DSS in Banks
DSS in Banks
DSS in Banks
Abstract
The main purpose of this research is to use Hermeneutic research approach to find out
how Decision Support System (DSS) is used in banks and financial services. The research
started from one stance, from which the further process could be extended to reach more
complete picture of Decision Support System’s usage in strategic decision makings in
banks. The research is also trying to find out the drawbacks and benefits of the DSS which
have been used nowadays in banks. Furthermore, the future improvements of using DSS to
make better decisions related with moral and different environments are also being dis-
cussed in the research findings.
During the primary data collection, resources from different channels have been used to
support the research. The primary data sources include lectures and discussion in three
banks’ visiting opportunities in Stockholm, Sweden, one interview with IT Vice president
from Bank of America Merrill Lynch, New York, two interviews with a professor and a di-
rector respectively from Lund University and Financial Services Innovation Centre in Uni-
versity College Cork, Ireland.
Experiences from both academic and practical have been shared to strength the research’s
validity and trustworthiness. Hermeneutic research approach addresses through the whole
research process which needs to be open-minded and flexible.
Unawareness of DSS for people who are working in banks is one of the issues today. Dif-
ferent embedded models regarding various functions are not so clear to bank staff; thus
there is a gap between human decisions and system decisions. There is a variation of re-
quirements between central banks, retail banks, commercial banks, investment banks.
Hence there should be a differentiation when implementing a system. Banking systems are
widespread systems which are influenced by environment factors, political, economic, so-
cio-cultural and technological variables.
Acknowledgement
The completion of this thesis would never happen with only the sole individual author.
Here I would like to sincerely show my appreciation to the individuals without whom
this thesis would be no means to be accomplished.
Special thanks to my tutor Jörgen Lindh, the inspirations, encouragement and the
lightening up of my confidence to carry on the research throughout the whole processes,
and the showing of the true meaning of the research is not only about finding the re-
sult but also confronting and solving the difficulties throughout the whole processes.
And to Ulf Larsson, my other tutor who gave me so much encouragement and thanks
to his patience and kindness to support me all the time.
Many thanks to Professor Sven Carlsson who provide such great information during
the time when the process got stuck. To JB McCarthy, development director from Fi-
nancial Services Innovation Centre from University College Cork, Ireland who provide
selfless help with the interview and their research papers.
To my previous working partner provide valuable information about Bank of America
Merrill Lynch, New York. Thanks to Jönköping International Business School Trad-
ing Room and SIFE Jönköping for providing me the bank trip.
Thanks to my seniors and friends Mágdala Leung and Mingming Jiang who gave me
great encouragement during my downtime. My colleagues and peers also deserve men-
tion for their constructive critique to make this thesis better. Last but not the least, I
would appreciate my parents and my family for their unconditional love and support
all the time.
Yanwei Mao
Table of Contents
1 Introduction ............................................................................ 1
1.1 Background ................................................................................... 1
1.2 Problem ......................................................................................... 2
1.3 Purpose ......................................................................................... 3
1.4 Research questions....................................................................... 3
1.5 Limitations ..................................................................................... 3
1.6 Interested parties........................................................................... 4
1.7 Definition ....................................................................................... 4
2 Method .................................................................................... 5
2.1 Research philosophy ..................................................................... 5
2.1.1 Epistemology ...................................................................... 5
2.2 Research design ........................................................................... 5
2.2.1 Interpretivist research designs ............................................ 5
2.2.2 Research design steps ....................................................... 5
2.2.3 Qualitative research ............................................................ 7
2.3 Research approach ....................................................................... 7
2.3.1 Hermeneutic ....................................................................... 7
2.3.1.1 Part and whole .................................................................................................. 8
2.3.1.2 Preunderstanding and understanding ............................................................. 8
2.3.2 Hermeneutical interpretation ............................................... 8
2.3.2.1 Pattern of interpretation.................................................................................... 9
2.3.2.2 Text .................................................................................................................... 9
2.3.2.3 Dialogue ............................................................................................................. 9
2.3.2.4 Sub-interpretation ........................................................................................... 10
2.3.3 Hermeneutic Summary ..................................................... 10
2.4 Data collection ............................................................................. 10
2.4.1 Qualitative Data ................................................................ 11
2.4.1.1 Possible primary data sources ........................................................................ 11
2.4.1.2 Secondary data ................................................................................................ 11
2.5 Interview ...................................................................................... 12
2.5.1 Interview with Swedish banks ........................................... 12
2.5.2 Interview with Professor Sven Carlsson ........................... 13
2.5.3 Interview with JB McCarthy .............................................. 13
2.5.4 Interview with Bank of America Merrill Lynch ................... 13
2.5.5 Summary .......................................................................... 13
2.6 Credibility of research findings .................................................... 13
2.6.1 Validity .............................................................................. 13
2.6.2 Reliability .......................................................................... 14
2.7 Analysis process ......................................................................... 14
3 Frame of reference .............................................................. 15
3.1 Introduction of DSS ..................................................................... 16
3.1.1 Umbrella terms for DSS .................................................... 16
3.1.2 Alter’s types of decision support ....................................... 16
3.1.3 Possible sources of better decision support ..................... 16
3.2 Decision support frameworks ...................................................... 17
3.2.1 The steps of Decision Support .......................................... 18
3.3 Decision making processes ......................................................... 18
3.3.1 Decision making procedures by Robert Harries................ 19
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3.4 PEST analysis model .................................................................. 20
3.5 Banking Structure in US .............................................................. 21
3.6 An example of decision support system – Datscha ..................... 22
4 Empirical results .................................................................. 23
4.1 Interviews with Swedish banks .................................................... 23
4.1.1 Lecture findings ................................................................ 23
4.1.2 Discussions ...................................................................... 24
4.2 Bank of America Merrill Lynch ..................................................... 24
4.3 Financial Services Innovation Centre .......................................... 25
4.3.1 DSS in financial sectors in general ................................... 25
4.3.2 DSS’s usage in different sectors ....................................... 25
4.3.3 Future perspective about DSS in financial sectors ........... 26
4.4 DSS professor Sven Carlsson ..................................................... 26
4.4.1 General perspectives about DSS...................................... 26
4.4.2 Key factors of using DSS .................................................. 27
4.4.3 DSS regarding financial sector ......................................... 27
4.5 Summary of data findings ............................................................ 28
5 Analysis ................................................................................ 29
5.1 DSS in banks’ usage and purpose .............................................. 29
5.2 How is DSS used in different levels in banks? ............................ 30
5.3 Benefits and drawbacks of using DSS ........................................ 31
5.4 More contributions to research purpose ...................................... 31
5.4.1 Risk management and DSS ............................................. 31
5.4.2 More factors to be considered during decision
making in banks .......................................................................... 32
5.4.3 Future perspective and improvement regarding
DSS in banks .............................................................................. 33
6 Conclusion ........................................................................... 34
7 Reflections ........................................................................... 35
8 Future research ................................................................... 36
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Figures
Figure 2-1 Qualitative research design ................................................................ 6
Figure 2-2 The Hermeneutic circle: basic version ................................................. 7
Figure 3-1 Main structure of frame of reference ................................................. 15
Figure 3-2 Decision Support Frameworks ......................................................... 17
Figure 3-3 The steps of Decision Support ......................................................... 18
Figure 3-4 PEST Analysis Framework .............................................................. 21
Figure 3-5 The process of Financial Intermediation ............................................ 22
Appendix
Appendix 1 – Interview questions................................................................. 40
Appendix 2 – Biography of Sven Carlsson ................................................... 41
Appendix 3 – Introduction of Financial Services Innovation Centre ............. 43
Appendix 4 – Risk Assessment Glossary ..................................................... 44
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1 Introduction
Every day, in different sectors, around the world, a lot of decisions need to be taken. Small
decisions to individuals are whether they should eat rice or noodles. Big decisions to coun-
tries can be if, a person should be elected as president or not. Better decision will change
small things in an individual’s life; big ones may even have impact on a country’s future.
