the relationship between credit risk management …
TRANSCRIPT
THE RELATIONSHIP BETWEEN CREDIT RISK MANAGEMENT
PRACTICES AND NON-PERFORMING LOANS IN KENYAN
COMMERCIAL BANKS: A CASE STUDY OF KCB GROUP
LIMITED
BY
FREDRICK O. NYASAKA
UNITED STATES INTERNATIONAL UNIVERSITY - AFRICA
SPRING, 2017
THE RELATIONSHIP BETWEEN CREDIT RISK MANAGEMENT
PRACTICES AND NON-PERFORMING LOANS IN KENYAN
COMMERCIAL BANKS: A CASE STUDY OF KCB GROUP
LIMITED
BY
FREDRICK O. NYASAKA
A Project Report Submitted to the Chandaria School of Business in
Partial Fulfilment of the Requirements for the Degree of Masters in
Business Administration (MBA)
UNITED STATES INTERNATIONAL UNIVERSITY-AFRICA
SPRING, 2017
ii
STUDENT’S DECLARATION
I, the undersigned, declare this my original work and has not been submitted to any other
college, institution or university other than United States University in Nairobi for
academic credit.
Signed __________________________ Date: _________________________
Fredrick Nyasaka (642001)
This project report has been presented for examination with my approval as the appointed
supervisor.
Signed __________________________ Date: _________________________
Mr. Kepha Oyaro
Signed:__________________________ Date: _____________________________
Dean Chandaria School of Business
iii
COPYRIGHT
© 2017 Fredrick Nyasaka
ALL RIGHTS RESERVED. Any unauthorized reprint or use of this research report is
prohibited. No part of study may be reproduced or transmitted in any form or by any
means, electronic or mechanical, including photocopying, recording, or by any
information storage and retrieval system without express written permission from the
author and the university.
iv
ABSTRACT
The objective of the study was to investigate the relationship between credit risk
management practices and related factors and non-performing loans at KCB Group. The
study aimed at examining how Credit Risk Management practices prevalence of non-
performing loans at KCB Group, investigating the effects of Non-Performing Loans on
Financial Performance of KCB Group and to identifying credit risk management
mechanisms to reduce the level of non-performing loans at KCB Group.
The study adopted a descriptive research method in order to obtain the data that is
necessary, which facilitated the collection of the primary data as a way of getting into the
research objectives. The descriptive research design helped in observing the relationship
between Credit Risk Management practices and the prevalence of non-performing loans,
Non-Performing Loans and Financial Performance, and credit risk management
mechanisms and non-performing loans. The study utilized the questionnaires to obtain
relevant information from respondents focusing on 100 credit managers in KCB head
office and branches in Kenya. Non-Probability sampling technique was used embracing
judgmental sampling technique which endeavors to get an example of components in
light of the judgment of the researcher. Data Analysis was conducted utilizing Statistical
Package for the Social Sciences (SPSS) on the information gathered to produce inferential
statistics. Presentation of results was done in tables and figures and recommendations and
conclusion presented.
Data analysis was done using Statistical Package for the Social Sciences (SPSS) on the
data collected in order to generate descriptive statistics and inferential statistics.
Presentation of results was done in form of tables and figures and a recommendation and
conclusion given.
The study examined how Credit Risk Management practices affect the prevalence of non-
performing loans at KCB Group. The study found that the bank considers characteristics
of the borrower, capacity, conditions and Collateral/Security in credit scoring for business
and corporate loans. The bank has a credit manual that documents and elaborates the
strategies for managing credit. To reduce on non-performing loans, the study found that
the bank has a well-documented Credit Risk Management policy. These policies help the
bank to contacts the credit bureau to assist in decision making to lend their customers.
v
The study also reveals that the bank has strategies for granting credits focus on whom,
how and what should be done at the branches and corporate division levels while
assessing borrowers.
The study established that non-performing loans negatively affects a bank’s lending
capacity due to diminished core capital. The study found that non-performing loans have
a negative effect on the bank’s profits through increased provisions. From the study, it
was revealed that high levels of non-performing loans deny banks easy access to capital
markets; both debt and equity. High levels of non-performing loans can lead to
undercapitalization of the bank resulting to job losses. The study also found that high
prevalence of non- performing loans creates a negative signalling effect in the stock
market thus lower share prices and market capitalisation. Non-performing loans leads to
shortening of loan repayment periods hence enhances the revision upwards of interest
rates thus denial of credit. The study revealed that non-performing loans negatively
affects the shareholder’s funds and this can loans can result to insolvency thus collapse of
banks.
The study assessed different credit risk management mechanisms that reduce the level of
non-performing loans. The study found that educating clients on borrowing terms and
conditions helps clients make accurate decisions easing reliance on collateral. Strict
system related credit performance monitoring ensures better loan performance. The study
established that frequent restructuring of non-performing loans to good book lowers the
levels of non-performing loans. Internal Appraisal Credit Rating Systems assist in
reducing the levels of NPLs. The study reveals that frequent reviews of sector limits in
line with the economy lending ensure a quality book. Adequate annual budget allocations
for loan monitoring ensure good asset quality. The study also found that collateralised
loans perform better and thus managing loan default.
The study concludes that the commercial banks have strategies for granting credits
focusing on whom, how and what should be done at the branches and corporate division
levels while assessing borrowers. The study also concludes that non-performing loans
negatively affects a bank’s lending capacity due to diminished core capital. From the
study, it is recommended that the management of commercial banks should develop
strategies to reduce level of non-performing loans because high levels of non-performing
vi
loans deny banks easy access to capital markets; both debt and equity. The study also
recommends commercial banks to educate their clients on borrowing terms and
conditions as this helps clients make accurate decisions easing reliance on collateral.
vii
TABLE OF CONTENTS
STUDENT’S DECLARATION ....................................................................................... ii
COPYRIGHT ................................................................................................................... iii
ABSTRACT ...................................................................................................................... iv
TABLE OF CONTENTS ............................................................................................... vii
LIST OF TABLES ........................................................................................................... ix
LIST OF FIGURES ...........................................................................................................x
CHAPTER ONE ................................................................................................................1
1.0 INTRODUCTION...................................................................................................1
1.1 Background of the Problem ......................................................................................1
1.2 Statement of the Problem ..........................................................................................4
1.3 General Objective .....................................................................................................6
1.4 Specific Objectives ...................................................................................................6
1.5 Significance of the Study ..........................................................................................6
1.6 Scope of the Study ....................................................................................................7
1.7 Definition of Terms...................................................................................................7
1.8 Chapter Summary .....................................................................................................8
CHAPTER TWO .............................................................................................................10
2.0 LITERATURE REVIEW ....................................................................................10
2.1 Introduction .............................................................................................................10
2.2 The Process of Credit Risk Management................................................................10
2.3 Effect of Non-Performing Loans on Financial Performance of Banks...................16
2.4 Mechanisms of Reducing Credit Risk-Non Performing Loans ..............................23
2.5 Chapter Summary ...................................................................................................27
CHAPTER THREE .........................................................................................................28
3.0 RESEARCH METHODOLOGY ........................................................................28
3.1 Introduction .............................................................................................................28
3.2 Research Design......................................................................................................28
3.3 Population and Sampling Design ............................................................................29
3.4 Data Collection Method ..........................................................................................30
viii
3.5 Research Procedures ...............................................................................................30
3.6 Data Analysis Method.............................................................................................31
3.7 Chapter Summary ...................................................................................................31
CHAPTER FOUR ............................................................................................................32
4.0 RESULTS AND FINDINGS ................................................................................32
4.1 Introduction .............................................................................................................32
4.2 Response Rate .........................................................................................................32
4.3 Background Information .........................................................................................33
4.4 Credit Risk Management Practices and Prevalence of Non-Performing Loans .....37
4.5 Effects of Non-Performing Loans on Financial Performance ................................42
4.6 Credit Risk Management Mechanisms that Reduce Non-Performing Loans .........46
4.7 Chapter Summary ...................................................................................................49
CHAPTER FIVE .............................................................................................................50
5.0 DISCUSSION, CONCLUSIONS AND RECOMMENDATIONS ...................50
5.1 Introduction .............................................................................................................50
5.2 Summary .................................................................................................................50
5.3 Discussion ...............................................................................................................52
5.4 Conclusions .............................................................................................................58
5.5 Recommendation ....................................................................................................59
REFERENCES .................................................................................................................61
APPENDICES ..................................................................................................................67
Appendix 1: Study Questionnaire ..................................................................................67
ix
LIST OF TABLES
Table 4.1: Current Position ................................................................................................34
Table 4.2: Work Experience ..............................................................................................35
Table 4.3: Determinants of Non-Performing Loans ..........................................................36
Table 4.4: Experience in the Credit Department ...............................................................37
Table 4.5: Credit Risk Management Practices ...................................................................38
Table 4.6: Documented Credit Risk Management Policy .................................................39
Table 4.7: Credit Manual ...................................................................................................40
Table 4.8: Strategies for Granting Credit ...........................................................................41
Table 4.9: Credit Risk Analysis .........................................................................................41
Table 4.10: Non-Performing Loans on Financial Performance .........................................43
Table 4.11: Non-Performing Loans and Profitability ........................................................44
Table 4.12: Access to Capital Market ................................................................................44
Table 4.13: Lending Capacity ............................................................................................44
Table 4.14: Insolvency .......................................................................................................45
Table 4.15: Shareholder’s Funds .......................................................................................46
Table 4.16: Credit Risk Management ................................................................................46
Table 4.17: Reducing Non-Performing Loans ...................................................................47
Table 4.18: Model Summary of Credit Risk Management Mechanisms ...........................48
Table 4.19: Anova of Credit Risk Management Mechanisms ...........................................48
Table 4.20: Coefficient of Variation of Credit Risk Management Mechanisms ...............49
x
LIST OF FIGURES
Figure 4.1: Response Rate .................................................................................................32
Figure 4.2: Gender of Respondents ...................................................................................33
Figure 4.3: Age Group of Respondents .............................................................................34
1
CHAPTER ONE
1.0 INTRODUCTION
1.1 Background of the Problem
Ombaba (2013) argues that a strong financial system is very important for a country to
flourish. The economic progress of a nation and development of banking is invariably
interrelated. The Banking sector is an indispensable financial service sector supporting
development plans through channeling funds for productive purpose, intermediating flow
of funds from surplus to deficit units and supporting financial and economic policies of
government. Therefore, the importance of bank’s stability in a developing economy is
noteworthy as any distress affects the development plans of a country which leads to
economic progress.
