(0.0309)
-0.0611
(0.0379)
0.0151
(0.0596)
-0.143**
(0.0681)
0.0218
(0.0591)
0.0835**
(0.0325)
-0.0180
(0.0362)
0.0554
(0.0370)
0.137***
(0.0377)
0.0488
(0.0584)
-0.125***
(0.0476)
-0.0265
(0.0486)
-0.0828*
(0.0432)
-0.131*
(0.0750)
0.400***
(0.0255)
0.200***
(0.0287)
0.915***
(0.0645)
0.854***
(0.0747)
0.839***
(0.0754)
0.00403***
(0.00123)
-0.00657
(0.0304)
-0.0569
(0.0380)
0.0170
(0.0599)
-0.136*
(0.0692)
-0.0441
(0.0610)
0.0837***
(0.0316)
-0.0138
(0.0370)
0.0467
(0.0358)
0.115***
(0.0369)
0.0509
(0.0586)
-0.121**
(0.0471)
-0.0198
(0.0476)
-0.0838**
(0.0423)
-0.0784
(0.0723)
0.358***
(0.0257)
0.157***
(0.0270)
-0.0411
(0.0368)
0.280***
(0.0943)
0.365***
(0.0939)
0.427***
(0.0986)
0.498***
(0.0982)
0.522***
(0.103)
0.682***
(0.104)
0.579***
(0.126)
3rd income quantile

4th income quantile
Unemployed
Formally employed
Informally employed
Self-employed
Retired
Urban village
Saved as a child
One media used
Two media used
Three media used
Four media used
Five media used
Six media used
Constant
Observations
3,000
2,572
2,572
df_m
7
16
17
F
9.109
25.66
25.81
71
2,572
24
23.18
Table 16: Capability of covering unexpected expenses on demographic and socioeconomic factors
age
male
Primary school
Secondary school
Tertiary school
Hhd head
2nd income quantile
(1)
(2)
(3)
(4)
0.117*
(0.0646)
1.255
(1.500)
-1.767
(2.200)
0.0463
(3.342)
0.636
(3.977)
1.882
(2.841)
2.465
(1.632)
0.135*
(0.0736)
1.099
(1.656)
-0.793
(2.223)
1.093
(3.604)
1.645
(4.253)
0.868
(3.057)
2.188
(1.939)
6.330***
(1.850)
7.044***
(2.081)
4.503*
(2.325)
1.730
(3.591)
-1.176
(2.813)
-0.115
(2.476)
3.199
(2.192)
6.275
(6.613)
5.586***
(2.082)
0.114
(0.0739)
1.293
(1.638)
-0.306
(2.210)
2.432
(3.582)
3.270
(4.252)
-0.815
(3.076)
2.408
(1.902)
5.930***
(1.861)
6.046***
(2.076)
2.896
(2.398)
1.478
(3.589)
-0.538
(2.836)
-0.239
(2.501)
3.003
(2.245)
5.391
(6.323)
3.956*
(2.039)
8.236***
(1.500)
54.43***
(3.148)
47.08***
(3.903)
46.50***
(3.891)
0.0853
(0.0759)
1.498
(1.718)
-0.857
(2.356)
1.764
(3.638)
2.141
(4.329)
-1.425
(3.123)
2.785
(1.987)
5.530***
(1.911)
5.640***
(2.104)
2.221
(2.448)
0.925
(3.615)
-1.253
(2.923)
-1.155
(2.587)
2.537
(2.357)
7.136
(6.564)
4.230*
(2.232)
7.424***
(1.596)
-0.189
(0.473)
3.939
(3.045)
2.488
(3.246)
5.659*
(3.108)
2.645
(3.521)
7.455
(4.906)
9.829*
(5.245)
11.07
(7.528)
42.31***
(5.417)
3rd income quantile