Davenport (2009), gives couple of examples of such: the decision to invade Iraq, not use
resources to solve global warming threats etc, all seem to be written in the shameful page
of the history book.
The history of the term decision making could be dated back to the middle of the past cen-
tury. Telephone executive Chester Barnard takes ‘decision making’ from public administra-
tion into the business world (Buchanan & Connell, 2006).
In the business world, decision making is a special art which includes three different levels
which are operational, tactical and strategic (Harris, 2009). These three levels of decision
makings are dealing with different pictures of the business, from everyday operational rou-
tine decisions to non-routine long term decisions.
1.1 Background
Decision making is based on information that the decision maker is gathering. Therefore,
in our planet the fastest growing activity is the amount of information that we are generat-
ing every day, every hour, every minute. Expanding rate of information is and has been
faster than anything else that could be measured over the scale of decades (Kelly, 2006).
There are some decision support systems which are computer-based Information Systems
(IS) that provide the best practical ways to approach the capture, management and exploi-
tation of information which would be essential for the business needs (Kuljis, Macredie &
Paul, 1999).
Decision Support System (DSS) has been developing for almost 40 years by different re-
searchers and technologists mainly within IS area. Explained by Power in 2007, in the his-
tory of development of DSS, five broad categories have been agreed on within this area,
they include communications-driven, data-driven, document driven, knowledge-driven and
model-driven decision support systems.
DSS’s benefits have been discovered by businesses and other organizations, for example,
speedy computations, improved communication and collaboration, increased productivity
of group members, improved the quality of decision making, improve the flexibility of time
and space of decision making etc (Turban, Aronson, Liang & Sharda, 2007).
In the rapidly changing world today, banking and the wider provision of financial service
are the two sectors that are facing more and more challenges. There have been significant
changes in banks, which traditionally, have been the warehouse for the safekeeping of
wealth. Nowadays, a wide range of financial products and services to both individual and
organizations are provided. Furthermore, banks also have their own ‘businesses’ which are
connected with different investments (Kuljis et.al, 1999).
DSS had expanded the scope of its applications since the beginning of 1980’s by academic
organizations and universities, besides the scope, the expanding of the field of DSS also
enriched the later development of the system (Power, 2007). The benefits of decision sup-
port system were recognized that it could be designed to support decision-makers at any
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level in an organization and could support operational decision making, financial manage-
ment and strategic decision-making (Power, 2007).
In banking and financial services, different Business Intelligence (BI) software has been
heavily invested into the organization to keep a competitive edge. The different technolo-
gies provide the opportunities to delivery rich, consumable and interactive information to
provide decision makers to make better decision. Solutions like dashboards, portable ana-
lytics and ad hoc reporting enables intergradations of Business Activity Monitoring (BAM),
Complex Event Processing (CEP) to view, monitor and report on business processes.
There is an example of a web based BI tools which are used in analyzing Swedish property
market. Swedish banks also use this tool to help make the right decisions to release loans to
debtors. The tool is called DATSCHA (more information could be found in the “Frame of
Reference 3.6”).
It is essential to the bank to make right decisions on investments or giving loans, especially
in the time when the economic is recovering from the last crisis.
In the rapid time of economic development, making the right decision at the right time is
crucial to the banking section today. Go together with the technology improvement, after
1995, World Wide Web, global Internet, and the later released HTML 2.0 specifications ac-
celerated the development speed of web-based DSS (Power, 2007).
Besides the rapid development in the business world including baking sector, different or-
ganizations have various ways to measure their success. Therefore, one factor that could
not be denied is that the revenue targets are becoming harder and harder to reach. By gain-
ing focus on making proper strategic and tactical decisions with necessary knowledge to
maximize revenue, minimize risk and remaining the competitive place in the market. BI
could be one of the best practical DSS to assist organizations to achieve the goal (Miller,
Brautigam and Gerlach, 2006).
1.2 Problem
Kuljis (1999) argues that two main factors have the contribution to the change of the core
business of financial institutions. One is deregulation of the sector, and the other is the de-
velopments in Information Communications Technologies (ICTs).
The new Information Technology (IT) enables new possibilities/advantages, however, also
implies risks/disadvantages. For example, ICT helps the bank to reduce the paper work
and improve the efficiency/effectiveness of the process. Conversely, if the organizations
depend on the new technology too much, and the system has unexpected crisis, all the data
could disappear in a flash. So the problems are the following. To what extent can we trans-
fer manual routines to automatic operations? Is the employees’ knowledge enough to real-
ize the borders? To what extent, could the company expect the employees to be aware of
the disadvantages and the emerging risks, so that the systems could make best use for the
company?
Most people might know about the economic landslide began around August, 2007, the
main reason might be that the financial market could not solve the subprime crisis of its
own, later on, the influences spread beyond the US’s borders (Singh, 2009).There might be
thousands of reasons that caused this economic crisis, since this is not the first time it hap-
pened in history. Put it in another way, why it happens again, is it possible to foresee these
possible outcomes by assistance from the technology systems?
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Obviously, banking system was not prepared for such a ‘worst case scenario’ and could not
follow the speed to ‘Save’ the occurring shortcomings. Together with even worse decisions,
a final catastrophe occurred. In 2008, the U.S. government with National Economic Stabi-
lization Act created a corpus of $700 billion to purchase distress assets (Singh, 2009).
Until now, there might come up with the questions, what is the role of IT-system in fore-
seeing the problems to support banks to make the right decisions? Did the technologies re-
ally contribute what they supposed to? Some pre-conclusion that could be drawn from the
American case is that the problems of complexity do not seem to be resolved in nowadays
systems.
1.3 Purpose
The purpose of this research is to find out to what extent and how decision support sys-
tems are used in financial sectors today. The research is also trying to give the suggestions
to provide better alignment of using decision support system to make better strategic deci-
sions. On the other hand, the shortcomings, risks and misuse of the system shall also be
covered in this thesis.
1.5 Limitations
In this thesis, the problems will be discussed mainly focusing on banks. Hence, for sure,
some of the problems mentioned in the thesis are of that dignity, which is that only banks
with strong finances and big size could have the problems and solve the problems.