According to Kipyego and Wandera (2013), commercial banks play a vital role in the
economy in the intermediation process by mobilizing deposits from surplus units to
deficit units. The surplus is channeled to deficit units through lending and this lending is
one of the main activities of commercial banks and any other financial institutions. Due to
these lending activities, credit risk management has been an integral part of the loan
process in banking business (Ogboi & Unuafe, 2013). Marshal and Onyekachi (2014)
argue that this kind of business activity therefore inevitably exposes banks to huge credit
risk which might lead them to financial distress including bankruptcy if not well
managed.
Any country’s banking industry stability is a pre-requisite for economic development and
resilience against financial crisis. This stability is assessed based on profit and quality of
asset it possesses. Even though banks serve social objectives through priority sector
lending, mass branch networks and employment generation, maintaining good asset
quality and profitability is critical for a banks survival and growth. A major threat of the
banking sector’s success is undoubtedly the prevalence of Non-Performing Loans
(NPLs).This affects operational efficiency which in turn affects the profitability, liquidity
and solvency position of banks. NPLs also affect the psychology of bankers in respect of
their disposition of funds towards credit delivery and credit expansion. These loans also
generate a vicious effect on banking survival and growth, and if not managed properly
leads to banking failures (Ombaba, 2013).
2
In response to this, commercial banks have almost universally embarked upon an
upgrading of their risk management and control systems. Due to the nature of their
business, commercial banks expose themselves to the risks of default from borrowers.
Prudent credit risk assessment and creation of adequate provisions for bad and doubtful
debts can cushion banks against crystallization of credit risks (Aduda & Gitonga, 2011).
According to Shubhasis (2005), risk management is important to bank management
because banks are “risk machines” they take risks; they transform them and embed them
in banking products and services. Risks are uncertainties resulting in adverse variations of
profitability or in losses.
Banking crises have a long history. Hardy (1998) argues that, the Great Depression of the
1930s was exacerbated by bank failures in the United States and elsewhere. In recent
decades, a large number of countries have experienced financial distress of varying
degrees of severity, and some have suffered repeated bouts of distress. Boyd and Gertler
(1994) explained that in the US during the great depression, the banking industry faced
competition from open markets sources of credit and nonbank intermediation. There was
a shrinking in their profits and a likelihood of failure where their failure rate jumped from
an average of 2 per year in the 1970s to roughly 130 per year in the period between 1982
to 1991.Due to this high failure rate, there was a rise in the number of banks in financial
distress. By the end of 1992, the Federal Deposit Insurance Corporation (FDIC) listed 863
banks with combined assets of $464 billion as problem institutions (FDIC 1993). Gaithi
(2010), In the early 1980s, the governments of several Latin American countries,
including Chile and Mexico, felt compelled to make up for losses in the banking system
by buying substandard loans from the banks for more than their true worth-to preserve its
solvency. Likewise, many African countries also had to restructure and recapitalize their
banking systems as well.
In 2013, there were high interest rates and economic shocks linked to the March 4
General Election which rendered thousands of borrowers unable to service bank debts,
pushing the volume of bad loans in Kenya to a five-year high. Data from Central Bank of
Kenya (CBK) showed that non-performing loans held by commercial banks rose to Sh70
billion in March as borrowers felt the impact of reduced government and private sector
spending in the run-up to the elections. This was 14.1 per cent higher than the Sh61.6
billion bad loans that the lenders held in December 2012. However, in that year, most
3
banks did not reduce their lending rates despite the clear signals from the CBK which
ultimately slowed down new lending but the wider net interest margins helped them grow
their profits,” said Vimal Parmar, the head of research at Burbidge Capital. As a result,
Kenya’s top two banks, KCB and Equity announced double digit growth in the volume of
NPLs during the first quarter of the year. This led to KCB announcing the reduction of
the NPL ratio and recoveries of non-performing loans as key drivers of its future
performance (Ngigi, 2013).
In 2014, the Central Bank of Kenya forced banks to set aside additional cash as provision
for defaults on multiple facilities. It required lenders to classify all loan accounts of a
borrower who defaults repayment of any one of their multiple loans for more than three
months. Such adverse classification led to an increase in prudential provisions. Change of
laws particularly relating to the recovery process, high interest rates in 2012 and
introduction of CBK prudential guidelines regarding multiple mortgage facilities,” as
stated by Housing Finance Group CEO Frank Ireri, led to banks year 2013 bad loans to
jump 30.9 per cent to Sh80.6 billion, the highest in over six years, even outpacing growth
in new credit advanced by the lenders (Ngigi, 2014).
The main aim of every banking institution is to operate profitably in order to maintain its
stability and improve in growth and expansion. In the last twenty years, the banking
sector has faced various challenges that include non-performing loans (NPL), political
interference and fluctuations of interest rate among others, which have threatened the
banks stability (Aduda and Gitonga, 2011). According to the Central Bank of Kenya
Annual Bank Supervision Report, the level of non-performing loans has been increasing
steadily from Sh56 billion in 1997, to Sh.97 billion in 1999. This high level of non-
performing loans continues to be an issue of major supervisory concern in Kenya. The
recent financial crises in USA and Europe suggest that NPL amount is an indicator of
increasing threat of insolvency and failure. However, financial markets with high NPLs
have to diversify their risk and create portfolios with NPLs along with performing loans,
which are widely traded in the financial markets. In this regard, Germany was one of the
leaders of NPL markets in 2006 because of its sheer size and highly competitive market
(Misati, Njoroge, Kamau & Ouma, 2010).
4
According to Misati et al., (2010), as pressure mounts on the banking industry’s
profitability resulting from over reliance on interest income by banks, it is strategically
imperative that banks focus on other revenue streams. National Industrial Credit Bank
(NIC) has introduced new products to diversify revenue by expanding the scope of its
activities in addition to its predominant asset finance focus and offering more general
commercial banking facilities and other products. Mwaniki and Gachiri (2014) indicates
that a subsidiary of KCB Group Limited-KCB Capital was granted an Investment
Banking license, marking the lender’s return to the bourse after a three-decade absence
after they sold their investment banking arm to Dyer & Blair in 1983.This new unit is
expected to increase the bank’s non funded revenue streams through fees earned from
advisory and brokerage services.
As a result of the banking failures in Kenya and to find a way forward to prevent further
failures, the Credit Information Sharing mechanism was launched in Kenya following the
legislation and gazette of the Credit Bureau Regulations on 11th July 2007. The Credit
Bureau Regulations were issued following the amendment to the Banking Act passed in
2006 that made it mandatory for the Deposit Protection Fund and institutions licensed
under the Banking Act to share information on non-performing loans through credit
reference bureaus licensed by the Central Bank of Kenya. This was the result of many
years of negotiations and agreement between Kenya Bankers Association, Central Bank
of Kenya, the Ministry of Finance and the office of the Attorney General aimed at finding
way forward to the challenges facing the lending environment in Kenya and especially
the banking sector (Kwambai & Wandera, 2013).
1.2 Statement of the Problem
The banking sector has delivered services to consumers and businesses remotely for
years. Continuing innovation and competition among banking sector players and new
market entrants has allowed for a much wider array of banking products and services for
retail and wholesale banking customers. These include activities such as; accessing
financial information, obtaining loans and opening deposit accounts, as well as relatively
new products and services such as electronic bill payment services, Internet banking,
mobile banking and business-to-business market places and exchanges. Due to these
developments, many problems have arose in the banking sectors a major one being the
5
failure of customers to return a loan borrowed which results in non-performing loans
(Haneef, Riaz, Ramzan, Rana, Ishaq & Karim, 2012).
