MAKARERE UNIVERSITY
MAKERERE UNIVERSITY BUSINESS SCHOOL
CREDIT RISK MANAGEMENT AND LOAN PERFORMANCE IN
DEVELOPMENT FINANCING
‘ (THE CASE OF UGANDA DEVELOPMENT BANK , AND
DEVELOPMENT FINANCE COMPANY UGANDA LTD )’’
MULONDO ROBERT
2000/HD101/1176U
SUPERVISORS:
PROF. DR. THOMAS WALTER
DR. N. NKOTE
A THESIS SUBMITTED IN PARTIAL FULFILMENT FOR THE AWARD OF
MASTERS OF BUSINESS ADMINISTRATION (MBA) DEGREE OF
MAKERERE UNIVERSITY
MARCH, 2011
i
DECLARATION
I, Mulondo Robert declare that this dissertation is my original work and that it has not
been presented in any other University for a similar or any other degree.
Signature: …………………………………………………..
Date:
……………………………………………………
ii
APPROVAL
This is to certify that this dissertation has been submitted in fulfillment of the
requirements for the award of the degree of Masters of Business Administration with my
approval as University Supervisor.
Signed …..………………………
Date…………………………
PROF. THOMAS WALTER
Makerere University Business School
Makerere University
Signed ………………………….
Date……………………………..
Dr. N. Nkote
Makerere University Business School
Makerere University
iii
DEDICATION
This work is dedicated to those who helped me carry out this research and to the almighty
God for the wisdom and gift of life that has made me realize and see the conclusion of
this book. To all scholars with research interest in risk management, I believe they will
find this work interesting contributing to new knowledge.
iv
ACKNOWLEDGEMENT
I would like to thank my supervisors Proff. Thomas Walter and Dr. Nkote who guided
me and helped me complete this dissertation.
Special thanks go to the management and staff of Uganda Development Bank and more
specifically Dr. Appiah – Executive Director Investment, and his senior team of project
advisors and analyst who constantly took keen interest in my research and provided all
the necessary assistance to enable me carry out this research. Am humbled by your
preliminary discussions, brainstorming session, and information given which was of great
help to make me understand the topic in a practical way.
I must acknowledge the material and moral support, the cooperation accorded to me from
staff of DFCU Ltd. during this research.
v
Table of Contents
DECLARATION.............................................................................................................................. ii
APPROVAL .................................................................................................................................... iii
DEDICATION ................................................................................................................................ iv
ACKNOWLEDGEMENT................................................................................................................ v
LIST OF TABLES AND FIGURES ............................................................................................. viii
LIST OF ACRONYMS ................................................................................................................... ix
ABSTRACT .................................................................................................................................... X
CHAPTER ONE.............................................................................................................................. 1
1.0
Background to the Study .................................................................................................... 1
1.1
Statement of the Problem ................................................................................................ 3
1.2 Purpose of the Study................................................................................................................ 3
1.3
Objectives of the Study ....................................................................................................... 3
1.4
Research Questions ............................................................................................................. 3
1.5
Significance of the Study..................................................................................................... 3
1.6
Scope of the Study ............................................................................................................... 4
1.7
Conceptual Framework ....................................................................................................... 4
1.8
Organization of the Report .................................................................................................. 5
CHAPTER TWO............................................................................................................................. 7
2.0
Literature Review ................................................................................................................ 7
2.1
Credit Risk Management ..................................................................................................... 7
2.2
Appraisal (Avoidance)......................................................................................................... 9
2.3
Credit Rating ..................................................................................................................... 10
2.4
Technical Feasibility ......................................................................................................... 16
2.5 Financial Viability and Financial Analysis ............................................................................. 16
2.6
Risk Transfer ..................................................................................................................... 18
2.7
Risk Diversification ........................................................................................................... 24
2.8
Risk Retention ............................................................................................................... 25
2.9 Loan Performance ................................................................................................................. 26
2.10 Relationship between Loan Appraisal and Loan Performance............................................ 28
vi
2.11
Relationship between other Risk Management Techniques and Loan Performance..... 29
CHAPTER THREE ....................................................................................................................... 31
3.0
Research Methodology ...................................................................................................... 31
3.1
Research Design ............................................................................................................. 31
3.2
Population .......................................................................................................................... 31
3.3 Sample size ............................................................................................................................ 31
3.4
Data Collection Instruments .............................................................................................. 32
3.5 Sources of Data ..................................................................................................................... 32
3.6
Measurement of variables.................................................................................................. 33
3.7 Validity and Reliability Tests ................................................................................................ 33
3.8
Data Analysis …………………………………………………………………. 35
3.9
Problems Encountered in the Study .................................................................................. 35
CHAPTER 4 ...................................................................................... Error! Bookmark not defined.
4.0
DATA PRESENTATION, ANALYSIS AND INTERPRETATION ............................... 36
4.1
Introduction ....................................................................................................................... 36
4.2
Demographic Data ............................................................................................................. 36
4.3 Factor Analysis ...................................................................................................................... 40
4.4 Relationship between Variables. ......................................................................................... 44
4.5
Relationship between Other Risk Management Techniques and Loan Performance. ....... 47
CHAPTER FIVE ........................................................................................................................... 48
5.0
INTERPRETATION, DISCUSSION, CONCLUSION AND RECOMMENDATION ... 48
5.1
Introduction ....................................................................................................................... 48
5.2
Interpretation and Discussion of Results. .......................................................................... 48
5.3
Examining the Relationship between other Risk Management Techniques and Loan
Performance................................................................................................................................... 51
5.4
Conclusions ....................................................................................................................... 53
5.5.
Recommendations ............................................................................................................. 54
5.6
Areas for Further Research ................................................................................................ 56
6.0
References ......................................................................................................................... 57
APPENDIX 1 ................................................................................................................................ 65
MAKERRE UNIVERSITY BUSINESS SCHOOL ...................................................................... 65
vii
LIST OF TABLES AND FIGURES
Table 1
Loan Performance for Development Finance for UDB and DFCU Ltd
2
Table 2
Sample Size Selection
32
Table 3
Reliability coefficient
34
Table 4
Response rate
36
Table 5
Gender distribution.
37
Table 6
Status of respondents by qualification
38
Table 7
Previous working knowledge from credit
38
Table 8
Age distribution of respondents
39
Table9
Working experience in the banking sector.
40
Table 10
Rotated Component Matrix: Appraisal
41
Table 11
Rotated Component Matrix: Other risk management techniques
43
Table 12
Correlation coefficients
45
Figure 1
Conceptual
Frame Work
Figure 2.
Pie chart showing previous working experience
viii
5
39
ABS
LIST OF ACRONYMS
Asset Backed Securities
ADB
Asian Development Bank
BIS
Bank for International Settlement
CDO
Collateralized Debt Obligations
CRA
Credit Rating Agency
CRT
Credit Risk Transfer
DFCU
Development Finance Company of Uganda
DFD
Development Finance Department
DFI
Development Finance Institution
EIB
European Investment Bank
EU
European Union
R&D
Research and Development
RAROC
Risk Adjusted Return on Capital
ROA
Return on Assets
ROE
Return on Equity
SME
Small and Medium Enterprises
UDB
Uganda Development Bank Ltd
UIB
Uganda Institute of Bankers
VaR
Value at Risk
ix
ABSTRACT
The study which focused on credit risk management and loan performance in
development financing was based on two objectives which were: to examine the
relationship between loan appraisal and loan performance, and to examine the
relationship between other risk management techniques and loan performance. A cross
sectional survey design was employed. Using a case study involving 46 respondents
comprising of all the technical staff from Uganda Development Bank and Development
Finance Company Ltd, a descriptive and correlation analysis was used to investigate the
relationship between loan appraisal, credit rating, financial viability, technical feasibility,
risk transfer, risk diversification, risk retention and loan performance. The findings
indicated that loan appraisal, credit rating, financial viability, technical feasibility, risk
transfer, risk diversification; risk transfer had a positive and significant relationship with
loan performance. The study held that credit risk management in the two banks has a
positive relationship to loan performance. Loan appraisal showed a very strong
significant relationship to loan performance as compared to other risk management
technique like risk transfer , risk diversification . The appraisal process helps identify and
analyze loss exposures support to monitor business risk which enhances normal loan
repayment behavior of any credit consumer. Loan diversification closely followed and
exhibited a strong positive correlation to loan performance. Investing loan portfolio in
different markets, regions or in different economies will reduce risk exposure, and lead to
better economic returns.
x
CHAPTER ONE
1.0
Background to the Study
Demand for development financing in Uganda is high. Despite this, statistics from Bank
of Uganda (BoU) and Ministry of Finance, Planning and Economic Development reveal
low levels of development financing in the economy (2002-2003 Budget Report).
According to this report, percentage investment credit distribution towards private sector
in form of development finance was as small as 10% compared to trade and other
services which was 52%, Manufacturing – 29% and Agriculture – 10%. In order to
promote economic development in any economy, new private enterprises/ investments in
key productive sectors of the economy must be encouraged through development
financing. The development of long-term capital market to benefit private enterprise and
ensure that deserving private enterprises have access to long term finance on competitive
terms, highly depends on availability of development finance institutions in an economy.
In 1977, the government of Uganda through Bank of Uganda (BOU) established the
Development Finance Department (DFD) to promote economic growth and development
programs, and refinance facilities. This was in addition to Development Finance
Company of Uganda (DFCU Ltd) and Uganda Development Bank established in 1964
and 1972 respectively.
Despite the long existence of the above two development finance institutions in Uganda,
offering products ranging from term finance, leasing, mortgage finance, and equity to
trade finance, a close examination of their loan portfolios reflect that the two institutions
are heavily characterized with high levels of non performing loans. Out of a total of 431
accounts at the onset of the restructuring process of UDB in 1997, approximately UGX
80.1 billion was in arrears representing 90% of non performing loans. After the
1
restructuring process, out of UDB’s total loan portfolio of UGX 40.2 billion in the year
2009, 32.5 % was non- performing as compared to 5.3% for DFCU with a total loan
portfolio of UGX. 326.2 billion. In the years 2009, UDB total loan portfolio was
UGX.40.8 billion of which 32% was non- performing ( UDB annual report, 2009) as
compared to 5.3% for DFCU with total loan portfolio of UGX. 326 billion (DFCU annual
report 2009).