Some of the example will be referred to as international, but the empirical study will mainly
be done in Scandinavia (or Sweden). This is for more practical reasons, such as near access.
Nevertheless, the interviews will also be open to overseas banks or organizations if it is
possible.
Financial decision makings are related with various problems or opportunities, therefore,
how the systems are being used and how much do banks depend on DSS might be difficult
to find an answer to. In banks and financial organizations, smaller functionality of services
provided to private customer for example commercial banks help individuals make invest-
ment decisions; bigger obligate functionality to the whole country, for example national
banks need to make strategic decision of adjusting inflation rate.
The research will be interested in different perspectives, and open to find out DSS’s usages
in different sectors in different banks or financial organizations which depend on the
access to get the empirical data. At the same time, it is hard to decide which specific areas
need to be focused on, since the functions in banks are pretty much interrelated to each
other. The research journey will start from investment sector.
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1.6 Interested parties
This research could interest a group which makes strategic decisions for the organizations.
It can include banks, financial organizations, both academic and practical. The group of
people will include CIO’s and CEO’s of headquarter of the bank as well as the manage-
ment level to make good use of system to execute the decisions.
1.7 Definition
Information Technology (IT): Is a term that encompasses all forms of technology used
to create, store, exchange, and use information in its various forms (business data, voice
conversations, still images, motion pictures, multimedia presentations, and other forms, in-
cluding those not yet conceived). It's a convenient term for including both telephony and
computer technology.
Information Communications Technology (ICT): Is an umbrella term that includes
any communication device or application, encompassing: radio, television, cellular phones,
computer and network hardware and software, satellite systems and so on.
Decision making: Is the process of sufficiently reducing uncertainty and doubt about al-
ternatives to allow a reasonable choice to be made from among them (Harris, 2009).
Decision support system (DSS): A conceptual frame-work for a process of supporting
managerial decision-making, usually by modeling problems and employing quantitative
models for solution analysis (Turban et.al, 2007).
Business Intelligence (BI): A conceptual framework for decision support, it combines
architecture, databases, analytical tools and applications (Turban et.al, 2007, p.753).
Banking System: Underpin nearly every banking process (Heidmann, 2010).
Hermeneutical: Understanding should continually refer back to an earlier preunderstand-
ing, preunderstanding must be fertilized by the new understanding (Alvesson and
Sköldberg, 2000).
Risk Management: Process by which the Board and Management make decisions – ac-
cording to their risk tolerance preferences- on what processes are best suited to allow the
Bank meet its strategic objectives (see “Appendix 4 – Risk Assessment Glossary”).
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2 Method
The method part will provide the reader the view of how the research will be conducted to
achieve the research purpose. The selection of research philosophies, research strategies,
and research approaches etc. will be presented here to make the clear view of the research
methodological processes.
2.1.1 Epistemology
It is hard to identify which philosophy approach is better in a certain contest, yet, in general,
a mixture between positivism and interpretive would perhaps reflect the stance of realism
regarding business and management research (Saunders, Lewis and Thornhill, 2006). Posi-
tivism could help generate the research strategy to collect the data which could be used to
develop hypotheses with the help of existing theories (Saunders et al., 2006). By the ap-
proach of interpretive, some researchers argue that the perspective from an interpretivist is
highly appropriate in the business and management research (Saunders et al., 2006).
Strategic decisions, banking systems, investments are considered to be highly confidential
business information. It might be difficult to get all the information/data by interviewing
/observing only one organization. Therefore, this ever-changing and never-ending business
world would not be enough to be analyzed by the generalized theories, as researchers, the
challenge is also to enter and understand the world by adopting an empathetic stance
(Saunders et al., 2006).
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In this research, after the topic has been decided to be author’s research interest. The pre-
literature search started by finding different information regarding decision making, deci-
sion making support system in banks or in financial services. The subject is very wide, and
the information which could be found to combine all those keys words together, is very li-
mited. In this situation, the linear research design would not be the best way to apply in my
research. Williamson (2002) suggested that by applying research in such situation, the de-
sign would be non-linear and iterative which means the various elements in the research is
interwoven, hence, with the development of one decisions to influence about others.
The following figure (2-1) is about ‘qualitative research design’ process which used in order
to show the research design more comprehensively. The iterative process indicates the in-
terconnection of the stages.
Topic of
interest
Defining sample
(places and persons)
Collecting data
Analyzing and
interpreting data
Report findings
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2.2.3 Qualitative research
Qualitative research approach focuses on getting deeper understanding of people’s pers-
pective, and the reasons and consequences behind their behaviors (Easterby-Smith, 1991;
Amaratunga et al., 2002). One of the strengths of a qualitative research is helping people to
see the worldview of the researches which simulates people’s experience of the world (Yin,
1984).
Within this research, DSS’s usage might be various looking into different banks and organ-
izations. By understanding the essential part of the research purpose, qualitative research
approach focuses on how to dig out the interlinks between systems and decision makings.
2.3.1 Hermeneutic
This research report started with very wide perspective. Strategic decision making itself is a
complicated process which combing tangible and intangible factors. Furthermore, the stra-
tegic decision is usually related with the top level of the whole organization. Decision sup-
port system could be one perspective to assist/improve the strategic decision making
processes. By narrowing it down as one interesting question or detail to focus on, at the
same time, to be open minded, flexible, not restricted by the theories or the predictions will
help the research to be spinning in a higher and higher level with more and more findings
(Alvesson and Sköldberg, 2009).
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As shown in figure 2-2, hermeneutic circle explained by Alvesson and Sköldberg (2009),
the hermeneutic spiral is showing an alternation between the pre-understanding and under-
standing, interpretation and dialogue, theory and practice which by getting more and more
knowledge and understanding of the research in a ‘growing’ process.
2.3.1.1 Part and whole
The circle in the middle of figure 2-2 is the original version of hermeneutic circle, the part
can only be understood from the whole, and the whole can be understood from the parts
(Alvesson and Sköldberg, 2009).
By starting at one point of the research area, and then delve further and further into the
area by alternating between part and whole, back and forth during this process, the deeper
understand of both part and whole would bring progress.
As mentioning before, the information regarding the usage of DSS combines with bank-
ing/financial sectors was very limited. Instead of being frustrated and pendulous, the au-
thor decided to start collecting information about decision support systems, to learn more
about its history and structure. By getting deeper and deeper understanding of DSS and BI,
the general picture of applying the system in banking/financial sectors came to my mind.
Later on, by doing more and more literature research, knowledge about decision making
support in different levels were built up to further the research. In data collection processes,
the starting point was with the help of this thesis tutor who suggested a professor who has
superior knowledge about DSS. Through the initial contacting with professor Sven
Carlsson from Lund University, he suggested that there was limited research paper related
with this research topic in Sweden could be accessed to. But, there is very useful informa-
tion provided by him that Dr. Martin Fahy from department of accountancy and finance in
National University of Ireland is doing research related within this area. Professor Carlsson
also provided useful information about Financial Service Innovation Centre (FSIC) in Uni-
versity College Cork, Ireland which was also doing both academic and practical projects re-
lated with IS and financial services which enabled and encouraged the on-going process of
this research.