Haneef et al. (2012) argue that financial institutions are exposed to various risks in pursuit
of their business objectives. These risks even become higher because banks are in a
competitive field. The Kenyan banking industry is quite competitive and has reached an
extent whereby a bank does not easily let go any of their clientelle be they low-cadre
earners,or self employed individuals whose risk of defaulting is high (Gweyi, 2013).The
failure to adequately manage these risks exposes financial institutions to not only
hampering profitability as their earnings are converting in to bad debts but also increasing
interest rate and causing economic slowdown, ultimately rendering them unsuccessful in
achieving their strategic business objectives (Haneef et al., 2012).
It is also important to note that the industry is still growing with new entrants into the
market still finding space in this competitive sector, great effort must be put to ensure
comprehensive and effective strategies are developed that minimize risk and maximize
loan performance at any particular point while in operation. Appropriate set of tools
should be determined and sustained in time to avoid the likelihood of loss and avoid
banks being subjected to penalties of illiquidity and downsized profitability (Gweyi,
2013). In the worst case, inadequate risk management may result in circumstances so
catastrophic in nature that financial institutions cannot remain in business (Haneef et al.
2012).
Mwangi (2012) argues that Commercial banks carry out credit risk management as a
measure of administering credit to borrowers. This is done by having a well-developed
credit mechanism and procedure. This includes; credit appraisal, training of staff and
setting credit standards and terms to offset the possibility for loss and improve on
financial performance. Commercial banks develop strategies to either eliminate or reduce
this credit risk. In the management of Credit risk, banks are concerned about their
financial performance. However, despite the efforts made to address the poor credit risk
management practices, commercial banks still have difficulties resulting from
implementation of credit risk management processes undertaken and changes in customer
base leading to decreasing financial performance.
6
Wanjira (2010) argues that there is need for commercial banks to prudently adopt non-
performing loans management practices. She explained that this will lead to improved
financial performance of commercial banks in Kenya concluding that there is need for
further research on effective credit management practices to enable the adaptations of
mechanisms to deal with issues of high numbers of non-performing loans in commercial
banks in Kenya.
1.3 General Objective
The general objective of this research was to determine the relationship between the
effectiveness of credit risk management practices and non-performing loans in Kenyan
Banks.
1.4 Specific Objectives
1.4.1 To examine how Credit Risk Management practices at KCB Group affect the
prevalence of non-performing loans.
1.4.2 To investigate the effects of non-performing loans on financial performance of
KCB Group
1.4.3 To identify credit risk management mechanisms to reduce the level of non-
performing loans at KCB Group
1.5 Significance of the Study
1.5.1 Central Bank of Kenya, Regulators and Other Policy Makers
Central Bank of Kenya and other regional regulators are interested in the factors leading
to high prevalence of non-performing loans. This helps them in revision of prudential
guidelines in the ever changing banking industry environment. The Banking Act which is
passed and revised by parliament through lawmakers and policymakers would benefit
from the study in enhancing the act to a stricter and relevant legislation.
1.5.2 KCB Group Limited and other Financial Institutions
KCB Group’s published financials indicate a sharp spike in the level of non-performing
loans. This study will therefore be relevant in assisting the banks identify credit policy
gaps and ways they should specifically be enhanced to ensure quality lending. Since most
of the factors are relevant across the banking industry, other financial institutions will also
7
immensely benefit from the research findings. General research findings will be a useful
contribution for the industry to better understand credit risk management practices and
provide prolific observations for understanding risk management practices in an
organization strive seriously to tackle the problem of loan recovery, tighten their credit
assessment scrutiny policy and arrange appropriate monitoring procedures in order to
keep an eye on NPLs. It is a fact that NPLs are steadily causing lesser profitability of
banking sector (Haneef et al, 2012).
1.5.3 Future Researchers
This research will provide more information on the relationship between credit risk
management and non-performing loans in Kenyan banks. This information will enrich
scholars with knowledge and provide a basis for further studies.
1.6 Scope of the Study
This study was limited to fifty (100) credit risk officials in KCB head office and branches
in Nairobi. Information was gathered using questionnaires. Some of the foreseen
limitations would be as a result of the sensitivity of the line of work that banks do,
information may not be easily be divulged. Secondly, though not in a great extent some
employees in the credit risk management may not be aware of the relationship between
the credit risk management and non-profit loans to respond to questionnaires. Interviews
were not favored as a data collection in this research. This was due to unavailability of
respondents, difficulty in synchronizing interview times due to their busy work schedules
at the bank.
1.7 Definition of Terms
1.7.1 Credit
Credit is derived from a Latin word “credere” meaning trust. When a seller transfers his
wealth to a buyer who has agreed to pay later, there is a clear implication of trust that
payment will be made at agreed date ( Aduda and Gitonga, 2011).
8
1.7.2 Risk
Holton (2004) explains that risk is exposure to a proposition of which one is uncertain.It
is a threat of damage or loss or any other negative occurrence that is caused by external or
internal vulnerabilities that may be avoided through preemptive action.
1.7.3 Credit Risk
Credit risk is the current and prospective risk to earnings or capital arising from an
obligor’s failure to meet the terms of any contract with the bank or otherwise to perform
as agreed (Kargi, 2011).
1.7.4 Credit Risk Management
This is defined as identification, measurement, monitoring and control of risk arising
from the possibility of default in loan repayments (Coyle, 2000).
1.7.5 Non-Performing Loans (NPL)
This is a credit facility of which the interest and or principal amount has remained past
due for a specific period of time. They can also be defined as loans that the principal or
interest has remained unpaid for at least ninety days (Ombaba, 2013).This represent
possible loss of funds due to loan defaults.
1.8 Chapter Summary
This chapter has given a brief background of the Research topic. General information and
relationship between credit risk management and NPL has been discussed linking this to
the problem statement. The general objective and the specific objectives guiding the study
are also given. The chapter concludes highlighting the relevance of the study and the
definitions of terms that have been used in this chapter.
The next chapter aims to review literature that discusses credit risk management and non-
performing loans in detail showing the correlation between the two. The chapter sets out
to highlight the upcoming issues of non-performing loans in credit risk management in
Kenyan banks with a focus of KCB Group. This gave way to chapter three that discussed
the research methodology that discussed the use of questionnaires as a data collection
9
method used for this study. Chapter four discussed the results and findings of this
research and Chapter five discussed, gave recommendations and conclusion of the whole
study.
10
CHAPTER TWO
2.0 LITERATURE REVIEW
2.1 Introduction
This chapter looks at studies done by various researches on the relationship between
credit risk management and non-performing loans while focusing on the objectives of this
research as mentioned in chapter one. This includes; examining the process of credit risk
management; investigating the effect of non-performing loans on financial performance
of banks and lastly to identify credit risk management mechanisms to reduce the level of
non-performing loans. A chapter summary is then given at the end of this section.
2.2 The Process of Credit Risk Management
According to Mwengei (2013) Credit risk management is a process and a comprehensive
system. The process that begins with identifying the lending markets, often referred to as
“target markets” and proceeds through a series of stages to loan repayment. Credit risk
refers to the probability of loss due to a borrower’s failure to make payments on any type
of debt. Credit risk management, meanwhile, is the practice of mitigating those losses by
understanding the adequacy of both a bank’s capital and loan loss reserves at any given
time. Aduda and Gitonga (2011) explain that banks as financial institutions extend credit
to their customers in form of loans, overdrafts, off balance sheet activities (i.e., letter of
credit (LC) guarantees), and credit card facilities. Banks grant credit to enhance their
revenue streams, maintain a competitive edge, to act as its bargaining power in the
industry, as well as to enhance their relationship with their customers.
However, banking institutions face intense challenges in managing credit risk which
include; Government controls internal and external political interferences and pressures,
production difficulties, financial limitations, market disruptions, delays in production
schedules and frequent instability in the business environment which undermine the
financial condition of borrowers (Mwengei, 2013). More than 80% of all banks balance
sheet relate to credit. All over the world exposure to credit risk has led to many banks
failure. Credit risk exposure particularly to real estate has led to widespread banking
problems in Switzerland, Spain, The United Kingdom, Sweden, Japan and others (Aduda
& Gitonga, 2011). In Kenya, Obiero (2002) found that credit risk is only second to poor
11
management in contributing to bank failures. Credit risk management involves different
levels which include;
2.2.1 Credit Risk Analysis
Credit risk analysis (finance risk analysis, loan default risk analysis) and credit risk
management is important to financial institutions which provide loans to businesses and
individuals. Credit can occur for various reasons: bank mortgages (or home loans), motor
vehicle purchase finances, credit card purchases, instalment purchases, and so on. Credit
loans and finances have risk of being defaulted (Nafula, 2009). To understand risk levels
of credit users, credit providers normally collect vast amount of information on
borrowers. Statistical predictive analytic techniques can be used to analyse or to
determine risk levels involved in credits, finances, and loans, i.e., default risk levels.