4th income quantile
Unemployed
Formally employed
Informally employed
Self-employed
Retired
Urban village
Financial literacy score
Saved as a child
One media used
Two media used
Three media used
Four media used
Five media used
Six media used
Constant
Observations
2,996
2,568
2,568
df_m
7
16
17
F
2.407
3.055
5.494
Estimates of the regression model. Standard errors in parentheses. *** p<0.01, ** p<0.05, * p<0.1
72
2,484
25
4.412
Table 17: Satisfaction rate on commercial banks on demographic and socioeconomic factors
(1)
age
male
Primary school
Secondary school
Tertiary school
Hhd head
2nd income quantile
3rd income quantile
4th income quantile
Unemployed
Formally employed
Informally employed
Self-employed
Retired
Urban village
Financial literacy score
Saved as a child
One media used
Two media used
Three media used
Four media used
Five media used
Six media used
Constant
0.00239
(0.00399)
0.0751
(0.0996)
-0.0300
(0.132)
-0.0134
(0.195)
0.0658
(0.222)
0.153
(0.181)
0.0160
(0.113)
0.152
(0.125)
0.127
(0.115)
0.0760
(0.124)
0.217
(0.183)
0.0618
(0.166)
-0.0456
(0.148)
0.184
(0.138)
0.779**
(0.348)
-0.212**
(0.106)
0.0231
(0.0815)
0.0608**
(0.0289)
-0.243**
(0.113)
0.141
(0.259)
-0.0413
(0.266)
-0.0870
(0.282)
0.350
(0.300)
-0.000557
(0.305)
0.679*
(0.353)
-0.414
(0.365)
Observations
1,458
df_m
25
F
3.092
73
Table 18: Probability of using financial instruments on demographic and socioeconomic factors
(1)
(2)
(3)
Insurance products Bank credit
Bank savings
Financial literacy index
-0.0109
-0.00364
0.0162
(0.0252)
(0.0332)
(0.0288)
Awareness of financial products index
0.271***
0.244***
0.262***
(0.0236)
(0.0329)
(0.0233)
Budgeting
0.000895
-0.00169
-0.00133
(0.00142)
(0.00139)
(0.00146)
Living within means
-0.000381
-7.82e-05
0.00144
(0.00134)
(0.00137)
(0.00135)
Not over-spending
0.000481
0.000529
0.00170*
(0.000995)
(0.00115)
(0.000919)
Monitor expenses
-0.00254**
0.00440**
0.00335**
(0.00128)
(0.00191)
(0.00154)
Attitudes towards info
-0.00257
-0.000764
-0.00195
(0.00180)
(0.00189)
(0.00199)
Planning unexpected
-0.000400
-0.000883
0.00160
(0.00120)
(0.00124)
(0.00132)
Saving for the future
6.20e-05
0.000580
0.000718
(0.00118)
(0.00144)
(0.00130)
Far sightedness
0.000612
0.00354*
0.00176
(0.00167)
(0.00201)
(0.00194)
Provisions for old age
-0.000893
-0.000626
0.00176
(0.00113)
(0.00146)
(0.00112)
Age
-0.00117
-0.00231
-0.00325
(0.00404)
(0.00508)
(0.00491)
Male
-0.120
0.0388
0.101
(0.0930)
(0.111)
(0.0975)
Primary school
0.205*
0.0908
-0.213
(0.124)
(0.146)
(0.132)
Secondary school
0.248
0.00907
-0.225
(0.172)
(0.186)
(0.194)
Tertiary school
0.311
-0.264
-0.100
(0.189)
(0.212)
(0.232)
-0.270*
-0.113
0.181
(0.140)
(0.153)
(0.150)
Hhd head
0.0627
0.299**
-0.176
(0.109)
(0.129)
(0.114)
(0.108)
(0.123)
(0.129)
Constant
-1.603***
-2.780***
-2.837***
(0.355)
(0.430)
(0.366)
Observations
2,482
2,482
2,474
df_m
35
35
34
F
7.576
5.159
11.30
74
(4)
Money transfers
0.0280
(0.0269)
0.365***
(0.0209)
-0.00330***
(0.00119)
-0.000749
(0.00127)
0.00121
(0.000941)
-0.00123
(0.00139)
0.00144
(0.00151)
0.000757
(0.00104)
0.00133
(0.00130)
-0.00582***
(0.00168)
0.00199**
(0.00100)
0.0166***
(0.00438)
-0.00284
(0.0884)
0.128
(0.103)
-0.0795
(0.159)
-0.0841
(0.195)
-0.207
(0.151)
0.198**
(0.0938)
(0.112)
-4.194***
(0.513)
2,482
35
16.48
Table 19: Probability of using financial instruments on financial capability scores