2.3.1.2 Preunderstanding and understanding
The hermeneutical circle indicates the relationship between preunderstanding and under-
standing is called the circle of alethic hermeneutics. Alethic hermeneutics dissolves the
stance between subject and object into more original situation of understanding by a dis-
closive structure.
From pre-literature review the information found scattered from different parts could help
form preunderstanding picture of how and what could be used in strategic decision making
processes in banks.
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• Penetration – the underlying, central problematic should be obvious
• Thoroughness – all the questions in the research should be answered
• Agreement (1) – in interpretation should agree with the author without distor-
tions
• Suggestiveness – the interpretation should be ‘fruitful’ and stimulate the imagi-
nation
• Potential – the application of the interpretation can be further expanded
2.3.2.1 Pattern of interpretation
Pattern of interpretation shows the coherent whole of partial interpretations, which should
make individual details of the text understandable, at the same time, growing from them.
The ‘facts’ from the interpreted materials should also be included in the pattern of interpre-
tation (Alvesson and Sköldberg, 2009).
The collected data will follow this pattern to be interpreted together with the chosen theo-
ries to be analyzed in this research.
2.3.2.2 Text
Refer to Ricoeur (1981) the text indicated here can be literal, consisting of written or spo-
ken words, it can also be figurative. By applying the interpretation process into text, facts
emerge. These texts might only be part of something, therefore, in some sense; these par-
ticular pieces are endowed with a deeper and richer meaning according to the overarching
pattern of interpretation. These texts also alternately influence the pattern of interpretation
which richness and modification are showing up during the hermeneutic process (Alvesson
and Sköldberg, 2009).
In this research, the chosen theories will help to interpret the text, therefore, during the
transformation of the frame of reference, new ‘facts’ will emerge and old ones might dis-
appear. This means, the chosen frame of reference will not lead the research to find the re-
sults but provide the necessary information for further empirical data findings to get the
‘fact’ (Alvesson and Sköldberg, 2009). The choice of frame of reference is based on the dif-
ferent areas for example, DSS, strategic decision making, investment, BI, which are in-
cluded in the research topic, they might look scattered, therefore through the hermeneutic
process, the inter-relationship and strategies will be found later on in banks and financial
sectors.
2.3.2.3 Dialogue
In relation to the text, hermeneuticians take neither monologic stance nor via a passive re-
ception of the text like grounded theory to continue the interpretation process, instead,
they use the procedure of asking questions which arise from preunderstandings, and then
to listen to it, within this dialogic form, the dynamic process of developing or transforming
is emanated (Alvesson and Sköldberg, 2009). During the dialogue, the attitudes of humble
for listening and active for answering are much recommended.
During the process of literature review and data collection, sometimes, gliding back and
forth between the ‘old’ aspect imposed in the preunderstanding and the new understanding.
Later on, as explained by Alvesson and Sköldberg (2009), questions which lead the whole
also interact with questions directed at the parts, these two types of questions enrich each
other, after all, research questions will transform and influence ‘facts’ as well as patterns of
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interpretation. Decision support system is not just a system; it includes the process of ana-
lytical decision making processes. Furthermore, the complication of banking and financial
organizations makes even more difficult to find out how those could be combined to be
applied in a good way, therefore, the back and forth dialectic process is inevitable. Even be-
tween the approaching the data collection and literature review, the process is more like di-
alectic to make the knowledge and understanding grow.
2.3.2.4 Sub-interpretation
During the hermeneutical interpretation process, sub-interpretation leads the research to go
deeper and find more valuable interpretation by narrow down the relevant stance. The
three criteria for assessing of plausibility in interpretation suggested by Hirsch (1967), helps
this research to go further.
1. A narrower class has more weight than a wider one because it is more precise to
find out the reasons behind one single certain phenomena.
2. By increase the number of numbers of classes, the plausibility of interpretation in-
creases.
3. The plausibility of the interpretation increase with the relative frequency of in-
stances which means, from the frequently happenings, interpretations could be kind
of summarized to find out ‘fact’.
This way of processing the research is well fit to gain more plausibility of the interpreta-
tions. Different ways of conducting data collection for example, by gaining to know more
about DSS, information is not only collected from literature, but also from academic pro-
fessor and person with real life experience. By one stance, expand from different area to
understand more and more, to increase the plausibility in the analysis.
During the whole process, new facts are created through the sub-interpretations, and old
ones disappear. This process is not solo process, it must be related to follow overarching
pattern of interpretation showed in (figure 2-2) the hermeneutic circle.
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Finding data both primary and secondary for this research is very crucial. It can significant-
ly influence the results of the research. In order to achieve this research purpose, the data
collection cannot focus on limited group of resources, for example, only to focus on CIO’s
or CEO’s interview in banks. Information from different angles, technical and business, in-
ternal and external, practical and academic, should be considered when collecting data. This
approach is also reflected by the hermeneutic circle.
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2.5 Interview
The in-depth interview will be applied to collect empirical data. The interviews will be con-
ducted by emails or by phones. This is done mainly because of the geographical location
and limited time reasons. According to King (2004) semi-structured interviews often refer
to qualitative research approach. In the semi-structured interviews, the themes and ques-
tions designed by research could be varied in orders or omitted/added depending on the
different interviewees (Saunders et al., 2006).
The interview questions and themes differ from different interviewees, therefore, the prin-
ciple of choosing the interview questions is required to achieve research objective and an-
swer the research questions.
The different questions are designed based on the pre-information acquired by initial con-
tacting with the following interviewees.
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discussions, Carnegie impressed us with its personnel open-mind and honesty. Therefore
the lecture content will not be allowed to be written officially in this thesis, instead, ques-
tions will be answered through its IT department regarding DSS and decision making.
2.5.5 Summary
Interview questions are all discussed and agreed by this thesis tutor to relate with the re-
search questions. Therefore, the questions do not limit the information which might
emerge from indirect relationship with research questions. All the main questions are in-
cluded in the “Appendix 1 – Interview questions”.
2.6.1 Validity
The concern of validity is about whether the findings are really about they appear to be
(Saunders et.al, 2007). In this research, the main interview questions are evaluated together
13
with tutor according the research questions. The interview summary is sent to the intervie-
wees to double check to avoid misinterpretation of the findings.
2.6.2 Reliability
Reliability is about whether the data collection techniques or analysis processes will yield
consistent findings (Saunders et.al, 2007). Will the measures repeatable on other occasions?
Will similar observations be reached by other observers (Saunders et.al, 2007)?
Therefore, the research approach for this thesis is hermeneutic approach; it is not very easy to
apply reliability to repeat measures. The stances in hermeneutic research, is from point to
whole, from preunderstanding to understanding, the whole processes need to keep open to
achieve the certain level. With such continuous processes, higher level of the understanding
of the relatively complete picture will be achieved. On hand, hermeneutic is an exciting re-
search approach, on the other hand, it might be the limitation to apply in a normal way of
measuring reliability.