Personal credit scores are normally computed from information available in credit reports
collected by external credit bureaus and ratings agencies. Credit scores may indicate
personal financial history and current situation. However, it does not tell you exactly what
constitutes a "good" score from a "bad" score. More specifically, it does not tell you the
level of risk for the lending you may be considering (Mwisho, 2011). Internal credit
scoring methods described in this page address the problem. It is noted that internal credit
scoring techniques can be applied to commercial credits as well.
Credit risk profiling (finance risk profiling) is very important. The Pareto principle
suggests that 80%-90% of the credit defaults may come from 10%-20% of the lending
segments. Profiling the segments can reveal useful information for credit risk
management. Credit providers often collect a vast amount of information on credit users
(Mwirigi, 2009). Information on credit users (or borrowers) often consists of dozens or
even hundreds of variables, involving both categorical and numerical data with noisy
information. Profiling is to identify factors or variables that best summarize the segments.
2.2.2 Credit Scoring
Credit scoring is a credit management technique that analyses the borrower’s risk. In its
early meaning, credit scores` were assigned to each customer to indicate its risk level. A
good credit scoring model has to be highly discriminative, high scores reflect almost no
12
risk and low scores correspond to very high risk or the opposite depending on the sign
condition. The more discriminative the scoring system is, the better are the customers
ranked from high to low risk. In the calibration phase, risk measures are assigned to each
credit pools (Miller, 2007).
The quality of the credit scores risk ranking and calibration can be verified by analysing
ex-post observed credit losses per score. Credit scores are often segmented into
homogeneous pools. In the past, credit scoring focused on measuring the risk that a
customer would not fulfil his/her financial obligations and run into payment arrears which
has evolved recently to exposure and also loss. Scoring techniques are nowadays used
throughout the whole life cycle of credit as a decision support tool or automated decision
algorithm for large customer bases. With increasing competition, electronic sale channels
and recent saving, credit and cooperative regulations have been important catalysts for the
application of semi- automated scoring systems. Since their inception, credit scoring
techniques have been implemented in a variety of different, yet related settings such as
credit approval (Mikiko, 2007).
Initially, the credit approval decision was made utilizing a simply judgmental approach
by just investigating the application structure subtle elements of the candidate and usually
centred on the estimations of the 5 Cs which are character, capital, capacity, collateral and
conditions of a client (McColgan, 2009). Character which measures the borrower’s
personal character and integrity including virtues like reputation and honesty and their
willingness to comply with the credit terms and conditions; Capital which measures the
difference between the borrower’s assets which may include car, house and liabilities for
example renting expenses and whether they exist; Collateral evaluation of the assets
provided in case payment
problems occur for example house hold assets, house, car; Capacity which measures the
borrower’s ability to pay based on for example job status, source of income and finally;
Conditions where the members’ borrowing circumstances are evaluated for example
market conditions, competitive pressure, and seasonal character.
13
2.2.3 Credit-Approval Process
This is a classical credit union technique where lending limit is a multiple of savings. This
technique helps to build savings-led institution and allows institution to learn about the
discipline and economic capacity of a client by observing frequency of deposits. Loans
may not have a direct relationship with repayment capacity (Kaplin, Levy, Qu, Wang,
Wang & Zhang, 2009). If the deposit rate is low, inflation rate is high and currency
devaluations expectations high, savings will be dampened.
Clear established process of approving new credits and extending the existing credits has
been observed to be very important while managing credit risks in banks. Credit unions
must have in place written guidelines on credit approval process, approval authorities of
individuals or committees as well as decision basis. The board of directors should always
monitor loans. Approval authorities will cover new credit approvals, renewals of existing
credits and changes in terms and conditions of previously approved credits particularly
credit restructuring which should be fully documented and recorded (Jappelli & Marco,
2007). Prudent credit practice requires that persons empowered with the credit approval
authority should not have customer relationship responsibility. Approval authorities of
individuals should be commensurate to their positions within management ranks as well
as their expertise (Mwisho, 2011).
Depending on the nature and size of credit, it would be prudent to require approval of two
officers on a credit application in accordance with the Board’s policy. The approval
process should be based on a system of checks and balances. Some approval authorities
will be reserved for the credit committee depending on the size and complexity of the
credit transaction (Jansson, 2012). Depending on the size of the financial institution, it
should develop a corps of credit risk specialists who have high level of expertise and
experience and who have demonstrated judgment in assessing, approving and managing
credit risk. An accountability regime should be established for decision-making process
accompanied by a clear audit trail of decisions taken and proper identification of
individuals/committees involved. All this must be properly documented (Hoque &
Hossain, 2008).
All credit approvals should be at an arm’s length, based on established criteria. Credits to
related parties should be closely analysed and monitored so that no senior individual in
14
the institution is able to override the established credit granting process (Greuning &
Iqbal, 2007). Related party transactions should be reviewed by the board of directors
under due processes of good governance.
Mwisho (2011) indicated that credit unions should have a written loan policy that is
approved by the board of directors of the financial institutions. The board should review
the policy on an annual basis and revise where necessary. The loan policy should include
the policy objective, eligibility requirements for receiving a loan, permissible loan
purposes, acceptable types of collateral, loan portfolio diversification requirements, loan
types, interest rates, terms, frequency of payments, maximum loan sizes per product type,
maximum loan amounts as a percentage of collateral values, member loan concentrations,
restrictions on loans to employees and officials, loan approval requirements, monetary
loan limits, loan documentation requirements and co-signer requirements. Besides the
loan policy, credit unions should also develop lending procedures which are developed by
the operational management team who are responsible to up-to-date and ensure they are
indicative of current lending practices (Gestel & Baesen, 2009).
Loan concentration limits is one of the critical element of the loan policy. The credit
unions should not issue a loan to a member or related parties if such loan would cause
that member or group of related parties to exceed the less of 10% of total assets or 25% of
the credit union’s institutional capital. For purposes of this regulation, related parties are
those dependent on the same source of income such as a family business. Officials or
their families must not directly or indirectly receive any commission, fee or other
compensation in connection with any loan made to a member.
The second critical component in the loan policy is the restriction placed on loans to
employees, officials and their immediate families. Muranga (2011) indicated that the
board of directors should approve all loans to these individuals by a simple majority vote.
However the official or employee requesting the loan should not be present during the
board discussion and vote. It is essential that the rates, terms and conditions on loans
made to or guaranteed by an official, employee or their immediate families are not more
or less preferential than the rates, terms and conditions of loans granted to other members
of similar credit history subject to specific review. The audit committee or its designee
should review the loan portfolio at least semi-annually. The objective of this review is to
15
determine the quality of the loan portfolio, discover any loans which have problems and
provide suggestions for loan recovery in order to minimize losses. The committee should
also ensure compliance with loan policy and procedures and present their findings to the
board of directors.
2.2.4 Credit Reference Bureau
Credit Reference Bureau (CRB) was created by an act of parliament “The Banking Act
CAP 488” under the banking (CRB) regulations, 2008 (COFEK, 2009). FSD (2013)
considers CRB to refer to a company licensed to collect and combine credit information
on individuals from different sources and provide that information upon the request of a
bank. In another definition, Kenya Bankers Association (2013) refers to CRB as
organizations having in their custody credit information about customers that is useful to
lenders. Banks may contact these agencies for information to help them make various
lending decisions. At present the law only allows information from banks to be combined
and only participating institutions can have access to this information as and when they
make requests. Furthermore, banks can only request a report on a borrower who has
actually applied for a loan from them.
World Bank surveys have documented that Public Credit Registries (PCR) exist in about
60 countries worldwide and more nations are planning to create them in the future. In
countries with PCRs, supervised financial institutions are required to provide data on
individual borrowers on a periodic basis, usually monthly. Core PCR data is information
on the identity of borrowers, the size of any loans or credit lines outstanding with
reporting institutions and their status. Status implies whether a loan is in good standing,
past due, in default or other non-accrual status (Majnoni, Miller, Mylenko & Powell,
2014).
The reason for the development of a robust CRB is as a result of loan default and NPL. A
loan is considered non-performing if it remains un-serviced for more than three months.
According to Irungu (2013), NPL increased by 14.1% to Sh70.25billion in March 2013
compared to Sh61.57billion in December 2012. CBK (2013) consider credit risk as the
current or prospective risk to earning and capital arising from an obligor’s failure to meet
any contract with a bank or if an obligor otherwise fails to perform as agreed. The largest
source of credit risk is loans issued to individuals as well as companies.
16
Credit Reference Bureaus (CRB) supplements the focal role acted by banks and other
financial institutions in developing monetary services in an economy. They gather,
oversee and distribute client data to money lenders inside a given regulatory framework.