Table. 1. Loan Performance for Development Finance for UDB and DFCU Ltd
UDB
DFCU LTD
Period (Years)
2008
2009
2008
2009
Total Loans ( Billion of Shillings)
32.8
40.4
282.7
326.2
Non – Performing Loans (Billion of Shs.)
10.6
13.2
24.9
17.3
32.5%
8.8%
5.3%
Percentage of Non – performing loans to 32.3%
total loan
Source: UDB and DFCU, 2009
The levels of non performing loans for UDB over the period 2008 to 2009 remained high
at 33% compared to Bank of Uganda standard of 5%. Given this poor loan quality, the
value of credit risk management and loan performance in development financing has
attracted significant attention to stakeholders in the financial sector calling for the need of
a quality credit risk management policy as this exposes the banks to high levels of credit
risk.
2
1.1
Statement of the Problem
Loan performance is a major constraint affecting the success and survival of development
finance institutions (DFI) in Uganda. Out of total loan portfolio for UDB and DFCU in
the year 2009 of UGX. 40.4 billion and UGX 326.2 billion, about 32% and 5.3% was non
performing respectively. This poor loan quality exposes the two institutions to high levels
of credit risk. If this is not checked, it would result in depletion of the capital base which
may lead to their collapse.
1.2 Purpose of the Study
This study examines and compares the relationship between credit risk management and
loan performance in the two development finance institutions.
1.3
(i)
Objectives of the Study
To examine the relationship between loan appraisal (avoidance) and loan
performance
(ii)
To examine the relationship between other risk management techniques and loan
performance
1.4
(i)
Research Questions
Is there a relationship between loan appraisal (avoidance) and loan performance?
(ii)
Is there a relationship between other risk management techniques and loan
performance?
1.5
(i)
Significance of the Study
This study shall contribute to existing knowledge on how to institute and
implement a credit risk management process to strengthen loan performance
(ii)
The results shall also contribute to the formulation of a risk management policy
for several financial institutions.
3
It shall also broaden the researchers understanding on the subject of credit risk
management and loan performance.
1.6

Scope of the Study
Geographical Scope
The study was carried out in Kampala where the two development finance institutions
are located.

Subject Scope
The study focuses on appraisal, credit rating, financial viability, technical feasibility,
risk transfer, risk diversification, risk retention and their relationship to loan
performance.
1.7
Conceptual Framework
The model below explains the relationship between credit risk management and loan
performance as developed by McNaughton et al, (1996). In this model, credit risk is
divided into two components namely: the appraisal component, and other risk
management techniques. Appraisal has three elements namely:
technical feasibility,
credit rating, and financial viability. On the other hand, other risk management
techniques has elements namely; risk transfer, risk diversification and risk retention. The
two components form the basis for monitoring and managing credit risk as explained by
Harrison, (1996). The two components of risk management if properly applied in a
financial institution will lead to loan performance. Loan performance has indicators like
ratio of non- performing loans to total advances, and ratio of provisions to total advances.
4
Figure i.` Conceptual Frame work
CREDIT RISK MANAGMENT
OTHER FACTORS:
Economic, social,
political, and
technology
Risk Avoidance
(Appraisal)
- Background
of applicant
(credit
history)
- Technical
feasibility
- Financial
viability
- Credit rating
LOAN
PERFORMANCE
Ratio of Non
performing loans
to total advances
Ratio of provision
to total advances
Other risk
management
techniques:
- Risk transfer
-Risk diversification
-Risk retention
analysis
Source: McNaughton et al, (1996).
1.8
Organization of the Report
This study has been organized into five chapters. Chapter one introduces the study
beginning with a brief background to the problem, a statement of the research problem,
the objectives and research questions, the significance and scope of the study and the
conceptual framework. Chapter two presents a detailed review of relevant literature
written about appraisal, technical feasibility, financial viability, credit rating, and how
these variables relate with loan performance. It also presents other risk management
5
techiniques namely risk transfer, risk diversification, risk retention and how they relate to
loan performance. Chapter three provides the methodology used to obtain data, how the
data was analyzed, and what factors were taken into consideration. It also gives the
limitation of the study. Chapter four gives the findings of the study and a brief
interpretation of the results with respect to the objectives of the study. Chapter five
contains the summary of the findings, detailed interpretation of the results, conclusions
and recommendations for further research.
6
CHAPTER TWO
2.0
Literature Review
Introduction
In this chapter a critical review of related literature is carried out. The chapter is
discussed following the variables used in the study. It begins by discussing and giving an
overview of the credit risk management, discusses the appraisal, credit rating, financial
viability, technical feasibility. The second part focuses on other risk management
techniques like risk transfer, risk diversification, risk retention. It ends by looking at loan
performance and giving ratio indicators that show loan performance.
2.1
Credit Risk Management
Altman and Kao, (1991), Carty and Fons, (1993), argue that credit risk involves the
possibility that the inherent risk of the asset migrates to a lower quality level, thereby
resulting in lower security values in a market-to-market pricing environment. Over the
last decade, a number of the world’s major development finance institutions and banks
have developed sophisticated systems to quantify and aggregate credit risk across
geographical and product lines, BIS, (1999). The initial interest in credit risk models
stemmed from the desire to develop more rigorous quantitative estimates of the amount
of economic capital needed to support a bank’s risk-taking activities, and more so to
assess the overall risk management aspect of any given institution.
Altman, (2004) supported the above argument by discussing that in credit risk
management, models are developed to allow a tailored and flexible approach to price
measurement and risk management. In this paper, it was discussed that models are, by
design, both influenced by and responsive to shifts in business lines, credit quality,
7
market variables and the economic environment. Furthermore, models allow banks to
analyze marginal and absolute contributions to risk, and reflect concentration risk within
a loan portfolio hence contributing to an improvement in overall credit risk management
culture. According to the BIS, (1999) report, the degree to which models have been
incorporated into the credit risk management and economic capital allocation process
varies greatly from one finance institution to another. While some have implemented
systems that capture exposures throughout the organization, others only capture
exposures within a given business line or legal entity. These report further points out
those internal applications of model output spans a wide range; from the simple to the
complex. Current applications included: Setting of concentration and exposure limits,
Setting of hold targets on syndicated loans, Risk-based pricing, Improving the risk/return
profiles of the portfolio, Evaluation of risk-adjusted performance of business lines or
managers using risk-adjusted return on capital (“RAROC”) and Economic capital
allocation. Institutions also rely on model estimates for setting or validating loan loss
reserves, either for direct calculations or for validation purposes. From BIS, (2001) report
on: “Update on Work on the New Basel Capital Accord”, another important measure of
credit risk is that of value at risk ( VaR). According to this report, the estimated
economic capital needed to support a bank’s credit risk exposure is generally referred to
as its required economic capital for credit risk. The process for determining this amount
is analogous to value at risk (VaR) methods used in allocating economic capital against
market risks. According to Slijkerman, (2002), banking supervisors and the banking
industry have been discussing the wider application of the Value-at-Risk approach to risk
management and capital regulation. Their argument is that to evaluate credit risk
8
inherent in individual loans, banks use a standardized approach to risk assessment, which
involves evaluating corporate loans by employing the ratings on unsecured debt issues
provided by external credit rating agencies. Under this approach, loans to corporations
would be allocated among a number of risk categories, each carrying predetermined risk
weights. Alternatively, banks with sufficiently developed risk assessment systems may
use an internal-ratings-based method to estimate the credit risk of their portfolios.
Thakor, (1996) argues that imperfect information on loan applicants can cause credit
rationing, and increase on the credit risk exposure to banks . Thakor further argues that
Credit Value-at-Risk (CVaR) regulation counters the problem of high risk loans and therefore
reduces the risk of the bank loan portfolio. . However, Thakor fails to provide a model to be
used to asses VaR in loan portfolio . The capital requirement, risk standards and Credit
Value-at-Risk regulation distorts the functioning of credit markets. However, the binding
risk constraint introduces credit rationing. According to Wiley, (1998), imperfect
information on creditors can cause credit rationing. The consequences of the introduction
of simple and risk-weighted capital adequacy requirements and rationing have been
studied intensively, both empirically as revealed by the Basel Committee on Banking
Supervision (1999), and theoretically as discussed by Freixas and Rochet (1997) work.
2.2
Appraisal (Avoidance)
According to Rupp, (2002), credit risk management is a process that involves a series of
steps; identifying and analyzing loss exposures through the appraisal technique,
measuring loss exposures, selecting the technique or combination of techniques to be
used to handle each exposure, implementing the techniques chosen and monitoring the
decisions made and making appropriate changes. It is also the support, control systems
9
and other practices necessary to manage the outstanding risk assets, normal repayment
and to monitor business risk. The appraisal technique involves credit initiation,
evaluation, negotiation, and approval of facility. As an important step in initiation
process, credit officer should visit the potential customer to gather information on client’s
business, mode of operation, management, and financial situation. Banks should base
their credit analysis on the five C’s principals of lending. The 5Cs as discussed by
Pandey, ( 1997), Van Horne, (1998), Sinkey, (1998) and Allyn Bacon, (1996) include the
customer’s character as determined by their honesty and ethical reputation. It also refers
to the capacity of the client as determined by their cash flows, and capital as determined
by the client’s real net worth. The collateral pledged for the credit facility is another
aspect, and the condition, that is the vulnerability of economic fluctuations. In credit
evaluation, a consistent and rating scheme to all investment opportunities should be
applied if credit decisions are to be made in consistent manner which results in aggregate
reporting of risk exposure Santomero, (1996). Several authors ( Santomero (1996),
Bannet (1984) and Harrison (1996) agree that credit scoring should be used in the
appraisal process to predict the credit worthiness of would be borrowers. However,
external factors like competition, economic cycle, natural disasters, technological
advances, regulatory changes, industry changes, demographic factors affect the credit
evaluation process and this at times results in problem loans Wayne, (1998).