14
3 Frame of reference
While doing the pre-literature review, very limited information could be found from the
current database in Jönköping University library regarding DSS and banking sectors. Nev-
ertheless, previous studies related with financial, banking and DSS could be the guidelines
to help the author to gain pre-understanding to understanding, from part to whole.
The following is the structure on how the theories will provide the guideline of empirical
data findings and the analysis to achieve the research purpose.
Decision support system is mainly used internally to support the strategic decision making
within the bank. Therefore, the information which input to DSS systems might also be in-
fluenced by the external customers.
As mentioned in the previous problem part, new technologies will help banks in some way;
the misuse of the system might also result in make huge disasters. By the stance of both in-
ternal and external, DSS would have some side effects towards misusing by decision mak-
ers.
This information is the pre-understanding of DSS used in banks, so the selected theories
are based on the pre-interpretation from literature review. The following picture, figure 3-1
provides the theories which are going to be used in this thesis. US banking structure pro-
vide the relationship between central bank and the intermediaries; Datscha is a real life ex-
ample of DSS which used in Sweden for making real estate business decision. The theories
listed in the middle of the picture are the theoretical support to analyze the empirical data
findings.
15
3.1 Introduction of DSS
Alter (1980) who publishes his Massachusetts Institute of Technology (MIT) doctoral dis-
sertation results in an influential book, expanded the framework for thinking about busi-
ness and management DSS. Later on, through his research, conclusion had been drawn
that DSS could be categorized in terms of generic operations (Power, 2007).
16
• Infrastructure: More effective use of shared infrastructure might lead to im-
provements
• Environment: Better methods for incorporating concerns from the surrounding
environment
• Strategy: A fundamentally different operational strategy for the work system
Type of Control
17
3.2.1 The steps of Decision Support
Described by Simon, the decision making process with four defined phases and the steps
of Decision Support (figure 3-3) show the relationship among these four phases.
1. Intelligence which involves searching for conditions that needs decisions.
2. Design which involves invention, development, and analysis possible alternative
courses of solutions.
3. Choice which involves selecting a course of action from available alternatives.
4. Implementation which involves adapting the selected course of action to the deci-
sion situation like problem solving or exploiting opportunities.
Intelligence
Implementation
Design
Put solution in-
to action
Creativity: find al-
Choice ternatives and so-
lutions
18
• Complete knowledge about all the alternatives is rarely possible, therefore, very few
decisions could be made with obsolete certainty.
• Certain risks are involved in decision making.
19
3.4 PEST analysis model
PEST Analysis (stands for Political, Economic, Socio-Cultural and Technological Envi-
ronment) is a very useful tool to help business leaders around world to build up their ver-
sion of the future by understanding the ‘big picture’ of the environment contains political,
economic, socio-culture and technological environment.
Financial decision makings are influenced by lots of factors as well. The each key factor in-
cludes different perspectives which listed in the following figure 3-4.
Political:
• Government type and stability.
• Freedom of press, rule of law and levels of bureaucracy and corruption.
• Regulation and de-regulation trends.
• Social and employment legislation.
• Tax policy, and trade and tariff controls.
• Environmental and consumer-protection legislation.
• Likely changes in the political environment.
Economic:
• Stage of business cycle.
• Current and project economic growth, inflation and interest rates.
• Unemployment and labor supply.
• Labor costs.
• Levels of disposable income and income distribution.
• Impact of globalization.
• Likely impact of technological or other change on the economy.
• Likely changes in the economic environment.
Socio-Cultural:
• Population growth rate and age profile.
• Population health, education and social mobility, and attitudes to these.
• Population employment patterns, job market freedom and attitudes to work.
• Press attitudes, public opinion, social attitudes and social taboos.
• Lifestyle choices and attitudes to these.
• Socio-cultural changes.
Technological Environment:
• Impact of emerging technologies.
• Impact of Internet, reduction in communications costs and increased remote work-
ing.
• Research and development activity.
• Impact of technology transfer.
20
Figure 3-4 PEST Analysis Framework
21
Figure 3-5 The process of Financial Intermediation
Liabilities
Liabilities are the amount owned which the legal claims against a business or household by
non-owners.
Benefits of Datscha
• Better analysis
• Faster analysis
• Simple
• No download or installation
22
4 Empirical results
4.1 Interviews with Swedish banks
Comprehensive information from both lectures and discussions about Sveriges Riksbank
(Central bank of Sweden) and two investment banks will be presented here. The data re-
sults will be categorized with lecture findings and discussion findings.
23
4.1.2 Discussions
During the discussion sections, questions were asked about Decision makings and DSS
within banks.
Nordnet Bank AB uses BI tool during the investment decision making processes. There
is a BI tool is used to generate formula to predict future risks volatility, from which, the
risk adjusted return could be allocated.
Making good decisions is not enough by using the tools, understanding the business model,
investment philosophy and strategy are also very important.
According to Mr. Artvro Arques, it is not easy to make sure end-users could use these BI
tools in a right way. Therefore, certain requirement about different knowledge background
could help to use the tools in a better way. Knowledge like portfolio theory, economics,
mathematics, statistics, finance, and experience from meeting with customers are recom-
mended.
Sveriges Riksbank’s decision making is most related with National level, the final deci-
sion regarding monetary policy is made by voting in Riksbank’s Executive Board.
Carnegie Investment Bank AB
There is no single system that could handle all types of issues. It depends on the specific
situation. There are some examples of systems which are frequently used in Carnegie such
as Bloomberg, internal systems like risk management systems, business intelligence reports
and external consultants.
24
Decision Support System in the bank
In the bank, Johan Svensson mentioned two DSS tools which are intensively used in mak-
ing and executing decisions. One is Programming Trading which is an automatic trading
system; the other is Market Maker which used to find opportunities in the market to make
money by using bank’s money. The BI tools in these two examples are used quite much,
respectively about 70% and 90% during the decision making process.
From his perspective, DSS’s benefit is to make decision faster; its drawbacks are less con-
trol and more chances of errors.
Decision makers and DSS
Decision makers have full capacity to use the system, to say the least, strategic decision
making group have people with different skills, the system could even be manipulated if
they want.
Economic crisis in US and expectations
The economic crisis has nothing to do with system, the most important reason is that
people ignored the facts of the risks and regulators failed to regulate the markets. Even if
the monitoring system was there, the people would still only pay attention to their own
benefits.
Now the situation of economic crisis in US is recovering, getting better and better. More
rules to regulate the banking systems are being created. Probably, the new rules might be
introduced that commercial banks cannot have their own trading.
25
ing to sell or buy as efficient as possible without looking at other demands. These DSSs are
without proper user-interface, lots of logics are build into a black box in the trading model.
DSS in retail banks
In most retail banks, even in the stock trading, DSS is not implemented to do the real time
trading. It is used to attract customer in order to enlarge bank’s money savings. Retailer
banks need to provide the stable environment for these individual customers to manage
their own savings.
In retailer banks, one of the biggest costs is staff. In one project, introduced by Mr. McCar-
thy in a 2nd largest retail in Ireland, managing the customer queues in an effective way to
reduce the staff cost. This kind of DSS is also one way to be used in retail banks.