They help banks in making quicker and more exact credit choices. Moreover, they make
credit accessible to more individuals empowering organizations decrease risk and fraud.
Due to the ease of sharing information from one financial institution to another, it creates
competition which leads to competitive pricing of for instance loans and thus making
them more affordable (CBK, 2010).
The need for CRBs was due to the huge number of non-performing loans as a result of
serial defaulters especially in the 1980s and 1990s who borrowed from one banking
institution to another without a trace and ended up collapsing many banks in Kenya.
There existed a restriction of disclosure of information by banks and hence a legal
framework was sort that would enable sharing of the said information under restricted
conditions. This was done by amending the Banking Act section 31, which catered for
publication of information and its restrictions. Currently we have only two licensed CRBs
in Kenya, namely Credit Reference Bureau Africa Limited and Metropol Credit
Reference Bureau Limited (KBA, 2013).
KBA (2013) acknowledges that it is punitive to have your details registered with the
bureau as the bureau is required to retain this information on NPL until the end of seven
years even after it is fully repaid. The umbrella body advise that just because you may
have a low credit score because you are listed as a defaulter does not mean that you
cannot access credit for seven years. It only means that the lenders will take extra caution
when dealing with you and may charge a higher interest rate or request additional
collateral for the facility you are seeking from the banks. This shows that the CRB
increases the cost of borrowing for people who have been unfortunate to have their names
with the bureau as well as deny the banks the much needed facility therefore lowering the
ability of lenders to make more profits.
2.3 Effect of Non-Performing Loans on Financial Performance of Banks
The financial performance of banks is contributed greatly by the loan interests that banks
make. However, the financial performance of banks is affected if these loans go bad. In
regard to banking regulations, banks make adequate provisions and charges for bad debts
17
which impact negatively on their performance. According to Shu (2002) non performing
loans also have a negative effect on a countries GDP growth, inflation rate and increase in
property prices.
2.3.1 Negative Effects on Banks Profitability
Non Preforming loans have a direct effect on the profitability of banks according to a
study of the financial statement of banks. To improve the economic status of the bank it is
therefore necessary to eradicate the non-performing loans (Altman & Sauders, 2011). The
economic efficiency and growth of the banks can be impaired if non-performing loans
remain existing and are continuously rolled over locking the resources of the banks in
unprofitable sectors (Barr, Seiford & Siems, 2009). The study by Muritala and Taiwo
(2013) investigated the impact of credit risk on the profitability of Nigerian banks. From
the findings it was concluded that banks’ profitability is inversely influenced by the levels
of loans and advances, and non-performing loans thereby exposing them to great risk of
illiquidity and distress.
It is also important to note that there exists a two-way, dual directional relationship
between credit risk management and non-performing loans. Subsequently, credit risk
management (CRM) has an impact on the profitability of banks and especially a bank like
Kenya Commercial Bank. The default rate, cost per loan asset and capital adequacy ratio
influence return on asset (ROA) as a measure of the bank’s (KCB) profitability.Kithinji
(2010) measured the effect of CRM on banks’ profitability through the use of regression
model. The study uses records on the total credit, level of non-performing loans, and
profits for the period of five years. It reveals that the accumulated profits of banks are not
influenced by the quantity of credit and non-performing loans. Hence, Kithinji (2010)
proposed that other variables other than credit and non-performing loans have greater
effects on the profitability of banks.
In a study conducted on 22 Nigerian Banks by Kurawa and Garba (2014), the results
confirmed that the independent variables attributed to CRM indicators had individual and
uniting effect on the profitability (measured by an index of ROA) of the Nigerian banks
under study. Two independent variables, DR ratio and CLA ratio, indicated a clear and
strong positive relationship with the independent variable ROA. These two independent
variables were influenced by loan losses, operating expenses, and the proportion of non-
18
performing loans which were the key determinants of asset quality of a bank. This is
consistent with the findings of Al-Khouri, (2011) who also confirmed that CRM
indicators affect profitability of banks. These findings have contradicted the findings of
Kithinji (2010) who revealed that the banks’ profitability is not influenced by CRM
components.
Banks have been reluctant to provide credit due to NPLs. In high NPL conditions, banks
carry out internal consolidation to improve asset quality (Altman & Sauders, 2011). Due
to this conditions banks have to raise provisions for loan loss that decreases bank’s
revenue reducing funds for lending. The corporate sector is then impaired due to the
cutback on loans making them unable to expand their working capital blocking their
chances of growing and continuing with their normal operation. This then triggers the
second round of business failure if banks are not able to finance firm’s working capital
and investments questioning the quality of bank loans that can lead to banking or
financial failure (Berger & De Young, 2007).
Efforts to deal with non-performing loans have been put in place with banks shortening
the period when loans become past due. This puts loans on borrowers’ schedule sooner
requiring them to start paying immediately ensuring loan losses do not worsen since
lenders are at a risk of being forced to take full write-down if borrowers go bankrupt. This
is done to prevent lenders from being caught off guard (Berger & De Young, 2007).
Muritala and Taiwo (2013) explains that bank management need to be cautious in setting
up a credit policy that will not negatively affect profitability and also to know how credit
policy (and strategy) affects the operations of their banks to ensure judicious utilization of
deposits and maximization of profit. In their study, Muritala and Taiwo further conclude
that improper credit risk management reduces the bank’s profitability, affects the quality
of its assets and increase loan losses and non-performing loans which may eventually lead
to financial distress. Their study advises that Central Banks should regularly assess the
lending attitudes of financial institutions and they could probably do this by assessing the
degree of credit crunch by isolating the impact of supply side of loans from the demand
side taking into account the opinion of the firms’ about banks’ lending attitude.
19
2.3.2 Liquidity Issues
The inability of owners, customers and other stakeholders of a financial institution to
meet cash obligations in a timely and a cost-efficient manner leads to liquidity issues.
This issues occurs when there is a sudden surge liability withdrawals resulting in a bank
to liquidate assets to meet the demand (Bessis, 2008). This emerges when administration
is unable to adequately plan for changes in financing sources and money needs. This
makes bankers and other financial institutions concerned about the risk of not having
enough cash to meet payment in a timely manner (Rose & Hudgins 2011).
Depositors and foreign investors may lose confidence on banks when they are faced with
huge non-performing loans. NPLs reduce total loan portfolio of banks which affects
interest earnings on assets constituting huge costs on banks (Fofak, 2011). Overseeing
liquidity requires keeping up adequate money reserves to meet customer withdrawals,
dispense loans and fund unanticipated money deficiencies while also devoting whatever
number assets as could reasonably be expected to augment profit (Risk Management,
GTZ 2010).
2.3.3 Negative Effect on Capital Mobilization
According to the Central Bank of Kenya, banks are expected to maintain adequate capital
to meet their financial obligations, operate profitably and promote a sound financial
system (CBK 2011). In any business, capital in any business serves as a mean by which
losses may be absorbed (Ogundina 2009). It provides any business with security to
withstand losses not covered by current earnings pattern. Regrettably most banks are
undercapitalized which could be attributed to the fact that many of the banks were
established with little capital in place. This situation has further worsened due to huge
amount of non-performing loans which has taking up the capital base of most of the
banks. Inability to recover the non-performing loans, effect of inflation and low level of
initial capital has also worsened the situation (Ogubunka, 2007). These factors have led to
erosion of the capital base of many banks. Non-Preforming loans can affect the capital
mobilization since investors will not invest in a bank with huge non-performing loans
(Ogundina, 2009).
20
Ogubunka (2007) indicates that when a bank is undercapitalized becomes difficult for it
to continue with their operations due to fewer funds. If it does continue without increased
capital distress ensues and many banks are affected by inadequacy of capital. They are
not able to sustain their operation as a result of overtrading and due to losses arising from
their functions leading to job losses of their employees. According to Direct investment
and domestic capital mobilization are some of the ways banks can raise funds to meet
their capital requirement.
2.3.4 Credit Risk Management
Credit risk management is defined as identification, measurement, monitoring and control
of risk arising from the possibility of default in loan repayments (Coyle, 2010). Pagano
and Jappelli (2013) shows that information sharing reduces adverse selection by
improving bank’s information on credit applicants. In their model, each bank has private
information about local credit applicants, but no information about non-local applicants.
If banks exchange information about their client’s credit worthiness, they can assess also
the quality of non-local credit seekers, and lend to them as safely as they do with local
clients. The impact of information sharing on aggregate lending in this model is
ambiguous. When banks exchange information about borrowers’ types, the increase in
lending to safe borrowers may fail to compensate for an eventual reduction in lending to
risky types. Information sharing can also create incentives for borrowers to perform in
line with banks’ interests.