2.3
Credit Rating
According to Treacy & Carey, (2000), credit risk rating in large U.S. Banks and
development finance institutions are becoming increasingly important in credit risk
management. They argued that credit rating summarizes the risk of loss due to failure by
10
a given borrower to pay as promised. However, each development finance institutions’
rating systems differ significantly from the other both in architecture and operational
design as well as in the uses to which ratings are put. One reason for these differences is
that, ratings are assigned by bank personnel and are usually not revealed to outsiders. For
large development banks, whose borrowers may number in the tens of thousands, internal
ratings are an essential ingredient in effective credit risk management. In short, risk
ratings are the primary summary indicator of risk for banks’ individual credit exposures
and risk rating are provided mainly by risk rating agencies. Credit rating agencies gather
and analyze all sorts of pertinent financial and other information, and then use it to
provide a rating of the intrinsic value or quality of a security as a convenient way for
investors to judge quality and make investment decisions Hickman, (1996). Hickman
showed that during the twentieth century in the United States, ratings provided investors
with
information that reflected the likelihood that an issue would go into default and
guidance as to the loss consequences of such events. How well did ratings agencies
perform in assessing probabilities of defaults in the state and local debt markets is the
question that all stake holders always seek an explanation. Hempel, (1971) studied 264
agency-rated issues that defaulted in the great depression era in the United States and
came up with the finding that although these issues were small in numbers compared to
the total defaults of that era, they did represent more than three-fourths of the dollar value
of defaulted state and local debt. However, Partnoy, (1999) takes a cynical view of the
use of rating agencies. They argue with some vehemence that the agencies are in the
business of selling regulatory licenses. This view is less a critique of the agencies per se
than it is of financial regulatory authorities that adopt and use agency ratings in their
11
regulatory procedures. On the other hand, Firdson, (1999), a proponent of the newer view
of the independent rating agencies, argues that by prohibiting the asset managers from
investing in or retaining bonds of less than a specified rating, asset-owners and assetguarantors can significantly limit their risk through use of ratings, even though they lack
the expertise to quantify that risk themselves. According to Fridson, it is hardly a perfect
system, but it is a method of constraining and disciplining the behavior of asset managers
and issuers at a low monitoring cost.
Understanding how rating systems are conceptualized, designed, operated and used in
risk management is thus essential to understanding how development banks perform their
business lending function and how they choose to control risk exposures, Altman (1997).
The specifics of internal rating system architecture and operation differ substantially
across development banks. The number of grades and the risk associated with each grade
vary across institutions, as do decisions about who assigns ratings and about the manner
in which rating assignments are reviewed. In general, while designing rating systems,
development bank management must weigh numerous considerations including; cost,
efficiency of information gathering, consistency of ratings produced, the nature of the
bank’s business and the uses to be made of internal ratings. There is no one correct rating
system; instead, ‘‘correctness” depends on how the system is used. For example, a
development bank that uses ratings mainly to identify deteriorating or problem loans to
ensure proper monitoring may find that a rating scale with relatively few grades is
adequate. In contrast, if ratings are used in computing for example, bonds rated Aaa on
Moody’s scale or AAA on Standard & Poor’s scale pose negligible risk of loss in the
short to medium term whereas those rated Caa or CCC are quite risky.
12
Gonzalez et al, (2004), discussed that ratings provided by credit rating agencies (CRAs)
are a measure of the long-term fundamental credit strength of companies, their long-term
ability and willingness to meet debt servicing obligations. In their paper, they further
stress that CRAs base their analyses on a company’s financial statements, franchise
value, management quality and competitive position in its industry, and seek to predict
credit performance – the servicing of debt obligations in full and on time – under a range
of macroeconomic and credit conditions, including stress situations. This analysis is
based not only on public information, but also on private/confidential information which
companies agree to share with CRA. These opinions, which stem from fundamental
credit analysis, are used to classify credit risk and are vital to development finance
institution as well. The purpose of ratings is to measure credit risk in terms of probability
of default, expected losses or likelihood of timely payments in accordance with
contractual terms. Ratings are a cardinal measure of credit risk if used over an
unspecified long horizon Keenan, (1999), and Bahar, (1999). Indeed, over the long term,
ratings are found by academic studies to be an accurate and unbiased estimator of default
probabilities. Thus, while ratings are ordinal in their design, associations can be drawn
with cardinal probabilities of default in the long term.
It should be noted that, ratings do not explain certain variables taken to be vital to
business operations, like taxation, systematic risk, supply and demand, volatility hence
may not capture all the riskness of any business operation. The various studies that have
tried to answer the question of the information content of ratings in general come to the
conclusion that ratings do help explain cross-sectional differences in yield spreads of
bonds securities. Gabbi and Sironi, (2002) argue that while ratings are found to be
13
effectively the most important factor determining primary yield spreads between
corporate bonds and the equivalent treasury securities, other factors, such as expected tax
treatment for bonds, are also important. This was supported by Elton et al (1995), who
discussed that losses stemming from expected defaults come last among the three factors
that can explain corporate spreads. Expected losses are found to explain only 18% of the
variation in the spread. Differential taxes appear to be more important and explain about
36% of the spread. Hence, a large portion of the spread is a compensation for systematic
risk that cannot be diversified away.
On the other hand, Campbell and Taksler, (2003) analyzed the effects of equity volatility
on corporate bond yields, and showed that volatility was directly related to the cost of
borrowing for corporate issuers. Dufresne, et al (2001) on this issue of spreads argued
that monthly credit spread changes appear to be driven principally by local
supply/demand shocks that are independent of both credit-risk factors and liquidity.
However, Chen et al, (2003) find liquidity to also be an important factor explaining
corporate bond spreads and further indicate that liquidity should indeed be priced into
corporate bonds. Another factor that impact on rating is that of price changes. Numerous
studies have focused on the price reactions of bonds and equities to changes in ratings.
Klinger, (2000) focus on the refinement of Moody’s rating system in 1982, shows that
investors do indeed react to changes in ratings if they are unexpected, in the same way as
they react to new information.
14
A number of academic papers have investigated the informational efficiency of ratings in
relation to the level of changes in default risk. Some of these studies tested the
consistency of ratings across industrial segments and geographical regions. Ammer and
Packer, (2000) showed that, in some years, US financial companies obtained higher
ratings than other companies with similar annual default risks. Cantor et al. (2001) also
examined inconsistencies across several groups. These studies did not set out to control
for inconsistencies across narrower sectors or to determine any company-specific
variables, such as size or leverage. They only took account of Moody’s ratings and did
not address the question of the information provided by credit rating sub-categories.
Galil, (2002) examined the quality of corporate credit ratings in relation to their default
prediction power. The focus was on whether ratings efficiently incorporate publiclyavailable information at the time of rating, the extent to which rating classifications are
informative and whether rating classifications are consistent across industries and
countries of incorporation. The results reveal that ratings could be improved by using
publicly-available information such as size, leverage and availability of collateral.
Therefore, combining such public information, industry classification with ratings could
produce a better assessment of default risk. Despite the fact that ratings have some
undesired qualities, the real informational content of ratings cannot be disregarded.
Ratings provide a better assessment of default risk than public information alone. This
result is consistent with the findings of Kliger and Sarig, (2000) and may confirm that
CRA activity adds value, even though ex-post ratings are not found to be entirely
consistent across industries and the narrowness of rating categories is found to be not
particularly informative.
15
2.4
Technical Feasibility
An assessment of the technical viability of a project, appropriateness of production
technology and availability of equipment are an essential component in credit risk
management that determines production capacity of any given firm. According to Faria,
(2002), technologies produce impact on the production process. In fact, being first to
adopt a new and more efficient technique means being able to enjoy productivity gains
before rivals. In other words, technical change fuels productivity. Therefore, it is
certainly useful both from the point of view of firms, financial institutions and policy
makers to understand the rate of adoption of new technologies in order to asses the
potential impact of technical change on productivity which has an implication on the
efficiency in loan servicing. Another firm level characteristic that has traditionally been
investigated as regards technology adoption is its R&D activity. Cohen and Levinthal,
(1989) argue that R&D provides a measure to reflect the firm’s ability to assimilate and
process new technological information at a minimum cost. Existing empirical evidence
show mixed results. Whereas Karshenas and Stoneman, (1995), Colombo and Mosconi,
(1995), do not find a statistical significant coefficient of this variable, Baldwin and
Diverty, (1995) show a highly significant positive effect. Despite the mixed results, R&D
activity is an important source of learning that can bring into new production methods
and product mix.
2.5 Financial Viability and Financial Analysis
According Griffith, (1985) in his work on personal financial statement analysis, discussed
that analysis of corporate financial statements is a well-established procedure. Investors
and loan officers apply a variety of ratios in judging the attractiveness or creditworthiness
of a company. However, the same does not seem to be true of personal financial
16
statements. Personal finance literature (theory) tell people that they should prepare a
financial statement (probably annually) as part of their financial planning, but almost
none tell much about how to judge the implications of such a statement.
Griffiths analysis of financial statements often involves some transformation of the
reported data. Techniques such as ratio analysis, percentage analysis and comparison to
industry data make it possible to identify significant relationships in a company's
financial data. These analysis techniques are most effective when they are applied to data
for several accounting periods which usually is possible because most companies report
two years of comparative financial statement data at each report date. According to their
work, analysis of financial statements may be divided into three parts; the firm's
profitability, capital position and liquidity position. However, the above scope of analysis
seems to capture less of the risk taken by the investor (financial institution). On the
contrary, the analysis of financial position should further focus on the long-term
indicators of risk taken from the balance sheet. In credit risk management, concern is
focused on the riskiness of a given customer. Hence use of leverage ratios that provide
information about the relative debt in the capital structure in the long run can help to
determine if the company has the ability to service both its current and long-term debt.
Therefore, the analysis of the capital structure will be based on two ratios: total liabilities
to total assets and times interest earned.