DSS in transaction and payments
Nowadays, lots of transaction and payment services are gradually separated from banks.
Companies like payroll, western unions are dealing with professional transactions. Payment
is most likely done with visa card or other type credit cards. DSS is used to alert customers
and risks during these sections. For example, large transactions will be sent by text message
or email to the card holder, so that card holder could be aware of the risks. This new de-
parture is to include the consumer to the decision making process regarding transaction
and payments.
Furthermore, systems are intelligent enough to discover the abnormal transactions to alert
the company to maintain the risks.
26
4.4.2 Key factors of using DSS
1. Knowing the purpose of Development of DSS
2. Data type and analysis
3. How the system should be used and educations to users
4. Before implementing, the descriptions of the using process, measure the
impact (few firms are doing this)
5. Data quality is related to the quality of DSS
The data quality cannot be monitored, but could be evaluated.
One suggestion is to choose the most important area to evaluate certain da-
ta to guarantee the decision support quality.
27
4.5 Summary of data findings
Throughout these series of interviews, information from both academic and practical pro-
fessionals, domestic and international banks emerged different pictures in front of me re-
garding DSS and decision makings in banks and financial services sector. These pictures
have their common images as well as their unique color. By summarizing these findings,
the foundation of getting the whole picture of using DSS in banks to support decision
makings is built to continue the next move.
28
5 Analysis
The analysis will start with answering the research questions. After that, more new ‘facts’
which have emerged from text and dialogue will be also shared to complement the herme-
neutic approach of analysis.
29
5.2 How is DSS used in different levels in banks?
From both academic perspective and practical perspective, DSS plays diverse roles in dif-
ferent levels in banks.
In the investment bank, BI tools have been used to aid decision makings; the Programming
Trading and Market Maker tools mentioned by Svensson, Vice president from America
Merrill Lynch are the examples. According to Mr. McCarthy from FSIC, lots of complex
logics combining with mathematics models; economic models are embedded in the system
to support the trading in a higher level. Even the users may not be aware of these decision
support functionalities. Also mentioned by Mr. McCarthy, insurance section also use DSS
quite a lot, since DSS could help insurance companies to proactive the risks and set reason-
able price for the products. According to Professor Carlsson, trading is also one section
which uses DSS quite much. Mr. McCarthy and Carlsson both thought that DSS is not that
well known by all the people in banks who are using them, the system is like a black box.
The investment bank Nordnet, BI tools are recommended by the company to help inves-
tors to make investment decisions. Within the investment process, in needs analysis, a cus-
tomer behaviour analysis system is used to help analysis the actual needs from the data
provided by customers. In the selection of funds, a specific BI tool is used to allocate risks
combining qualitative analysis and quantitative analysis to make the good choices. In the
higher level, BI is also used by Nordnet to predict future risks to evaluate the return on in-
vestment so that the proper investment decision could be made.
In the lower level, for example transaction and payment, mentioned by Mr. McCarthy, DSS
is also used to monitor the process, during this process, consumer is being included as part
of the decision making process to make the decision by getting the notice information sent
by systems.
According to Professor Carlsson, that DSS has been the top three investment items in dif-
ferent organizations in past years. People are more aware of the importance of using DSS
to support the decision making.
The steps of decision support introduced by Simon (1977) could be used to summarize
how DSS is used in banks, in different decision support levels.
The most important is to discover problems or opportunities in banks to understand where
Decision Support is needed. The following are the needs from different sectors in banks
and financial services.
1. Investment: choose right items to invest, to make profit to meet both investors’
and banks’ needs, to predict risks and return on investment
2. Insurance: Set right price and manage the risks
3. Trading: make trading fast and profitable
4. Prevent abnormal Transaction/Payment, prevent losing of stolen payment card
By answering this research questions more comprehensively, the situation of DSS’s usage
should also be summarized here.
Too much dependency on system or totally ignore the system’s alert. For example, men-
tioned by Svensson about America economic crisis, people ignored risks informed by sys-
tems to go after the benefits, even though the risks were in front of them, pursuing current
benefits was more attractive than thinking about long term damage to the organization.
30
The knowledge of DSS is uneven, most of the decisions are experience based, therefore,
objective and independent risks might lost the contributions chances to support decision
makings.
• In the banks which are quite dependent on DSS, less control of making deci-
sions and more chances of errors will happen during the decision making proc-
ess.
• In general towards using DSS in financial sectors, the sense of change or mod-
ify the system models will not be that obvious since the complexity of the sys-
tem is not known so well by lots of people. Therefore, some mistakes could not
be highlighted so fast to be improved. This drawback is also related with the
fact which was pointed out by Professor Carlsson that few firms describe the
system’s working process of DSS before implementing; therefore, the impact
could be measured correctly after implementing.
31
framework “A Model of risks in the organization, risk frameworks typically enumerate the various
classes of risk and the degree of Risk Management expected” (see Appendix 4 – Risk Assessment Glos-
sary). By applying risk framework, the risk is defined and categorized into different level and
different priorities. In this sense, DSS could be used more precisely to make better deci-
sion.
The findings from Carnegie, is bit different regarding the DSS’s usage. Carnegie follows
certain processes when making big investment decisions. Therefore, DSS is just small part
during the decision making, most of the decision makings are decided by personal expe-
rience and group work. As the situation happened through last two years with financial cri-
sis, Carnegie had hard time to get recovered. Simple conclusion cannot just be made that
the letting down of the financial situation confronted by Carnegie is because they did not
use more than expected of DSS system to manage the risks. Nevertheless, if they are aware
of the benefits of DSS and they use it in the proper way, at least they might have more in-
formation to help making better decision. Harris (2009) summarized in the ‘decision mak-
ing process’ which provide a clear view of each step during the decision making process.
Harris (2009) argued that during the step of collecting facts, input from other perspectives
was very important to help to make decision. Then the later step of ‘rate the risk of each al-
ternative’ requires the risk raking, ratios, or grades which could be compared. What could
be suggested here, DSS could be used to obtain more complete data, and provide alterna-
tives with different risk ranking for decision makers.
32
5.4.3 Future perspective and improvement regarding DSS in banks
Some expectations from interviewees, not only from technical perspective, but also from
educational perspective are also valuable to be shared to accelerate the DSS’s better usage
in banks.
According to both Mr. McCarthy and Professor Carlsson, data collection and data quality
are two crucial areas which could improve DSS’s quality. Data collected from different
points could allocate more accurate and complete sources for decision making. Improving
the data quality by correcting mistakes frequently in most important decision making areas
is also crucial to guarantee the decision making’s quality.
Moreover from academic perspective, Carlsson also mentioned about the ethic issues, in
business school today, ethic education is ignored by both school and students. Using such
BI-system related to banks, certain moral standards and responsibility should be the qualifi-
cation for the users or the decision makers. As discussed with Svensson regarding America
economic crisis, ignorance of the risks and pursuing for personal maximum benefits were
the main reasons to cause this crisis.