Klein (2012) shows that information sharing can motivate borrowers to repay loans, when
the legal environment makes it difficult for banks to enforce credit contracts. In this
model borrowers repay their loans because they know that defaulters will be blacklisted,
reducing external finance in future. Vercammen (2008) and Padilla & Pagano (2010)
show that if banks exchange information on defaults, borrowers are motivated to exert
more effort in their projects. In both models, default is a signal of bad quality for outside
banks and carries the penalty of higher interest rates, or no future access to credit. Loan
defaults and nonperforming loans need to be reduced (Central Bank Supervision Annual
Report, 2006; Sandstorm, 2009).
21
2.3.5 Loan Characteristics
Derban (2008) in their study on performing loans recovery in Ghana indicates that failure
to honour financial obligation when it falls due by borrowers can be categorised into three
sections: the intrinsic features of borrowers and their businesses operations. Secondly, the
characteristics of the lending institution and the suitability of the loan product advanced
to the borrower that makes it unlikely for repayment to occur. Systematic risk forms the
third category caused by macroeconomic factors that include economic, political and
business operations (Derban, 2008). In their study Roslan (2007) on poor loan
repayments by small businesses in Malaysia, the study established that monitoring and
early detection of problems that may arise due to the rate of portfolio default can be
arrested through close and informal relationships between MFIs and borrowers. In
addition, cooperation and coordination among various agencies that provide additional
support to borrowers may help them succeed in their business.
Vigenina and Kritikos (2008) on a related study indicate that individual lending has three
elements namely the demand for non-conventional collateral, a screening procedure
which combines new with traditional elements and dynamic incentives in combination
with termination threat in case of default, which ensure high repayment rates up to 100
percent. In a research by Saloner (2007) on poor loans repayment in Africa indicates that
by increasing the loan size for a borrower, it provides an incentive for repayment of his
loans on time and in full so that he continues borrowing. If an individual is able to repay
progressively larger loans, it can be inferred that he is growing his business and
increasing his income.
Quoting Cerven and Ghazanfar, 2009; Godquin 2004, Saloner (2007) acknowledge the
fact that the larger the loan, the more financially beneficial the loan is to the institution.
Increase in loan size is, therefore, useful to both the borrower and the lending institution.
Unfortunately, because the institution is able to be profitable by lending larger sums of
money, this can cause default as borrower grapple with the challenge to meet their
financial obligation. Through support, motivation and leadership from the group, there is
a strong incentive for each member to honour his financial obligation due to fear of losing
on one's personal reputation within the group. In most cases members of a group find
their origin from the same locality or village, this ensures that loan servicing is honoured.
22
In addition Islam (2009) in his research, records that group lending encourages peer
monitoring of which in the long run provides the institutions with the ability to be more
flexible with their credit financing. This ensures that lower rates than other lenders are
charged or similar rates with an assurance of higher rates of repayment with lower risks.
Although most of the research on joint lending finds positive effects, an empirical study
of microfinance institutions and borrowers in Thailand summed that group lending joint
lending does not have a substantial effect, either positive or negative, on the loan
settlement (Kaboski & Townsend, 2008).
2.3.6 Performance of Commercial Banks
A sound and profitable banking sector is able to withstand negative shocks and contribute
to the stability of the financial system (Bennardo, Pagano & Piccolo, 2007). Moreover,
commercial banks play a significant role in the economic growth of countries. Through
their intermediation function banks play a vital role in the efficient allocation of resources
of countries by mobilizing resources for productive activities. They transfer funds from
those who don't have productive use of it to those with productive venture. In addition to
resource allocation good bank performance rewards the shareholders with sufficient
return for their investment. When there is return there shall be an investment which, in
turn, brings about economic growth.
On the other hand, poor banking performance has a negative repercussion on the
economic growth and development. Poor performance can lead to runs, failures and
crises. Banking crisis could entail financial crisis which in turn brings the economic
meltdown as happened in USA in 2007 (Marshall, 2009) That is why governments
regulate the banking sector through their central banks to foster a sound and healthy
banking system which avoid banking crisis and protect the depositors and the economy
(Shekhar & Shekhar, 2007).
A more organized study of bank performance started in the late 1980’s (Olweny &
Shipho, 2011) with the application of Market Power (MP) and Efficiency Structure (ES)
theories (Athanasoglou, 2008.) The MP theory states that increased external market
forces results into profit. Moreover, the hypothesis suggest that only firms with large
market share and well differentiated portfolio (product) can win their competitors and
earn monopolistic profit.
23
On the other hand, the ES theory suggests that enhanced managerial and scale efficiency
leads to higher concentration and then to higher profitability. According to Nzongang and
Atemnkeng in Olweny and Shipho (2011) balanced portfolio theory also added additional
dimension into the study of bank performance. It states that the portfolio composition of
the bank, its profit and the return to the shareholders is the result of the decisions made by
the management and the overall policy decisions.
2.4 Mechanisms of Reducing Credit Risk-Non Performing Loans
2.4.1 Credit Information Sharing
Credit information sharing (CIS) was introduced to the banking sector by the Central
Bank of Kenya (CBK) through an amendment to the banking act in 2003 which allowed
for information sharing among banks (CBK, 2003). The actual launching of CIS
happened in Kenya on 11th July 2007 following the gazetting of the banking Credit
Reference Bureau (CRB) regulations. According to Kenya Credit Information Sharing
Initiative (KCISI), the regulations were issued pursuant to an amendment to the banking
act passed in 2006 that made it mandatory for the deposit protection fund and institutions
licensed under the banking act to share information on non-performing loans (NPL)
(Davel, Gabriel & Serakwane, 2012).
According to FSD Kenya (2012), Central Bank of Kenya since inception licensed CRB
Africa and Metropol East Africa as Credit information service providers. The
organizations compiled credit information, public record data, and identity information
and made it available to lenders in the form of a credit report of individuals and
organizations. When a bank evaluates a request for credit, it can either collect information
on the applicant first-hand or source this information from other lenders who already
dealt with the applicant. Information exchange between lenders can occur voluntarily via
“private credit bureaus” or be enforced by regulation via “public credit registries,” and is
arguably an important determinant of credit market performance (Malhotra, 2011).
The concept of credit information sharing (CIS) is well established globally just like
Kaminsky and Reinhart (1999) observed that CIS can avert the likelihood of the banking
sector going into crises, CIS is pertinent to the banking sector. Credit information refers
to any positive or negative information bearing on an individual’s credit worthiness,
credit standing, credit capacity, character, general reputation, personal characteristics, or
24
mode of living, including but not limited to the history and or profile of an individual or
entity with regard to credit, assets, and any financial obligations.
The need for credit reporting is to assist in reducing information asymmetry, build
information capital, enhance access to affordable credit in line with vision 2030, extend
financial services within the economy, help lenders make faster more accurate decisions
and lastly ease reliance on collateral (FSD, 2012). Behr and Sonnekalb (2012)
acknowledge that credit information sharing specially one that is controlled by registry
such as CRB improves performance.
The advent of CRB was at the backdrop of challenges experienced by banks which
threatened the existence of these banks as increasingly banks were subjected to default
rates which were not manageable leading to banking crises. CBK as a regulator coupled
with stakeholders like Kenya Bankers Association (KBA) and Financial Sector
Deepening (FSD) among others came together and initiated consultative forums to bring
about sanity in the banking sector. This was after witnessing the collapse of major banks
in Kenya (Daima bank, Euro bank, Trust banks among others) which led to loss of
depositor funds (Brownbridge, 2008).
2.4.2 Monitoring and Control
The occurrence of bad debts can be reduced if lenders pay attention to monitoring and
control (Rouse 2009). In monitoring and control Rouse identified internal records, visits
and interviews, audited accounts and management accounts as some of the ways that help
in the monitoring and control process. This can minimize the occurrence of non-
performing loans through ensuring the utilization of the loan for the agreed purpose,
identifying early warning signals of any problem relating to the operations of the
customer’s business that are likely to affect the performance of the facility; ensuring
compliance with the credit terms and conditions and enabling the lender discusses the
prospects and problems of the borrower’s business.
Through the monitoring and control process, a lending decision can be made on sound
credit risk appraisal and assessment of creditworthiness of borrowers. Though past
records of satisfactory performance and integrity serve as useful guide to project trend in
performance they don’t guarantee future performance. A loan granted on the basis of
25
sound analysis might go bad because the borrower may not meet obligations per the terms
and conditions of the loan contract (Norton and Andenas, 2007). Lenders are thus advised
to have proper follow up and monitoring aspects which are essential. This include;
ensuring compliance with terms and conditions, monitoring end use of approved funds,
monitoring performance to check continued viability of operations, detecting deviations
from terms of decision and making periodic assessment of the performance of the loans
(Leply, 2007).
Basically there are three types of loan follow up systems. These are: physical follow up,
financial follow up and legal follow up. The physical follow-up helps to ensure existence
and operation of the business, status of collateral properties, correctness of declared
financial data, quality of goods, conformity of financial data with other records,
availability of raw materials, labor situation, marketing difficulties observed, undue
turnover of key operating personnel and change in management set up among others
(McManus, 2010). The financial follow up is required to verify whether the assumptions
on which lending decisions was taken continues to hold good both in regard to borrowers’
operation and environment and whether the end use is according to the purpose for which
the loan was given (Leply, 2007).