(5)
Credit from MFI
(6)
(7)
Community
Informal credit
based savings
Financial literacy index
0.0523*
-0.0293
-0.0261
(0.0289)
(0.0271)
(0.0302)
Awareness of financial products index
0.248***
0.290***
0.196***
(0.0215)
(0.0184)
(0.0208)
Budgeting
0.000870
-0.00140
-0.00118
(0.00151)
(0.00142)
(0.00113)
Living within means
-0.00416**
0.000319
-0.00439***
(0.00165)
(0.00117)
(0.00117)
Not over-spending
0.00193*
0.00163**
-0.00200**
(0.00105)
(0.000812)
(0.000932)
Monitor expenses
-6.64e-05
-0.00100
-0.000301
(0.00161)
(0.00133)
(0.00138)
Attitudes towards info
-0.00309*
-0.00121
0.000471
(0.00187)
(0.00175)
(0.00153)
Planning unexpected
0.000218
0.000770
-0.000919
(0.00136)
(0.00118)
(0.00134)
Saving for the future
0.000947
-0.000912
0.00219*
(0.00176)
(0.00120)
(0.00119)
Far sightedness
-0.000345
-0.00163
0.00410**
(0.00190)
(0.00182)
(0.00166)
Provisions for old age
0.000987
0.000685
-0.00483***
(0.00122)
(0.00102)
(0.00116)
Age
-0.00845
-0.00989**
-0.00486
(0.00567)
(0.00395)
(0.00409)
Male
-0.128
-0.00643
-0.226**
(0.117)
(0.0848)
(0.0892)
Primary school
-0.0513
-0.0534
-0.252**
(0.131)
(0.103)
(0.119)
Secondary school
0.0165
0.106
-0.210
(0.195)
(0.172)
(0.178)
Tertiary school
-0.189
-0.0364
-0.430**
(0.232)
(0.196)
(0.205)
-0.187
-0.466***
-0.116
(0.173)
(0.163)
(0.142)
Hhd head
-0.0317
0.0244
0.0402
(0.131)
(0.104)
(0.105)
(0.113)
(0.119)
(0.113)
Constant
-1.849***
-1.404***
-0.717**
(0.481)
(0.426)
(0.355)
Observations
2,425
2,482
2,482
df_m
33
35
35
F
10.41
12.10
13.42
75
(8)
Informal savings
-0.0352
(0.0220)
0.361***
(0.0172)
0.00155
(0.00103)
-0.000225
(0.00117)
0.00181**
(0.000723)
0.00100
(0.00116)
-0.000245
(0.00137)
7.80e-05
(0.00110)
-0.000889
(0.00112)
-0.00182
(0.00156)
-0.00208**
(0.000805)
0.00118
(0.00371)
-0.162**
(0.0765)
-0.0605
(0.0968)
0.0768
(0.143)
-0.144
(0.162)
-0.128
(0.124)
0.0748
(0.0834)
(0.0964)
-0.839***
(0.312)
2,482
35
17.22

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Financial Inclusion and Capability Survey Report

Financial Inclusion Practice

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The corresponding lead author can be contacted at: szottel@worldbank.org

Usage of Banks ........................................................................................................................... 17

Usage of Bank Products .............................................................................................................. 20

Usage of Nonbank Financial Institutions ...................................................................................... 23

Usage of Products of Nonbank Financial Institutions ................................................................... 25

Barriers to Formal Account Ownership ........................................................................................ 26

Background on the Mozambique Survey ......................................................................................... 55

Financial Inclusion ........................................................................................................................... 57

Regression Tables ........................................................................................................................... 59

Financial Inclusion ....................................................................................................................... 59

Figure 38: Estimated population break-down by urban/rural ...................................................................... 55

Abbreviations and Acronyms

Alliance for Financial Inclusion

The delivery of financial services outside conventional bank

Savings and credit self-help groups such as ASCAs, OPEs,

The capacity to act in ones best financial interest, given

Financial Inclusion is defined as proportion of individuals who use

Any public or private institution whose main function is the provision

The totality of financial institutions that operate in Mozambique. This

In this report, the definition of financial system is equivalent to the

Financial institutions that are licensed by and prudentially

Financial institutions that are not registered with or officially

recognized by any government authority, e.g. unregistered money

Key Facts Statement

A summary statement which provides consumers with simple and

Financial institutions that target poor and low-income persons as

Protection of low-income people against specific perils in exchange

A money changer is a person who exchanges the coins or currency

A money lender is an informal lender, either person or a group

A Financial Institution that provides financial services without

Times in people's lives when they are more likely to be receptive to

Summary of Key Recommendations

Use a wide range of programs, including mass

BdM, Ministry of Finance,

This number includes credit from banks and MFIs.

Relationship between Financial Inclusion

Financial Consumer Protection

Background on the Mozambique Survey

Population aged 18 and older

1.2 Usage of Banks

Source: WB Financial Capability Survey, Mozambique 2013

Source: WB Financial Capability Survey, Mozambique 2013

Figure 3: Knowledge and usage of commercial banks by degree of media consumption11

Source: WB Financial Capability Survey, Mozambique 2013.

Source: WB Financial Capability Survey, Mozambique 2013.

1.3 Usage of Bank Products

Figure 5: Bank account penetration in different regions in Mozambique

Source: WB Financial Capability Survey, Mozambique 2013

Source: WB Financial Capability Survey, Mozambique 2013

Source: WB Financial Capability Survey, Mozambique 2013

Source: WB Financial Capability Survey, Mozambique 2013

Source: WB Financial Capability Survey, Mozambique 2013

1.4 Usage of Nonbank Financial Institutions

Source: WB Financial Capability Survey, Mozambique 2013

Source: WB Financial Capability Survey, Mozambique 2013

1.5 Usage of Products of Nonbank Financial

Figure 12: Usage of financial products in rural and urban areas