2.5.1 Financial Analysis
According to the Asian Development Bank,( 2003) operations manual bank policy report,
the term financial analysis comprises a quantitative and qualitative examination in
17
sufficient depth to determine the reliability of the financial data pertaining to a project, a
sector, and an executing agency. As an integral part of project preparation, ADB requires
the use of financial analysis and an assessment of the financial policies and the capacity
of the financial management systems practiced or proposed by the borrower or executing
agency to support project implementation and operation. Executing agencies are to
maintain a financial management system that ensures accountability, efficiency,
economy, and solvency. The scope of assessment of the financial management systems,
the extent of financial analysis required, and the formulation of financial performance
indicators are discussed below.
2.5.2
Analysis of the Executing Agency
Sensitivity analysis on key risks affecting the achievement of the Project’s development
objectives and assessment of the financial policies and the actual and forecast efficiency
and viability of the executing agency's financial operations as well as the financial
performance indicators adopted as covenants for project monitoring
Assessment of the executing agency’s solvency, liquidity, and profitability during the
loan period
2.6
Risk Transfer
According to the International Association of Insurance Supervisors (2003), Financial
Services Authority (2002), and Rule (2001b) who examined credit risk transfer between
banks and non-bank financial sectors, including the insurance sector argue that banks are
shifting credit risks from their balance sheets to insurance companies, amongst others,
and insurance companies are issuing catastrophe bonds that are being sold to institutional
investors such as investment funds and other end-investors. Although risk transfer
18
markets have the potential to enhance financial stability by diffusing exposures, there are
concerns that they may equally lead to more concentrated and non-transparent risks,
Andersen, (2001). This was supported by Häusler, (2004) who discusses how the blurring
of boundaries between insurance and other financial institutions implies heightened
importance of insurers for financial stability. It is also inline with the work of Podpiera,
(2003) who explored the potential for the insurance sector to affect the vulnerability of
the financial system, focusing on the banking-type activities that life insurance companies
have increasingly taken on, as well as risks stemming from the possible failure of a large
reinsurer. To achieve the risk transfer, use of derivatives has gained significant
importance in the financial sector as Standard and Poor’s (2003b) and Fitch Ratings,
(2004) provide a review of the factors underlying banks’ use of credit derivatives.
Rule, (2001) pointed out that that banks and insurance companies are exposed to various
credit, market and insurance risks in the course of their business, and they can manage
these risks in three ways: Arrange for another entity to take on the risk at the outset. For
example, a bank might arrange a bond issue for a corporate customer rather than lending
itself; or an insurance company might arrange for a customer to ‘self-insure’ by
establishing a captive insurance company rather than buy insurance cover.
They can also retain risks on their balance sheets and seek to control them through
careful monitoring, pricing and diversification and hold the risk only temporarily before
selling it into a secondary market, hedging it with another offsetting transaction or
repackaging it in order to sell/hedge it. In principle, firms can use risk-transfer methods to
disperse risks making them less vulnerable to particular regional, sectoral or market
shocks.
19
Banks have tended to take on a bundle of risks attached to term lending but more crucial
among them all is the credit risk since it affects borrower’s willingness and ability to pay.
The past decade has seen a growing range of new techniques and markets for transferring
risk which include:
2.6.1
Loan Trading.
Markets for trading of individual loans are well established particularly in the United
States but also to a lesser extent in other countries including the United Kingdom.
Institutional investors and specialist loan funds have in recent years taken up around half
of many syndicated loans in the United States. Much of the secondary trading was
initially in distressed debt (trading at less than par) but the 1990s saw growth in par debt
trading.
2.6.2
Portfolio securitization.
According to Modak, (2001), securitization has emerged globally as an important
technique for bundling assets and segregating risks into marketable securities. This
typically involves the transfer of assets from the originator to a vehicle company which
then issues securities to investors backed by the cash flows on the transferred assets. The
transaction is intended to remove risk from the balance sheet of the originator while
ensuring that investors are exposed to the transferred assets only. It allows investors to
improve their yields while keeping intact or even improving the quality of investment
Vora, (2001). In this era of bank consolidations, Collateralized debt obligation and assets
backed securities can help banks to proactively manage their portfolio. This is supported
by Standard and Poor, (2003) who argued that asset backed securities, and collateralized
debt obligations can help banks in restructuring their stressed assets. Asset-backed
20
securities typically shift credit risk on pools of relatively homogenous assets such as
residential mortgage loans, credit cards or car loans. These transfers of credit risk on
diversified corporate bond or loan portfolios are known as collateralized debt obligations
The above argument is supported by the Ugandan Banker, (2004) where it is discussed
that asset securitization is a process that involves the packaging of individual loans and
other debt instruments, converting the package into a security or securities and enhancing
their credit status/ rating to facilitate their sale to third party investors. A critical element
of asset securitization is the creation of a special purpose vehicle to purchase loans and
issue asset backed securities on their collateral. The special purpose vehicles may be a
subsidiary of the originator of the loan, or of the investment bank that underwrites and
distributes securities. The whole essence of special purpose vehicle to create a clean and
legal break in the transaction for it to be regarded as asset sale without recourse.
2.6.3
Derivatives and Credit-enhancement Mechanisms
According to Erin, (2003), credit derivative transaction involves one party shedding
credit risk (in other words, buying credit protection) and another taking on this risk
(selling credit protection). Credit risk can be transferred in part or in its entirety either by
buying credit risk protection to reduce credit risk exposure or by directly selling the
credit-risk bearing instrument. Sellers of credit protection take on credit risk in a manner
similar to purchasers of corporate bonds, loans, or other credit instruments. Credit
derivatives remain a small but rapidly growing market and are increasingly used in both
market-based and relationship-based systems. According to the work of Kiff, (2003),
insurers have made some use of credit derivatives to gain additional credit exposure and
21
to diversify credit risks. British Bankers’ Association, (2002) points out that credit
derivatives can be classified into two broad categories; those that transfer the credit risk
relating to an individual borrower (single-name products) and those relating to a number
of borrowers (portfolio products). Examples of these two categories are single-name
credit default swaps and collateralized debt obligations respectively. In a credit default
swaps transaction, the protection seller agrees to pay the protection buyer if a reference
entity (a company or sovereign) experiences a predefined “credit event,” such as a default
on a debt obligation. According to the Financial Services Authority, (2002), the
protection seller receives a premium (typically paid quarterly) from the protection buyer
over the lifetime of the transaction. According to Parsley, (1996), derivatives are
transactions to exchange future payments contingent upon the future behaviour of a welldefined variable. In this paper, the most actively-traded derivatives are based on interest
rates, exchange rates, commodity prices, bond prices and equity indices and mostly have
short maturities.
McDermott, (1997) and the Economist, (2001) supported this by pointing out that creditderivative market is growing as banks, securities firms, corporations, and other
institutions seek to hedge their credit exposures or realign their lending portfolios. The
derivative seller provides insurance against an event of default that changes the value of
the underlying asset. In all of these cases, the relationship between the original borrower
and lender is preserved except in the outright sale of the credit asset in the secondary
market. It is important to note that the seller-counterparties in credit-risk derivative
transactions, or the more traditional credit insurance providers, are increasingly mindful
of managing and trading their own credit portfolios, hence, these institutions are
22
particularly interested in techniques that combine the stand-alone and portfolio aspects of
their revenue-based assets. The credit-risk derivative and credit-enhancement markets
have been improving, and will continue to improve the credit market’s liquidity, and vice
versa. This development, in turn, will require more accountability and transparency of
asset values and will also motivate attempts to price the products more profitably.
2.6.4
Alternative Risk Transfer (ART)
ART is a catch-all term for a range of less conventional ways – some developed in the
1980s, others more recently – in which general insurance companies can take on and shed
risk.
It embraces insurance of new types of risk such as credit portfolios.
These
instruments and techniques are being used increasingly to shift credit, market and
insurance risks amongst banks, insurance companies, reinsures and other capital market
investors, such as pension funds and mutual funds.
According to the European Investment Bank report 2004 on “Credit risk transfer by EU
Banks: Activities, risks and risk management May 2004, it is discussed that banks
involved in portfolio management use credit risk transfer instruments for credit risk
shedding (protection buying) and/or risk taking (protection selling) purposes. In this
activity, banks typically aim to run matched credit risk positions. From their survey
conducted among European Union Banks, it reveals that for the portfolio management
banks that were involved in risk- shedding, the main motivation was to reduce the risks
related to single entities, to obtain capital management benefits and regulatory capital
relief, and to access funding through securitization. For the banks that used the market to
take on credit risk, the main reason given was to diversify credit risk by acquiring claims
23
on firms that would otherwise not be accessible to them through regular client
acquisition. The key motivation for banks to sell protection was the diversification of
risk. In some countries, a need to find profitable additional investments was also regarded
as an important motive, especially if the volume of deposits outweighed that of loans.
According to the Uganda Institute of Bakers, (2004) report, banks with a specialized or
narrow customer base have resorted to protection selling in order to diversify the credit
risk in their banking book, particularly as the ability to originate credit risk transfer
instruments to shed risk can be quite constrained by the nature of a bank’s assets (for
example, non-rated small micro enterprises loans). In the case of banks with a wider
customer base and more widespread activities (lending, asset management, investment
banking), versatility has enabled them to buy protection on one side while selling it on
the other.
2.7
Risk Diversification
Brannan, (2000), argued that diversification is the primary tool for lenders to control
borrower risk, and highlighted the fact that risks arise well before default occurs and
warned against the construction of "bullet-proof" portfolios that can under perform. Jose
Lopez, (2000), supported this by discussing that there was value in diversification of
credit portfolios and pointed out how this value can be measured. However, there are
several factors that contribute to the degree of diversification for a credit portfolio and
because these factors vary over time, the measurement of credit diversification is
particularly challenging. Wilson, (1998), brought out the benefits of diversification in
credit portfolios. The finding indicate that there is a significant difference in performance
of portfolios concentrated in one region from that diversified to different economies.
24
Therefore, Wilson’s argument focuses on advocating for diversification of loan portfolios
across nations where the benefits are much stronger than they are when diversification
occurs across sectors in a given economy. However, the above argument is criticized by
Campbell et al. (2001), who discussed that
the degree of diversification for a credit
portfolio will depend on several other factors like; Size of the portfolio, and issues of
maturity variation.