The purpose of legal follow up is to ensure that the legal recourse available to the Bank is
kept alive at all times. It consists of obtaining proper documentation through registration
and follow up of insurances to keep them alive (Rose, 2010). Specific issues pertaining to
legal follow up include: ascertaining whether contracts are properly executed by
appropriate persons and documents are complete in all aspects, obtaining revival letters in
time (this are letters to renew registration of security contracts that have passed the
statutory period as laid down by the law), ensuring loan/mortgage contracts are updated
timely and examining the regulatory directives, laws, third party claims among others
(Koch & MacDonald, 2007).
2.4.3 Credit Appraisal
This includes loan request procedures and requirements contained in the credit policy
documents of banks to guide loan officers in the processing of loans for customers. This
is one of the crucial stages in the loan processing procedures because this stage analyses
information about the financial strength and creditworthiness of the customer. Some of
26
the factors considered in granting loans include; applicant’s background, the purpose of
the request, the amount of credit required, the amount and source of borrower’s
contribution, repayment terms of the borrower, security proposed by the borrower,
location of the business or project and technical and financial soundness of the credit
proposal (ADB Desk Diary, 2008). This is what Chen (2009) explained as five techniques
of credit vetting known as the five Cs framework used in assessing a customer’s
application for credit which include; character that assesses the willingness of the
customer to pay the loan by looking at the past credit history, credit rating of the firm, and
reputation of customers and suppliers. The borrower’s honesty, integrity and
trustworthiness are assessed (Rose, 2010). The second C represents Capacity which refers
to the business’s ability to generate sufficient cash to repay the debt. An analysis of the
applicant’s businesses plan, management accounts and cash flow forecasts that gives a
good indication of the capacity to repay (Sinkey, 2008).
The third C represents Capital which refers to the owner’s level of investment in the
business (Sinkey, 2008). Banks prefer owners to take a proportionate share of the risk.
Although there are no hard and fast rules, a debt/equity ratio of 50:50 would be sufficient
to mitigate the bank’s risk where funding (unsecured) is based on the business’s cash flow
to service the funding (Harris, 2007). Lenders prefer significant equity (own
contribution), as it demonstrates an owner’s commitment and confidence in the business
venture.
The fourth C represent Conditions which are external circumstances that could affect the
borrower’s ability to repay the amount financed. Lenders consider the overall economic
and industry trends, regulatory, legal and liability issues before a decision is made
(Sinkey, 2008). Once finance is approved, it is normally subject to terms and covenants
and conditions, which are specifically related to the compliance of the approved facility
(Leply, 2007). Banks normally include covenants along with conditions when credit
facilities are granted to protect the bank’s interest. The primary role of covenants is to
serve as an early warning system (Nathenson, 2009). Covenants can either be negative or
positive (Sinkey, 2008).
Fifth but not least is collateral which is also known as security. These are the assets that
the borrower pledges to the bank to mitigate the bank’s risk in event of default (Sinkey,
27
2008). It is something valuable which is pledged to the bank by the borrower to support
the borrower’s intention to repay the money advanced. Security is taken to mitigate the
bank’s risk in the event of default and is considered a secondary source of repayment
(Koch and MacDonald, 2007). Supporting of the aforementioned, Rose and Hudgins
(2011) define secured lending in banks as the business where the secured loans have a
pledge of some of the borrower’s property (such as home or vehicles) behind them as
collateral that may have to be sold if the borrower defaults and has no other way to repay
the lender.
2.4.4 Write Offs
When loans are not recovered from borrowers, banks clean up their balance sheets which
is the normal practice of banks all over the world. Write-offs are in recognition of reality
that the original asset has diminished in value and that it needs to be carried on the
balance sheet at its realistic value. For many years, banks all over the world were carrying
huge non-performing assets but were not recognizing this value erosion. Writing off loans
helps banks clean their accounting entry recognizing that a loan has become un-
collectable but does not in any way impair a bank’s ability to take action against a
borrower by taking assets belonging to the borrower to recover the loan. An exception is
when a compromise agreement is arrived at or in the case of settlements made under
banks own schemes (Haneef et al., 2012).
2.5 Chapter Summary
The chapter was able to review literature by various writers. The main objective which
was to determine the relationship between the credit risk management and non-
performing loans in Kenyan Banks has been covered fully. Precisely, literature review has
covered the process of credit risk management at KCB Group, the extent to which non-
performing loans affect the financial performance of KCB Group, to develop mechanisms
of reducing credit risk-non performing loans at KCB Group and the chapter summary.
The next chapter discuses on the research methodology giving details of the research
procedures and a data presentation method that will be used.
28
CHAPTER THREE
3.0 RESEARCH METHODOLOGY
3.1 Introduction
This chapter highlights the research methodology that was applied in this study. It
deliberates on the research design, the population under research focusing on the
sampling design, sampling frame, sampling technique sample size and the data collection
and analysis method that was used in this study. A summary of the research methodology
was given at the end of this section.
3.2 Research Design
The data required,methods used to collect data and analysis of the data are explained
through research design.The data and methods and the way in which they are organized in
a research project need to be most effective in producing the answers to the research
question (Wyk; 2014). The research adopted descriptive research design which assists in
explaining the relationship between credit risk management and non-performing loans at
KCB. Descriptive research was to help provide answers to the questions of who, what,
when, where, and how associated with a particular research problem. It is utilized to get
data concerning the present status of the events and to define "what exists" regarding
variables or conditions in a circumstance (Labaree, 2015).
This design is concerned with conditions,practices,structures,differences or relationships
that exists,opinions held,processes that are goin on or trends that are evident making it the
suitable research design for this research.The advantage of this research design is that it is
less time consuming and response rate is high. Chances of respondents refusing to
cooperate are very low especially when the use of questionnaires as a data collection tool
is used (Coopers & Schindler, 2006). The design focused on understanding the
relationship between credit risk management and non-performing loans constituting the
blueprint for the collection, measurement and analysis of data.
29
3.3 Population and Sampling Design
3.3.1 Population
Cooper & Schindler (2006) describe populace as the entire collection of essentials where
references have to be made. In relation to research, population is a large collection of
individuals or objects that are the main focus of a scientific query (Castillo, 2009).The
target population was administrative staff at KCB head office and its branches in Kenya
drawn from the Credit department targeting 200 credit officials.
3.3.2 Sampling Design
3.3.2.1 Sampling Frame
Sampling frame is recognized as a list of features from which a sample is drawn (Cooper
& Schindler, 2006). It is a device used to define a researcher’s population of interest. It
defines a set of elements from which a researcher can select a sample of the target
population. The selection of a sample from a defined target population requires the
construction of a sampling frame which ensures that the right population that the
researcher is targeting for the research is identified (Currivan, 2004). In this study, the
sampling frame encompasses the credit officials from KCB head office and branches in
Kenya.
3.3.2.2 Sampling Technique
This study adopted a non-probability sampling technique. This is a technique that does
not use chance selection procedures but relies on personal judgment of the researcher
(Maholtra, 2011). Under non-probability sampling, the research adopted a judgmental
sampling technique which endeavours to acquire a sample of components in view of the
judgment of the researcher. The elements comprised of credit officials from KCB head
office and Branches in Kenya.
3.3.2.3 Sample Size
The sample size used in this research was the 200 credit officials at KCB head office and
branches in Kenya. Statistical determination was utilized to distinguish the proper sample
size which can be summed up to represent the whole target populace. To get the
minimum populace sample for this study, the research carried out a census which was
30
considered to be free from error and to give 100% surety and representative of the
populace (Handy, 2009).
3.4 Data Collection Method
Primary information was utilized as a part of this study. The information was gathered by
use of questionnaires which were structured according to the specific objectives of the
research. The utilization of questionnaires was supported in light of the fact that they give
an efficient and effective way of collecting data within a small period of time and they
assist in easier coding and analysis of data. The questionnaires entailed open ended
questions that provide an understanding of new ideas and closed ended questions that
ensure respondents are controlled to specific categories.
This research used both open and close ended questions in line with the objectives of the
study using a five point Likert scale for the closed ended questions. The questionnaires
contained two sections. The first section sought to establish the respondents’ demographic
data while the successive sections sought to find the respondents’ opinions on the three
objectives of the study.
3.5 Research Procedures
The questionnaires were pretested first on 4 respondents at the credit division at the head
office to assess the fulfilment, exactness, precision, accuracy and clarity of the
questionnaires. This aided in the acceptance of the last survey that was utilized as a part
of the study. After the change of the last questionnaires, the analyst clarified the reason
for the examination and looked for consent from the head office to complete the study on
the chose branches in Nairobi. The questionnaires were directed to credit officials with
the help of a qualified research assistant during work hours. This method of
administration was justified as the nature of the research requires expert knowledge on
credit information sharing to be able to provide appropriate response as expected from the
research objectives. Keeping in mind the end goal to guarantee high survey reaction rate,
the specialist utilized updates and pre-contact with respondents. Prologue to do an
examination in the organization was done utilizing an introductory letter looking for the
organization's power to direct the exploration and in addition acknowledgment to
guarantee secrecy of data got and obscurity of respondent's personality.