During the discussions with Mr. McCarthy, the knowledge gap between users and system is
also the problem need to be improved in the future. On one hand, as Carlsson mentioned,
few organizations today describe clearly using process of DSS, therefore, the end users
sometimes have to guess and try, at the same time, certain mistakes occur. On the other
hand, business students from university should also be educated, not only by theories but
also by doing practices.
33
6 Conclusion
As shown in the analysis part, by answering and applying theories to analyze the findings,
both expected and unexpected results have emerged, by which, deeper and wider view to
conduct further understanding processes is provided. There are some emphases the author
would like to share in a more comprehensive summaries.
Banks and financial service sectors are being aware of DSS’s benefits nowadays. The
growth needs of implementing DSS system are obvious in a general view according to this
research.
Unawareness of DSS for people who are working in banks is one of the issues today. Dif-
ferent embedded models regarding different functions are not so clear to bank staff; there-
fore, there is a gap between human decision and system decision.
Risk analysis needs to be developed further to solve the risk management in different levels
in banks and financial services.
Various requirements between central banks, retail banks, commercial banks, investment
banks should be differentiated when implementing the system.
Banking systems are widespread systems which are influenced by environment factors, po-
litical, economic, socio-cultural and technological variables.
34
7 Reflections
The research now may temporality come to an end when looking back to the beginning,
and remembering the frustration of not knowing where to start, how to start and later
when the more and more possibilities to collect data from both academic and practical
world, and more and more secondary data was found this all helped to aid the research to
achieve the purpose of this thesis.
The most experience gained from this thesis is not only the results which have been dis-
covered, but also the attitude towards the whole research. The main line of the research
was to be open-minded and flexible in order to gain more knowledge. From the partial
knowledge about decision support system, decision making to discover how these are used
in banks. Even having limited resources in the beginning which were about BI and the re-
search method, and later on finding more and more primary and secondary data emerged
in front of me, I could say, my horizon is expended through this thesis.
Decision support system is also like this hermeneutic research process, it has been used up
and down during the decades, with the technological development; more and more banks
are using and are going to implement DSS to make better decisions. Therefore, different
perspectives including the system itself, banking system, and also environmental factors as
social culture, economics, political need to be merged and harmonized.
35
8 Future research
A latest report from McKinsey Quarterly, 2010 “Overhauling bank’s IT systems” says that
most of banks are struggling with outdated technologies in core banking systems dating
from1970’s (Heidmann, 2010). According to the report, the IT systems’ change is becom-
ing less costly and risky; Decision Support System is one of the Core Banking Systems. The
further research could be deepened into more concrete level to find out how Decision
Support System could assist and contribute Decision making process in different banks.
Furthermore, risk frameworks should be addressed to make the DSS more consistent to
the other systems within banks.
36
List of references
List of references
Turban, E., Aronson, J.E., Liang, T.P., Sharda, R. (2007) Decision Support and Business Intelli-
gence System. (8th ed.). New Jersey, Pearson Education.
Yin, R. K. (1994). Case study research: Design and method. (2nd ed.). Sage Publications, London.
Internet sources
Alter, S. (2004) A work system view of DSS in its Fourth Decade. Retrieved: 2010-03-21,
from http://hbr.org/2009/11/make-better-decisions/ar/1
BBC (2009) Timeline: Iceland economic crisis. Retrieved: 2010-03-21,
from http://news.bbc.co.uk/2/hi/7851853.stm
Buchanan, R. (2009) New Approach to Better Decisions Retrieved: 2010-04-19,
from http://www.di.net/articles/archive/better_decisions/
Buchanan, L. and Connell, A.O. (2006, January) A brief history of decision making, Harvard
Business Review. Retrieved: 2010-03-21, from http://hbr.org/2006/01/a-brief-
history-of-decision-making/ar/1
37
List of references
38
List of references
39
Appendix
Questions to interview with Johan Vice president in Bank of America Merrill Lynch
1. Can you tell me about your work in Bank of America Merrill Lynch New York?
2. Does your section use decision making support system to make decisions when
doing trading?
3. In your bank, do you know which sections are using the decision support system to
make decisions?
4. What do you think are the benefits and drawbacks of using DSS?
5. The economic crisis in US was well know, do you think misusing the DSS could be
one of the reason?
6. How the situation is now in US after economic crisis in bank, is there any changes
comparing with before (crisis)?
1. In general, what do you think of the importance of DSS regarding financial sec-
tor?(for making financial decisions for example investment?)
2. Could you explain more about the work you have been doing regarding DSS
/simulation around customer queues and staffing schedules for retail banks?
3. You mentioned about Risk management, what do you think is the relationship will
be regarding DSS and decision making in Trading, Mortgage etc.?
4. What is your perspective or future expectations to align/deploy DSS in decision
making regarding financial sector?
5. What do you think are the drawbacks and benefits of using DSS when making stra-
tegic financial decisions?
40
Appendix
Phone 046-2228026
E-mail Sven.Carlsson@ics.lu.se
Fax 046-2224528
Room EC2-225
I am Regional Editor for Knowledge Management Research & Practice and I am also on
the editorial boards of Journal of Decision Systems, Electronic Journal of Business Re-
search Methods, and Information and Communication Technologies for the Advanced En-
terprise.
I have written over 100 peer-reviewed journal articles, book chapters, and conference pa-
pers and my work has appeared in journals like Journal of Management Information Systems, De-
cision Sciences, Information & Management, Journal of Decision Systems, International Journal of Tech-
nology Management, Knowledge Management Research & Practice, Information Systems and e-Business
Management, Scandinavian Journal of Information Systems, and Electronic Journal of Information Sys-
tems Evaluation, as well as in well-recognized handbooks like Handbook on Knowledge
Management and Handbook on Decision Support Systems.
41
Appendix
I have been on a number of conference boards, for example, the organizing committee of
ECIS ´97 (European Conference of Information Systems) and I was the chairman for
ECKM 2002 (European Conference on Knowledge Management). I was on the organizing
committees for the IFIP W.G. 8.3 conferences in 2000, 2004, and 2006. I am vice-
chairman of IFIP W.G. 8.3 on Decision Support Systems and I am a member of
INFORMS and AIS. I regularly review papers for international journals and conferences, as
well as act as an “expert examiner” of research projects.
My research has an international focus and currently I co-operate with researchers at Uni-
versity College Cork (Ireland), Marshall School of Business, USC, Los Angeles, School of
Business Systems, Monash University, Melbourne, Copenhagen Business School, and Un-
iversità della Calabria.
I supervise Ph.D. students at Informatics, LUSEM. In 2000 the Swedish National Research
School "Management and IT" was established. I teach in the school and I am a member of
the school’s board. The school has more than 60 PhD students. Benkt Wangler (College of
Skövde) and I manage the research network “Knowledge in Organzations, KiO.” I am a
recipient of Lund University’s most prestigious teaching award: “Teaching Award for Out-
standing Contributions to Undergraduate Education.“
Link: http://www.ics.lu.se/staff/Sven.Carlsson
42
Appendix
The Centre provides a resource for global financial services companies to participate in cut-
ting-edge innovation and development that will have global impact. The Centre also allows
participants to share information and expertise, while also keeping abreast of the latest de-
velopment in the financial services software market. Innovation is unpredictable and revo-
lutionary, the Centre aims to reduce this uncertainty and exploit the power of innovation
through the development of cutting edge software solutions.