2.8
Risk Retention
According to Sanderson, (1991), today’s business environment demands lean, cost
efficient operations with no waste. As an important part of this process, risk managers
seek to reduce the economic impact of risk on their organizations through opting for
greater levels of risk retention. Risk retention analysis will help you decide how much
risk you are able to retain which could be accomplished through risk rating models
Amato et al, (2004). Gordy’s, (2003) work shows that, knowing the right amount of risk
to retain promotes financial efficiency. Risk retention analysis provides you with answers
to the following question; How much risk is there in my current loan structure? This
provides you with a risk retention capacity for your organization or financial institution.
Consideration is given to a number of factors in order to derive an estimate of the ability
to retain risk. These include; Historical financial information from reports & accounts,
future financial projections for the organization, market conditions and economic trends.
As a result of this, the rate of interest charged should be adjusted to reflect the level of
risk being retained. It should be noted that risk retention review should be a never-ending
process for the risk management professional. It should be noted that the decision to
25
retain risk is a function of the materiality of the risk, its predictability, and the transfer
costs avoided. The measure of a successful risk financing program is its responsiveness to
a substantial occurrence. In a publicly traded organization, the reason for retaining added
risk is to increase earnings, and earnings are a substantial factor in determining the price
of the equity shares of the company and the company's overall value.
Insurance industry trends show that risk retention groups emerge during volatile times,
but their efficacy should still be questioned. From the work of Kolodkin, (2001), the
return of hard market conditions, buyers will seek options outside of the commercial
marketplace and alternative risk funding vehicles promise pricing stability and more
control for the insured. The question that remains is, are these promises that alternative
markets, and specifically risk retention groups can keep? Does retaining additional risk
yield additional earnings? Clearly, risk assumption can meet this test if loss experience is
favorable and the cost of risk transfer is uneconomical compared to risk assumption.
Increasing risk retention, regardless of risk financing structure, may save premium
payments, but without a thoughtful review of the return on investment, organization's
economic value may not be maximized.
2.9 Loan Performance
The concept of loan performance refers to the ratio of non performing advances (loans) to
the total portfolio. A non performing advance/loan is that part of loan whereby interest
and principal installment are still outstanding for at least six months after they are due
Mugoya, (1972), and Bank of Uganda, (1992). It can be calculated as follows:
None performing ratio =
{Non Performing advances} X 100
Total loan portfolio
26
According to Bank of Uganda report (1992), a ratio of 10% is accepted to be nonperforming and the higher the ratio, the worse the loan performance. Performance of loan
portfolio may be measured using proxies for credit risk and measures of loan quality such
as provision for loan loses, net losses or charge offs, non performing assets, return on net
assets and return on equity among others. A high proportion of loans to total assets and
rapid growth of the loan portfolio are potential early warning signals of loan quality
problems which indicate potential failure Sinkey, (1998). As noted by Peterson (1981),
simple comparisons of average loan performance between two groups of borrowers can
be misleading if the groups do not exhibit similar distributions of expected returns. If, for
example, the proportion of highly qualified non-minority borrowers is substantially
higher than that of highly qualified minority borrowers, default rates of non-minority
borrowers—observed without controlling for other determinants of credit quality would
be lower than those associated with mi-nority borrowers. This finding, however, would
simply reflect the differences in average creditworthiness for the two groups of borrowers
and would not necessarily indicate differential underwriting standards Ferguson and
Peters (1995). Simple bivariate correlations suggest that default probabilities differ
significantly by loan, borrower, and location characteristics. For example, higher default
rates appear to be associated with higher loan-to-value ratios, lower incomes, and smaller
loan amounts. Another caveat is that the basic theoretical prediction that discrimination
results in better observed relative loan performance depends on the assumption that
lending bias takes the form of different standards of creditworthiness for different groups.
27
2.10 Relationship between Loan Appraisal and Loan Performance
Recent studies of lending activity have documented large and
persistent
disparities on the relationship between appraisal and performance Canner, et al (1991).
From the studies done on mortgage lending to minority and non minority borrowers in
the United States, the basic premise is that biased lenders will require higher expected
profits for loans to minority borrowers and hold minority applicants to underwriting
standards in excess of those required for other applicants Becker, (1971). Thus
discrimination through appraisal process results in lower expected default costs for loans
originated for marginally qualified non-minority borrowers Munnell, et al, (1992). This
premise implies that biased lenders may hold minority applicants to more stringent
underwriting standards than those required for other applicants Peterson, (1981). Thus
discrimination results in lower expected default costs and higher expected profits for
loans originated for marginally qualified minority mortgage borrowers in comparison
with those observed for marginally qualified non-minority borrowers. It is important to
note that this theory assumes that discrimination against minorities occurs at the margin,
affecting those who are near the borderline for creditworthiness, and excludes the
possibility that the discrimination is unrelated to credit risk. The theory predicts that this
discrimination
changes
loan
performance
at
the
margin.
Thus
inferences
about discrimination that are made from loan performance data must distinguish between
average and marginal loan performance. Hence, as noted by Peterson, Ferguson and
Peters, (1995) also supported this argument by stating that simple comparisons of average
loan performance between two groups of borrowers can be misleading if the groups do
not exhibit similar distributions of expected returns in the absence of distribution.
28
2.11
Relationship between other Risk Management Techniques and Loan
Performance.
In their work, Samolyk et al, (2003) studied geographic diversification since 1994 using
geo-coded data reported by banks to the Federal Deposit Insurance Corporation, and
investigated how diversification is associated with Bank Holding Company portfolio
choices and performance. Their findings show that geographic diversification across
markets leads to an improvement in the risk/return tradeoff facing a given bank. A key
point is that diversification does not necessarily imply safer banks. Depending on their
preferences, some bank owner may respond to the improved investment by taking
additional risks via increasing leverage, increased holding of risky assets, or both. The
lack of performance gains from geographic diversification is not inconsistent with the
findings of Acharya et al, (2002) who studied diversification by Italian banks. Acharya,
(2002) find that diversification across industrial loan groups is associated with lower
bank returns. However, Hughes, (2001) find that once one incorporates risk and financial
capital into the production frontier techniques, the estimate financial returns to scale
(largely through capital savings) are considerably larger than when risk and capital are
ignored. In their study of publicly-traded bank holding companies (BHCs), Demsetz,
(1997) found out that the larger bank holding company were better diversified across
regions and loan types, such diversification reduced the volatility of banks’ stock returns
and improved the loan performance. Nevertheless, spreading out financial operations
over a broader space does not come without costs. DeYoung et al, (1999) found out that
inefficiencies tend to increase with the distance between a bank holding companies
headquarters and its subsidiaries, presumably because the managers at subsidiary
branches tend to have some levels of mismanagement that may affect returns. It should
29
be noted that distinguishing diversification effects from scale effects is difficult as they
tend to happen almost at the same time, that is to say, banks get bigger ie (more assets)
and wider (more markets) all happen at the same time. The costs associated with scale
changes (diversification) may confound or conceal the savings and risk effects we expect
to find from diversification across markets.
30
CHAPTER THREE
3.0
Research Methodology
This chapter specifies the research design used criteria for sample selection, data sources,
instruments used for data collection, data processing, and analysis. The chapter ends with
a review of limitations encountered during the study.
3.1
Research Design
This study was an explanatory and cross- sectional design. It identified elements of
credit risk management and examined how they affected loan performance. Research
investigated and compared the relationship between credit risk management and loan
performance in both UDB and DFCU Ltd. It was a combination of cross-sectional and
analytical study mainly based on secondary data, but also accomplished with primary
data obtained through in-depth interviews with technical staff who work in the two
institutions with a credit related function.
3.2
Population
The population comprised of 25 technical staff of UDB and 75 from DFCU, hence the
total population targeted was 100.
3.3 Sample size
Using purposive sampling design, data was collected from 11 technical staff from UDB
with a credit related function and 35 from DFCU Ltd, hence the total sample size was
selected for interview
was 46. Purposive sampling design was used because only
technical staff was targeted to respond to the questionnaire.
31
Table 2. Sample size selection
Level
UDB
DFCU
Total
3.4
Total population
25
75
100
sample size
11
35
46
Data Collection Instruments
 Questionnaire
Primary data was collected using questionnaires which were distributed to different staff
members in the two banks especially those either with a credit function or have prior
experience in credit operations or those with a function connected to credit. The
questionnaire had two parts. The first part captured elements of the appraisal namely
technical feasibility, financial viability, and credit rating. The second part captured
components of other risk management techniques namely; risk transfer, risk
diversification, and risk retention.
3.5 Sources of Data
3.5.1 Primary Data
Primary data was obtained through questionnaires distributed to staff in the two banks
especially those with a credit function or with prior experience in the credit function.
3.5.2
Secondary Data.
Secondary data was obtained from journals, and annual reports of the two banks.
32
3.6
Measurement of variables
 Appraisal was measured as a composite of technical feasibility, financial
viability, and credit rating using attitude statements of a 4 – point Likert –
scale ranging from relevant, quite relevant, some how relevant and not
relevant.
Other risk management techniques was measured as a composite of risk
diversification, and risk retention using a 5–point Likert scale ranging from
relevant, quite relevant, some how relevant and not relevant.

Loan performance was measured by ratio analysis using secondary date
obtained from the annual reports of the two banks. The two ratios used are:
ratio of non – performing loans to total advances, and ratio of provisions to
total advances.
3.7 Validity and Reliability Tests
 Reliability tests
Cronbach alpha was used to determine the consistency of scales used to measure study
variables. All the Cronbach alpha coefficient for credit risk management constructs were
above 0.6 implying that the scales used to measure credit risk management constructs
were consistent and therefore reliable as shown in the table 3 below.
33
Table 3. Reliability Coefficient
Variable
Cronbach
Coefficient
Credit history
0.8228
Technical feasibility
0.7777
Financial viability
0.8428
Credit rating
0.7402
Risk transfer
0.7687
Risk diversification
0.6797
Risk retention analysis
0.7271
Appraisal
Other risk management
Techniques
Source: Primary data

Validity test
Content validity test index (C.V.I) was used to test for validity of questionnaire. A four
point scale of relevant, quite relevant, some how relevant and not relevant was used by
two experts to rate the relevancy of questions on the questionnaire on the study variables.
The two C.V.Is for the two experts were above 0.5 which indicated that the instrument
was valid for the study. The content validity tests were C.V.I
0.7283.
34
(1)
= 0.8226, C.V.I
(2)
=
3.8
Data Analysis
Data was edited, coded for completeness, and processed using computer software called
the statistical package for social scientist (SPSS). This was chosen because it is able to
compute all the statistical quantities that were required for the interpretation of the data
that was collected from the field.
Spearman’s correlation coefficient was used to determine the strength of relationships
between the two variables ie credit risk management and loan performance. On the other
hand, the dependent variable (loan performance) was measured using ratio analysis ie, the
ratio of non performing loan to total advances, and the ratio of provisions to total
advances.
3.9
Problems Encountered in the Study
The major problem encountered was that of delays to fill questionnaire which arose due to
busy schedules of technical staff that were targeted. However, this was overcome by
scheduling follow up on a weekly basis until all the questionnaire distributed fully received
response.
35
CHAPTER FOUR
4.0
DATA PRESENTATION, ANALYSIS AND INTERPRETATION
4.1
Introduction
This chapter comprises of presentations of results, and their interpretation. The results are
presented according to study objectives which were: (i) to examine the relationship
between loan appraisal and loan performance. (ii) to examine the relationship between
other risk management techniques and loan performance.
The chapter begins with a background description of statistics, then factor analysis which
was used to extract factors that measure the credit risk management variables, and
inferential statistics that show the relationships between study variables.
4.2
Demographic Data
The results that follow show the background characteristics of the respondents that were
involved in the study. 46 questionnaires were administered to respondents in the two
banks namely Uganda Development Bank, and Development Finance Corporation of
Uganda. Overall, 46 responded to the questionnaires which represented a response rate of
100% as reflected in the table 4 below.
Table 4.
Response Rate
Institution
Frequency
Percentage
DFCU
35
76
UDB
11
24
Total
46
100
Source: primary data
36
According to the results in the table 4 above, the greatest number of respondents was
from DFCU Ltd (35 respondents) representing 76% of the total number of respondents.
On the other hand, about 24% of the respondents were from DFCU Ltd
4.2.2 Gender of Respondents
Cross tabulation were used to study the status of respondent distribution by gender as
shown in the table 5 below.
Table 5. Gender Distribution.
Frequency
Percentage
Male
19
41.3
Female
26
56.5
Non response
1
2.2
Total
46
100
Source: Primary data
Results in the table 5 above show the majority of respondents were females representing
about 57% and about 41% of those interviewed were males.
4.2.3 Qualification of Respondents
The status of respondents with respect to the highest qualification attained was obtained
and the findings are indicated in the table 6 below:
37
Table 6. Status of Respondents by Qualification
Frequency
Percentage
Diploma
1
2.0
Degree
5
10.9
Masters
34
73.9
Phd
6
13.0
Total
46
100.0
Source: Primary data
According to table 6 above, about 74% of the respondents had a postgraduate
qualification.
4.2.4 Working Experience in the Bank
Cross tabulation was used to obtain the working bank experiences of respondents as
indicated in the table 7 below.
Table 7. Previous Working Knowledge from Credit
Frequency
Percentage
Yes
26
56.5
No
18
39.2
Non response
1
4.3
Total
46
100.0
Source: Primary data
From the
table 7 above, about 57% has prior experience of working in the credit
department and figure 2 below also show the same result.
38
Figure 2. Pie Chart Showing Previous Working Experience
RESPONSE
NON
NO
YES
YES
NO
NON RESPONSE
4.2.5 Status of Respondents by Age
Cross tabulation was used to obtain the age distribution of respondents as indicated in the
Table 8. Age Distribution of Respondents
Frequency
Percentage
31-40 years
27
58.7
41-50 years
14
30.4
Above 50 years
5
10.9
Total
46
100.0
Source: Primary data
From the table 8 above show that about 59% of the respondents were aged between 31 40 years. This implies that data was obtained from mature people.
39
4.2.6 Working Experience in the Banking Sector.
Data was collected from the respondent on their experience levels from the banking
sector. Cross tabulation was computed and sued to study the status of respondent
distribution by experience of work as shown in the table 9 below.
Table. 9
Working experience in the banking sector.
Frequency
Percentage
2-5 years
10
21.7
6 -10 years
26
56.5
above 1 years
10
21.7
Total
46
100.0
Source: primary data
The results in the table 9 above indicate that the majority of the respondents had over six
years working experience representing about 57% of the total number of respondents.
4.3 Factor Analysis
Factor analysis was used to extract factors that measured the credit risk management
variables using the principal component analysis and varimax method. Factors with eigen
values > 1 were extracted and items with correlation coefficients below + 0.3 deleted
because they were considered to be having low contribution to the factors extracted.
Table 10 shows correlation coefficients for the four factors extracted: background of
applicant (credit history), technical feasibility, financial viability, and credit rating and
these form the appraisal component.
40
Table 10: Rotated Component Matrix : Appraisal
Component
1
2
We demand for a business plan from all clients/ borrowers
.742
We analyze the business plans to identify risk exposure
.742
We consider professionalism in the respective business
We look at the relevant experience in the loan applicant
.533
.711
We consider cash flow projections of a given project before finance
it.
We look at the long term planning horizon of every applicant.
We look at the conditions ie political, economic before we finance a
project
We look at collateral as a secondary source of repayment
We consider the accounts receivable and inventory as security
We look at capitalization of the business
We consider the net worth of the business
We consider the past track record of repayment
We look at character of the loan applicant
We look at the credit trustworthiness of loan applicants
We look at the leadership quality or capacity of managers
We periodically monitor projects financed.
We consider capacity of loan applicants
We request for past financial reports from all clients
We demand for audited financial reports
We analyze financial reports
We calculate the ratio analyze for the profitability, efficiency,
leverage
We analyze the growth in sales of our clients
Interest coverage ratio is important before we finance
We look for the sound management policies of our borrowers.
We only finance projects with sound financial management policies
We finance projects with potential market/ trade
We look at the consumption behaviour of the market.
We look at the marketing strategy of the loan applicant
We finance projects that use appropriate technology
We have qualified staff to assess the level of technology
We look at access to infrastructure
We look at the availability of raw materials before we finance a
project
We look at the implementation plan of all projects
We consider if a project has specialized man power
The bank has an internal credit rating system
We do credit rating on all projects
I participate in the design of credit rating system
41
3
4
.493
.405
.396
.319
.309
.557
.679
.745
.784
.747
.575
.542
.576
.595
.0482
.684
.514
.542
.490
.792
.315
.733
.676
.300
.443
.735
.343
.457
.525
.573
.561
.691
.510
.596
The bank quantifies risk through credit rating
We base our rating on financial reports
We rate the management capacity of loan applicants
Our rating system predicts debt servicing capacity of loan applicants.
The rating used can determine deteriorating / non performing loans
We use public and private information in rating
I know how to use rating system
The bank monitors all problem loans
Eigen
% of variance
.678
.485
.472
.535
.442
.421
.808
.660
9.11
6.090 3.860 3.254
19.383 12.974 8.213 6.923
Source: Primary Data
From the table 10 above, credit history has an eigen value of 9.11, and a percentage of
variance of 19.383. Technical feasibility has an eigen value of 6.090 and a percentage of
variance of variance of 12.974. Financial viability has an eigen value of 3.860 and a
percentage of variance of 8.213. Credit rating has an eigen value of 3.254 and a
percentage of variance of variance of 6.923.
Table 11 has factors extracted for other risk management techniques namely: risk
transfer, risk diversification, and risk retention and this form the component of other risk
management techniques. Their associated eigen values and correlation coefficients are
shown in the table 11 below.
42
Table 11. Rotated Component Matrix: Other risk Management Techniques
1
2
Our loan portfolio is fully insured
Clients are requested to provide financial guarantees
3
.569
.770
Our loans are guaranteed with fixed deposits
.767
We consider debentures as loans guarantee
.315
We participate in loan portfolio hedging against risk
.677
.761
.545
.679
.717
The bank use credit derivatives to hedge risk
The bank has used interest rates swaps in market
The bank uses forward exchange rate contract to hedge the risk
Risk transfer improves loan recovery
The loan portfolio is invested inn different sectors of the economy
.646
We do not concentrate our loan portfolio in particular sector of the economy
.634
Decision to diversify is taken by management
Diversification has reduced risk exposure in this institution
We invest in different loan products
Default level has reduced due to diversification
Retention is only used to cover a small portion of loss
Loss that is cored by retention is about 5% of the loan portfolio
We prefer covering loss from bank resources
.703
.396
.599
.396
.418
We have widely used risk retention to know how much exists in our loan portfolio
We constantly carry our loan retention reviews
The bank has risk management policy
The bank has pre-set concentration limits in every
The bank has preset portfolio limit
All staff members are evaluated
The bank quickly responds top market changes
We used risk based pricing in our loan portfolio
We periodically assess credit quality of our loan portfolio
Eigen values
% of variance
Source : Primary data
.574
.572
.692
.458
.679
.515
.785
.604
4.249 3.790 3.025
15.737 14.035 11.205
The results from the 11 above show that risk transfer had eigen value of 4.249 and a
percentage of variance of 15.737. Risk diversification had had an eigen value of 3.790
and a percentage of variance of 14.035. Risk retention had an eigen value 3.025 and a
43
percentage of variance of 11.205 implying that the variable extracted are relevant in
measuring credit risk.
4.4 Relationship between Variables.
Multiple correlations were used to establish the relationship between appraisal, financial
viability, technical feasibility, credit rating with loan performance. Loan performance
was measured using two ratios namely; ratio of non- performing loans to total advances,
ratio of provisions to total advances. The results of the above relationship are summarized
in table 12 below with corresponding correlation coefficients as tabulated.