Link: http://www.fs-innovation.org/
43
Appendix
Should you have any comments or suggestions to enhance this glossary, please send them
directly via e-mail to Ana María Sáiz (amsaiz@iadb.org).
• Appetite for Risk: A measure of the propensity for Risk Taking or Risk Aversion.
• Avoiding Risk: A Risk Management technique of redesigning the task to deal with
a different set of risks (usually lower). Not to be confused with Risk Reduction,
which refers to reducing the level of a given risk or set of risks, or with Eliminating
Risk.
• Control Environment: The tone at the top of an organization, including how risk
and opportunities are viewed, overall attitude towards adherence to sound business
practices and ethics, internal controls, value assigned to human capital, incentives,
and how authority is delegated and accountability is enforced.
1
This glossary of terms contains definitions from:
1. The Risk Assessment Glossary compiled by David McNamee, Mc2 Management Consulting.
http://www.mc2consulting.com/riskdef.htm
2. The COSO System – a system of internal controls or Control Framework defined by the Committee of Sponsoring
Organizations of the Treadway Commission -USA.
44
Appendix
• Control Risk: The tendency of the Internal Control system to lose effectiveness
over time and to expose, or fail to prevent material risk exposure.
• Corporate Governance: The organization's strategic response to risk. Usually en-
compasses a number of activities and functions, such as Leadership, Assurance,
Stewardship, Structure, etc. Governance is usually exercised by the Governance
Team made of senior managers and the Board.
• Environment: The external forces, conditions and circumstances that are the
source of risk. The environment includes competitors, borrower wants, technologi-
cal innovation, sensitivity, stakeholder expectations, capital availability, sove-
reign/political, legal, regulatory, financial markets, catastrophic risks, etc.
• Fiduciary Risk: The risk that project funds might be used for purposes other than
those stated in the loan contract, or the use of funds without the consideration to
the principles of economy and efficiency. The risk that the Bank might use its ad-
45
Appendix
ministrative budget for purposes that are not consistent with its development effec-
tiveness mandate.
• Hard Assets: Physical assets (land, buildings, equipment) and financial assets (cash,
credit, financial instruments). Hard assets are usually on the records of account in
an organization and subjected to inventory and/or custodial safeguards. See also
Soft Assets.
• Hazard: Risk associated to the consequences of natural disasters (i.e. all atmos-
pheric, hydrologic, geologic, and wildfire phenomena that, because of their loca-
tion, severity, and frequency, have the potential to negatively affect humans, their
structures, or their activities).
• Impact: Result or effect of an event that materializes the risk. There may be a
range of possible impacts associated with an event. The impact of an event can be
positive or negative relative to the Bank’s related objectives.
• Inherent risk: The risk to the Bank in the absence of any actions management
might take to alter either the risk’s likelihood or impact.
• Integrated Risk Management: The consideration of Risk at all levels of the or-
ganization, from the Strategic to the day-to-day job of the customer-facing em-
ployee. Integrating risk management into internal auditing means adopting Risk-
Based Auditing and using risk management tools to plan internal audits.
• Likelihood (or Probability): The possibility that a given event will occur. The li-
kelihood is often measured in qualitative terms such as high, medium, and low, or
other judgmental scales, or “probability” indicating a quantitative measure as a per-
centage, frequency of occurrence, or other numerical metric.
46
Appendix
• Managing Risk: Entails selecting the right strategy for each risk based on the risk
appetite defined for each operation. Risk management strategies encompass:
“avoidance”, “reduction”, “sharing”, acceptance.”
• Opportunity: The possibility that an event will occur and positively affect the
achievement of objectives.
• Pervasive Risk: The type of risk found throughout the environment. The focus is
on the environment of the business activity instead of the activity itself. Think of it
as the "Corporate Culture."
• Process Risk: The risk that business processes are not clearly defined, are poorly
aligned with business objectives and strategies, do not satisfy stakeholders' needs,
or expose assets to misappropriation or misuse.
• Reputation Risk: The risk of loss of brand image, or Stakeholders’ support such
that the Bank will be unable to operate at its full capacity. Is directly related to Im-
age and Branding risk, and to Stakeholder Relations risk. (Image and Branding
risk: is the risk of losing borrowers, key staff members or the ability to compete,
due to perceptions that the Bank does not deal fairly with borrowers, stakeholders,
bidders/suppliers, or knows how to manage its business; Stakeholder Relations
risk: is the risk of a decline in stakeholders' confidence that may impair the Bank's
ability to have political support in the international community and to efficiently
raise capital).
47
Appendix
• Residual Risk: The remaining risk after management response to the risk.
• Risk: Risk is the likelihood that due to action or inaction, the occurrence of an
event affects the Bank’s ability to fully meet its strategic objectives.
• Risk Appetite (or Risk Tolerance): The broad-based amount of risk the Bank is
willing to accept in pursuit of its mission (or vision).
• Risk Assessment: The identification of risk, the measurement of risk, and the
process of prioritizing risks.
• Risk Classification: The categorization of risk, typically into High, Medium, Low
and intermediate values.
• Risk Event: The manifestation of risk into consequences that may relate to inter-
nal or external sources, which affects achievement of objectives. Otherwise, Risk is
only a potential.
• Risk Identification: The method of identifying and classifying risk. See Risk
Classification.
48
Appendix
• Risk Matrix: A form of Risk Measurement and Risk Prioritization in one step that
uses risks on the horizontal axis and system components or audit steps on the left
axis. Both axes are sorted to the left corner (High), creating a matrix with qua-
drants of High, Medium and Low groups of elements and risks.
• Risk Ranking (or Risk Prioritization): The ordinal or cardinal rank prioritization
of the risks in various alternatives, projects or units. Also, Risk Scenarios: A me-
thod of identifying and classifying risks through creative application of Probabilistic
events and their Consequences. Typically a Brainstorming or other creative tech-
nique is used to stimulate "what might happen."
• Risk Response: set of actions to align risks with the Bank’s risk tolerance and risk
appetite.
• Sharing Risk: Risk Management technique for distributing the possible Conse-
quences of risk among several parties. Insurance and other contracts are methods
used to share or Transfer Risk.
• Soft Assets: Human resources (people, skills and knowledge) and intangible assets
(information, brands, and reputation). Soft assets are hard to value and are not
usually reflected in the books of account, nor are they typically subjected to period-
ic inventory. See also Hard Assets.
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Appendix
• Strategic: Used with “objectives”: having to do with high-level goals that are
aligned with and support the Bank’s mission (vision or mandate).
• Threat: Risk associated to the consequences of crime, robbery, fraud and corrup-
tion.
• Value-At-Risk: Often abbreviated as VAR, these are a class of Models used by fi-
nancial institutions to measure the risk in complex derivative portfolio positions.
VAR estimates the total aggregate value in the portfolio exposed to the risk of loss.
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