44
Table 12
8
Spearman’s
rho
1
Appraisal
1
FVA
2 0.666**
TECHFEAS 3
RATING
2
3
4
5
6
7
1
0.683**
4 0.58**
1
0.628** 1
0.693** 0.679** 1
TRANSFER 5
0.485**
0.252
0.378** 0.329*
DIVERSIF 6
0.659**
0.338*
0.432** 0.414** 0.387** 1
RENTENTI 7
0.318**
0.055
0.001
MAGMT
0.638**
0.412** 0.588** 0.589** 0.306*
0.556** 0.044
0.575**
0.275
0.398** 0.352*
0.262
0.348*
0.400** 0.374*
0.575**
0.275
0.398** 0.352*
0.262
0.348*
0.4**
8
Provisions/Tot
0.162
1
-0.008
0.119
1
1
al
Advances
NPL/Total
Advances
45
0374*
4.4.1 Relationship between Loan Appraisal and Loan Performance
This section deals with objective one which was establishing the relationship between
loan appraisal and loan performance in the two banks. The researcher observed a
significant positive relationship between loan appraisal with Provision/Total advances
ratio (r = 0.575, P- value < 0.01). There was also a significant positive relationship
between loan appraisal and the ratio of non- performing loans to total advances (r =
0.575, P- value < 0.01) as shown in table 12.
4.4.2 Relationship between Financial Viability and Loan Performance
In line with objective one, there was a significant positive relationship between financial
viability and the ratio of provision to total advances (r = 0.275, P – value > 0.005).
Similarly, there was a significant positive relationship between ratio of non performing
loans to total advances (r = 0.275, P – value > 0.005).
4.4.3 Relationship between Technical Feasibility and Loan Performance
From the results in the table 12, there was a significant positive relationship between
provision to total advances, and non – performing loans to total advances ratio (r = 0.398,
0.398 P < 0.001) respectively. This was done following objective one of this research.
4.4.4 Relationship between Credit Rating and Loan Performance
According to the results as tabulated in table 12, there was a significant positive
relationship between credit rating and provisions to total advances ratio (r = 0.352, P =
value < 0.05). In the same way, there was also a significant positive relationship between
credit rating with ratio of non – performing loan to total advances ( r = 0.352, P = value
< 0.05).
46
4.5
Relationship between Other Risk Management Techniques and Loan
Performance.
This deals with objective two which was to establish the relationship between other risk
management techniques with loan performance. Note that other risk management
techniques have three variables namely; risk transfer, risk diversification, and risk
retention.
4.5.1 Relationship between Risk Transfers with Loan Performance.
According to table 12, there was a significant positive relationship between risk transfer
with provisions to total advances (r = 0.262, P> 0.05). In the same way, the researcher
also established that there was significant positive relationship between risk transfer with
non- performing loans to total advances (r = 0.262, P> 0.05).
4.5.2 Relationship between Risk Diversification and Loan Performance
From table 12, there was a significant positive relationship between risk diversification
with provisions to total advances, and non – performing loans to total advances (r =
0.348, 0.348 P < 0.05) as shown in table 12.
4.5.3 Relationship between Risk Retention and Loan Performance
Risk retention analysis helps to know how much risk is there in loan structure, and
provides you with a risk retention capacity for any financial institution. There was a
significant positive relationship between risk retention with provision to total advances,
non- performing loans to total advances (r = 0.400, 0.400 P < 0.01) respectively.
In general, there was a significant positive relationship between other risk management
techniques and loan performance ie provision to total advances, non- performing loans to
total advances ( r = 0.374, 0.374, P = 0.01).
47
CHAPTER FIVE
5.0
INTERPRETATION, DISCUSSION, CONCLUSION AND
RECOMMENDATION
5.1
Introduction
The chapter presents interpretations, a discussion, and conclusion of results presented in
chapter four, followed by recommendations arising out of the findings of the study. The
first part discusses the relationship between loan appraisal (avoidance) and loan
performance which was objective one of the study. The second part discusses the
relationship between other risk management techniques and loan performance. The
chapter ends with recommendations and conclusions.
5.2
Interpretation and Discussion of Results.
This section is divided into two parts. The first part deals with interpretation and
discussion of findings in relation to the two objectives given in chapter one and the
second part discusses other finding obtained from the study.
5.2.1
Examining the Relationship between Loan Appraisal and Loan
Performance.
The Pearson correlation test on the relationship between loan appraisal and loan
performance revealed that there was a significant positive relationship between loan
appraisal with Provision / Total advances ratio (r = 0.575, P- value < 0.01), and ratio of
non performing loan to total advances. This implies that as the process of loan appraisal
is improved and done properly, the loan performance also improves. Proper loan
appraisal will help identify and analyze loss exposures, use a combination of techniques
48
to handle each exposure to ensure loan performance of any given portfolio. These
findings are in agreement with literature by Rupp, (2002) whose work asserts that the
appraisal technique process helps to identify and analyze loss exposures, and this leads to
select control techniques to handle these exposures. Rupp’s supports the above findings
by stating that the control systems enhances management of outstanding risk assets, and
enhances normal repayment which helps to monitor business risk. It is also in line with
the work of Santomero, (1996), Barents PLC (1998), Bannet (1984) and Harrison (1996)
who argue that the appraisal process helps to predict the credit worthiness of would be
borrowers. Loan appraisal process looks at the 5Cs of credit as discussed by Pandey,
(1997), Van Horne, (1998), Sinkey, (1998) and Allyn & Bacon (1996) will lead to
formation of good loan portfolio.
5.2.2 Examining the Relationship between Financial Viability, Financial Analysis
and Loan Performance
The correlation test between financial viability, financial analysis and loan performance
revealed a significant positive relationship between financial viability, financial analysis
and the ratio of provision to total advances, and ratio of non performing loans to total
advances (r = 0.275, 0.275, P – value > 0.005) respectively. This implies that whenever
the project’s financial viability improves, then loan performance will also improve.
Similarly whenever the financial analysis of a given project is done properly, then this
will lead to an improvement in the loan performance that is to say; an improvement in the
ratios of non – performing loans to total advances and the ratio of provisions to total
advances. The finding is supported by the work of Griffith, (1985) whose work reveal
that use of such ratios help in judging the attractiveness or creditworthiness of a company
49
and can enhance loan performance. Griffiths work points out that such ratio analysis will
tell more about the profitability, capital and liquidity position of a given enterprises and
these are important elements for an improvement in loan performance. It is also in line
with the (ADB, 2003) -Asian Development Bank operations bank manual policy report
where it is argued that as an integral part of project preparation, ADB requires the use of
financial analysis and an assessment of the financial policies and the capacity of the
financial management systems practiced or proposed by the borrower or executing
agency to support project implementation and operation. When executing agencies
maintain a financial management system that ensures accountability, efficiency, and
solvency, loan performance will also be improved.
5.2.3 Examining the Relationship between Technical Feasibility and Loan
Performance.
There was a significant positive relationship between provision to total advances, and non
– performing loans to total advances ratio (r = 0.398, 0.398 P < 0.001) respectively. This
implies that when there is technical change in form of new technology adoption which
leads to productivity, the loan performance will also improve. This is in line with the
work of Fria, (2002) who discusses that technologies produce impact on the production
process, and being first to adopt a new and more efficient technique means being able to
enjoy productivity gains before rivals and this has an implication on the efficiency in loan
servicing.
50
5.2.4 Examining the Relationship between Credit Rating and Loan Performance.
There was a significant positive relationship between credit rating and ratio of provisions
to total advances, Non performing loan to total advances ratio (r = 0.352, 0.352, P =
value < 0.05) respectively. This implies that when the credit rating is improved, then loan
performance also improves. It should be noted that credit rating summarizes risk of loss
Treacy & Carey, (2000) and when loss is controlled, loan performance will also improve.
It is supported by the work of Fernando et al (2004), who argued that ratings measure and
reveal the long-term fundamental credit strength of companies, that is to say their longterm ability and willingness to meet debt servicing obligations.
5.3
Examining the Relationship between other Risk Management Techniques
and Loan Performance.
This discussion is focused on objective two of the research which is to examine the
relationship between other risk management techniques and loan performance.
5.3.1 Examining the Relationship between Risk Transfer and Loan Performance
There was a significant relationship between risk transfer with provisions to total
advances, (r = 0.262, P> 0.05). This implies that when the process of risk transfer is
improved through hedging, use of insurance firms to insure loans, and use of derivatives
methods David Rule, (2001, the loan performance will also improve. This finding is also
supported by Parsley 1996, McDermott 1977 and the Economist 2001, who argue that
credit-derivative helps to hedge credit exposures and will realign the portfolios. It
provides insurance against default that the value of the underlying asset.
51
5.3.2 Examining the Relationship between Risk Diversification and Loan
Performance.
There was significant positive relationship between risk diversification with the ratio of
provisions to total advances, and non – performing loans to total advances (r = 0.348,
0.348 P < 0.05) respectively. The above result implies that when diversification of loan
portfolio is improved then loan performance will also improve. Note that diversification
of loan portfolio mean investing the loan portfolio in different sectors of the economy,
or different region and this will control risk and lead to loan performance which is in line
with the work of Brannan, (2000), who argued that diversification is the primary tool for
lenders to control borrower risk and realize loan performance. This was also supported
by Wilson, (1998), who advocates for diversification of loan portfolio across nations
where the benefits are much stronger than they are when diversification occurs across
sectors in a given economy.
5.3.3 Examining the Relationship between Risk Retention and Loan Performance
There was a significant positive relationship between risk retention with provision to total
advances, non- performing loans to total advances (r = 0.400, 0.400 P < 0.01)
respectively. This implies that whenever there is an improvement in the risk retention,
then loan performance will also improve. This finding is in line with Sanderson, (1991)
who argue that knowing the right amount of risk to retain promotes financial efficiency
and improves loan performance.
52
5.4
Conclusions
The study focused on examining the relationship between loan appraisal, credit
rating, technical feasibility, financial viability, risk transfer, risk diversification, risk
retention to loan performance. The above elements form a credit risk management.
Findings revealed the following:

That loan appraisal was significant and positively related to loan performance.
This brings forth the importance of loan appraisal in ensuring effective
performance of loans.

Credit rating was significantly and positively related to loan performance.
This signifies the importance of establishing an internal credit rating system to
summarize risk of losses inherent in loans

The relationship between technical feasibility and loan performance was
positive. However, the magnitude of relationship was not strong which meant
that technical change or technological change is an important factor that
contributes to increased productivity but has a slight contribution to loan
performance.

Financial viability was positively and significant related to loan performance.
This signifies the importance of lending to entities with strong financial base.

The relationship between risk transfer was significant and positive and this
signifies the need for banks to use insurance firms to take on risk in form of
insurance covers for loans.

Risk diversification was significantly and positively related to loan
performance. The need for diversifying loan portfolio to different sectors,
region is necessary
53

The relationship between risk retention and loan performance was significant
and positive and this signifies the need to limit amount of risk that bank take
on their loan portfolio.
Therefore, the study holds that credit risk management in the two banks has a significant
and positive relationship to loan performance.
5.5. Recommendations
Based on the findings of this study, the following recommendations are suggested
(i) Considering that there is a significant positive relationship between loan appraisal and
loan performance, it is important for the bank to formulate an appraisal process/
procedures, format that details ways of capturing all the credit risk. The appraisal process
should identify and analyze all loss exposures, and measure such loss exposures. This
should guide in selection of technique or combination of techniques to handle each
exposure. The appraisal process should capture key issues like the capital adequacy,
capacity of the applicant, value of the collateral, and repayment history.
(ii) From the findings, financial viability had a significant positive relationship with loan
performance. In development financing, it is important for all the executing agencies to
lend to entities with sound and stable financial positions. Such entities should be
maintaining sound financial management systems that ensure accountability, efficiency,
and solvency. It is also important to make a detailed assessment of financial viability
through use of tools like ratio analysis to judge the attractiveness and creditworthiness,
liquidity levels, efficiency, profitability, leverage of a given company before financing.
(iii) The significant and positive relationship between technical feasibility and loan
performance indicate that it is critical for the bank to keep a look at the technology and
54
production process of a given project both in the short and in the long term before
financing. Technical change will always impact on the production process, and can bring
about efficient techniques of production which impacts on efficiency.
(iv) Since credit rating had a significant positive relationship with loan performance, it is
important that while assessing projects, internal credit rating should be part and partial of
the appraisal process. Technical staff should be trained to be able to conceptualize,
design, and male operational an internal credit rating system that suits the banks’
operations to control risk exposures.
(v) Considering that there is a significant positive relationship between risk transfer and
loan performance, banks should increase use of insurance firms in a bid to transfer or
share risk in case of default. It is also important for the bank to start practicing advanced
hedging methods for example use of derivative products like swaps, option, and futures.
Derivatives provide insurance or protection against an event (default) that changes the
value of the underlying asset (loan).
(vi) From the findings, risk diversification has a positive relation with loan performance.
Diversification of loan portfolio should be part and partial of banks policy in a bid to
Spread risk. Loan portfolio should be invested in different sectors, regions.
Diversification should also be done across nations where the benefits are much stronger
than when diversification occurs across sectors.
(vii) The significant positive relationship between risk retention and loan performance
indicate that risk retention analysis should be never an ending process as banks
constantly decide how much risk to retain. Hence use of credit rating models should
55
continuously be applied. This helps to ascertain how much interest rate to charge for a
given loan as it summarize and quantify risk in a given loan portfolio.
5.6
Areas for Further Research
The study was only focused on development banks in Uganda. However, it could be
expanded to cover other commercial bank in Uganda. The study also majored on
establishing the relationship between credit risk management and loan performance. This
should also be widened to establish the relationship between risk management and
performance of commercial bank.
56
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64
APPENDIX 1
MAKERRE UNIVERSITY BUSINESS SCHOOL
We are carrying out a research on topic: Credit Risk Management and Loan Performance
in Development Financing. The case of Uganda Development Bank and Development
Finance Company of Uganda (DFCU Ltd).
Members of staff of this institution have been selected as a unit of analysis. Please kindly
respond to the questionnaire by filing in as appropriate. The information given through
this questionnaire is purely for academic purposes, but the recommendations there from
may be beneficial to your organization. Your response will be treated with utmost
confidentiality.
GENERAL INFORMATION
(Tick the appropriate box)
1
Name of Institution……………………
2
Gender
a) Male
3
Age
a) 20-30 years
4 Education
a) Diploma
Female
b) 31 -40 years
b) Degree
c) 41 50 years
c) Masters
d) above 50 years
d) Phd and above
5. Current rank. ……………………..
6) Have you ever worked in a credit department before?
a) Yes
b) No.
7. Working experience in banks
a) Less than 2 years
B) 2 – 5 years
c) 6-10 years
65
d above 10 years
10
11
12
13
15
14
15
16
17
Strongly
disagree
Disagree
Uncertain
1
SECTION I. APPRAISAL
We demand for a business plan from all clients/ borrowers
We analyze the business plan to identify risk exposure
We consider professionalism in the respective business
We look at relevant experience of the loan applicants
We consider cash flow projections of a given project before we finance it
We consider capacity of the loan applicants
We look at the long term planning horizon of every loan applicant
We look at the conditions ie economic, political before we finance a
project
We look at collateral as secondary source of repayment
We consider accounts receivables and inventory as security
We look at capitalization of the business
We consider the net worth of the business
We consider the past track record of repayment
We look at the character of loan applicants
We look at the credit trustworthiness of loan applicants
We consider the leadership quality or capacity of managers.
We periodically monitor projects financed
1
2
3
4
5
6
7
8
9
10
SECTION II. FINANCIAL VIABILITY AND ANALYSIS.
We request for past financial reports from all clients
We look the quality of financial report presented
We demand for audited financial reports
We analyze financial reports
We calculate ratio analysis for profitability, efficiency, leverage
We analyze growth in sales of our clients/ borrowers
Interest coverage ratio is important before we finance
We look for sound financial management policies of our borrowers
We only finance projects with sound financial management policies
Financial analysis determines credit strength of a client
66
Disagree
Uncertain
Agree
Strongly
agree
SECTION II: FINANCIAL VIABILITY AND ANALYSIS
Please respond to the following statements by indicating the extent to which you agree or disagree as per
the given choices
5
4
3
2
1
Strongly
disagree
1
2
3
4
5
7
8
9
Agree
Strongly
agree
SECTION I:
APPRAISAL
Please respond to the following statements by indicating the extent to which you agree or disagree as per
the given choices.
5
4
3
2
SECTION III: TECHNICAL FEASIBILITY
Please respond to the following statements by indicating the extent to which you agree or disagree as per
the given choices
Disagree
Strongly
disagree
3
2
1
Strongly
disagree
Agree
4
Disagree
1
Uncertain
2
Agree
Uncertain
3
5
Strongly
agree
1
2
3
4
5
6
7
8
9
4
Strongly
agree
5
SECTION III. TECHNICAL FEASIBILITY
We finance projects with potential market/ trade
We look at consumption behaviors of the market
We look at the marketing strategy of loan applicants
We finance projects that use appropriate technology
We have qualified staff to assess the level of technology.
We look at access to infrastructure
We consider availability of raw material before we finance a project
We look at the implementation plan of all projects
We consider if the project has specialized manpower
SECTION IV: CREDIT RATING
Please respond to the following statements by indicating the extent to which you agree or disagree as per
the given choices
1
2
3
4
5
6
7
8
9
10
11
SECTION IV. CREDIT RATING
The bank has an internal credit rating system.
We do credit rating on all projects
I participate in the design of the credit rating system
The bank quantifies risk through credit rating
We base our rating on financial reports
We rate the management capacity of loan applicants
Our rating system predicts debt serving capacity of loan applicants
The rating used can determine deteriorating / non performing loans
We use public and private information in rating
I know how to use rating system
The bank monitors all problem loans
67
Strongly
disagree
Disagree
Uncertain
Agree
Strongly
agree
SECTION VII: RISK RETENTION
Retention is only used to cover a small proportion of loss
Loss that is covered by retention is about 5% of loan portfolio
We prefer covering loss from bank resources
We have widely used risk retention to know how much that exist in our loan
portfolio
We constantly carry our risk retention reviews
68
Disagree
Uncertain
Agree
Strongly
agree
5
1
SECTION VI. RISK DIVERSIFICATION
The loan portfolio is invested in different sectors of the economy
We do not concentrate our loan portfolio in particular sectors of the economy
Decision to diversify is taken only by management
Diversification has reduced risk exposure in this institution
We invest in different loan products
Default level have reduced due to diversification
SECTION VII: RISK RETENTION
Please respond to the following statements by indicating the extent to which you agree or disagree as per
the given choices
5
4
3
2
1
2
3
4
Strongly
disagree
Disagree
Uncertain
SECTION V. RISK TRANSFER
Our loan portfolio is fully insured
Clients are requested to provide financial guarantees
Our loans are guaranteed with fixed deposits
We also consider debentures as loans guarantee
We participate in loan portfolio hedging against risk
The bank uses credit derivatives to hedge risk
The bank has used interest rate swaps in the market
The bank uses forward exchange rate contract to hedge risk
Risk transfer improves loan recovery
SECTION VI: RISK DIVERSIFICATION
Please respond to the following statements by indicating the extent to which you agree or disagree as per
the given choices
5
4
3
2
1
2
3
4
5
6
1
1
Strongly
disagree
1
2
4
5
6
7
8
9
10
Agree
Strongly
agree
SECTION V: RISK TRANSFER
Please respond to the following statements by indicating the extent to which you agree or disagree as per
the given choices
5
4
3
2
1
2
3
4
5
6
7
SECTION VIII:
CREDIT RISK MANAGEMENT
The bank has a risk management policy
The bank has pre-set concentration limits in every sector
The bank has pre set portfolio limits
All staff members are evaluated
The bank quickly responds to market changes
We use risk based pricing in our loan portfolio
We periodically assess credit quality of our loan portfolio
Thanks for your time and cooperation
69
1
Strongly
disagree
Disagree
Uncertain
Agree
Strongly
agree
SECTION VIII:
CREDIT RISK MANAGEMENT
Please respond to the following statements by indicating the extent to which you agree or disagree as per
the given choices.
5
4
3
2