31
3.6 Data Analysis Method
Qualitative and Quantitative techniques were utilized in data analysis. Qualitative
technique refers to any sort of exploration that produces discoveries not arrived at by
means of statistical procedures or other means of quantification. This approach is
regularly communicated as individual worth judgments from which it is hard to make any
aggregate general inferences. Quantitative research on the other hand intends to make
speculations regarding a particular populace in light of the after effects of an agent test of
that populace. The research findings then subjected to scientific or measurable
manipulation to produce a broad representation of data to the total population and
forecasts of future events under different conditions (McDanile and Gates, 2009).
The gathered information was coded and evaluated using descriptive statistics,
particularly mean and standard deviation to portray every variable under study. Factor
Analysis was utilized as a part of measuring the variability of the variables that were
observed and correlated. The information was examined using Statistical Package for
Social Sciences (SPSS) program and interpreted in tables and figures presenting the
findings of the research.
The collected data was coded and analysed using the descriptive statistics, specifically
mean and standard deviation to describe each variable under study. Factor analysis was
also used in measuring the variability of the variables that were observed and
correlated. The data was analysed using Statistical Package for Social Sciences (SPSS)
program and presented using tables, and figures to give a clear picture of the research
findings.
3.7 Chapter Summary
The chapter highlighted the different techniques and methodology this research adopted
in conducting the study in order to answer the research objectives of this research. The
research adopted descriptive research design and a target population of 100 credit
managers was used. The information was collected using primary data collection; the
research procedures involved conducting of a pilot study to affirm the reliability of the
research questionnaire. Information was analysed using Statistical Package for Social
Sciences (SPSS) program and presented in tables, and figures. Chapter four presents the
finding and analysis of the study.
32
CHAPTER FOUR
4.0 RESULTS AND FINDINGS
4.1 Introduction
This chapter shows the analysed results and findings of the study on the study questions
regarding the data collected from the respondents. The first part of this chapter covers the
response rate. The second part is about the background information, which presents
demographic presentation of the respondents. The third part examines how credit risk
management practices affect the prevalence of non-performing loans. The fourth part
investigates the effects on non-performing loans on financial performance. The fifth part
identifies credit risk management mechanisms that reduce levels of non-performing loans
and the final section is the summary of the whole chapter.
4.2 Response Rate
A response rate is the total number of respondents or individuals participated in a study
and it is presented in the form of percentage. This study had a sample size of 100
individuals working with Kenya Commercial Bank Credit Department at their
headquarters in Nairobi.
The study in Figure 4.1 represents the response rate of the study. From the study, it is
clear that 70% of the respondents took part in the study while 30% did not participate in
the study. The study, therefore, implies that the response rate was good to be used.
Figure 4.1: Response Rate
33
4.3 Background Information
4.3.1 Gender of Respondents
Figure 4.2 shows the gender representation of the study. From the table, it is well shown
that 68.6% of the population at Kenya Commercial Bank credit department is male while
31.4% is female. The study implies that there is more male population than female
population at KCB credit department.
Figure 4.2: Gender of Respondents
4.3.2 Age Group of Respondents
The study used Figure 4.3 to show the level of education of the population at Kenya
Commercial Bank credit department. From the figure, it is indicated that 4.3% of
respondents are between 18 to 28 years of age, 74.3% of respondents are between 29 to
39 years of age, 12.9% of respondents are between 40 to 50 years of age and 8.6% of
respondents are above 50 years of age.
The implication of the study is that majority of the population working at the KCB credit
department are within 29 to 39 years of age. The assumption from the study is that Kenya
Commercial Bank needs more of the youth than older people in the credit department.
34
Figure 4.3: Age Group of Respondents
4.3.3 Experience in Experiential Marketing
Table 4.1 depicts the relationship between age group and respondents’ current position at
KCB. According to the table, 100% of respondents within 18 to 28 years of age are loan
officers. On the other hand, 68.1% of respondents who were in the age bracket of 29 to 39
years were credit analysts, 17% were recovery/monitoring officer and 14.9% of the
respondents were credit managers.
The study also shows that 71.4% of respondents who were within 40 to 50 years of age
were credit analysts and 28.6% were credit managers. For those respondents who were
above 50 years of age, 33.3% were credit analysts and 66.7% were credit managers.
Table 4.1: Current Position
What is your current Position
Total Loan
Officer
Credit
Analyst
Monitoring
Officer
Credit
Manager
Age
Gro
up
18-28
YRS
2 0 0 0 2
100.0% 0.0% 0.0% 0.0% 100.0%
29-39
YRS
0 32 8 7 47
0.0% 68.1% 17.0% 14.9% 100.0%
40-
50YRS
0 5 0 2 7
0.0% 71.4% 0.0% 28.6% 100.0%
ABOVE
50 YRS
0 2 0 4 6
0.0% 33.3% 0.0% 66.7% 100.0%
Total 2 39 8 13 62
3.2% 62.9% 12.9% 21.0% 100.0%
35
4.3.4 Work Experience
Table 4.2 displays the relationship between gender of respondents and work experience.
From the table, 58.3% of male respondents have worked for the KCB for 5 to 10 years,
14.6% have worked for the bank for 11 to 15 years and 27.1% of respondents have
worked for the bank for above 15 years. Contrary, 9.1% of female respondents have
worked for KCB for less than 5 years, 77.3% have worked for the bank for 5 to 10 years
and 13.6% of the same category of respondents has worked for the bank for above 15
years.
Table 4.2: Work Experience
For how long have you worked for your organization
Total Less than 5
years
5-10
years 11-15 years Above 15 years
Gen
der
Male 0 28 7 13 48
0.0% 58.3% 14.6% 27.1% 100.0%
Female 2 17 0 3 22
9.1% 77.3% 0.0% 13.6% 100.0%
Total 2 45 7 16 70
2.9% 64.3% 10.0% 22.9% 100.0%
On a general point of view, more of the respondents (64.3%) have worked for the bank
for 5 to 10 years.
4.3.5 Determinants of Non-Performing Loans
The study in Table 4.3 reveals the correlation between work experience of respondents
and determinants of non-performing loans. From the study, all (100%) of the respondents
with less than 5 years of work experience agree that determinants of non-performing
loans are obvious. The study also shows that 8.9% of respondents with 5 to 10 years of
work experience strongly agreed that determinants of non-performing loans are obvious,
37.8% agreed to the statement, 35.6% disagreed and 17.8% strongly disagreed that
determinants of non-performing loans at KCB are obvious.
The study on the other hand shows that 42.9% of respondents with 11 to 15 years of work
experience agreed that determinants of non-performing loans are obvious and 57.1%
strongly disagreed to the statement. For the respondents with above 15 years of work
36
experience, 14.3% strongly agreed that determinants of non-performing loans are
obvious, 57.1% agreed to the statement and 28.6% disagreed that determinants of non-
performing loans at KCB are obvious.
Table 4.3: Determinants of Non-Performing Loans
Are the determinants of nonperforming loans
obvious Total
Strongly
Agree Agree Disagree
Strongly
Disagree
For
how
long h
ave
you
work
ed f
or
your
org
aniz
atio
n
Less than
5 years 0 2 0 0 2
0.0% 100.0% 0.0% 0.0% 100.0%
5-10
years 4 17 16 8 45
8.9% 37.8% 35.6% 17.8% 100.0%
11-15
years 0 3 0 4 7
0.0% 42.9% 0.0% 57.1% 100.0%
Above 15
years 2 8 4 0 14
14.3% 57.1% 28.6% 0.0% 100.0%
Total 6 30 20 12 68
8.8% 44.1% 29.4% 17.6% 100.0%
4.3.6 Experience in the Credit Department
The study in Table 4.4 reveals the relationship between the length the respondents have
worked for the bank and the length the respondents have worked in the bank credit
department. From the Table 50% of respondents with less than 5 years of work
experience had worked in the bank’s credit department for less than 5 years and 50% of
respondents with work experience of 5 to 10 years had worked for the bank’s credit
department for less than 5 years. The study shows that 63.6% of respondents with 5 to 10
years of work experience had worked for the bank’s credit department for 5 to 10 years,
13.6% of work experience within 11 to 15 years had worked for the bank’s credit
department for 5 to 10 years and 22.7% of respondents with above 15 years of work
experience had worked for the bank’s credit department for 5 to 10 years.
The table also depicts that 75% of the respondents with 11 to 15 years of work experience
had worked for the bank’s credit department for 11 to 15 years and 20% of respondents
with above 15 years of work experience had worked for the bank’s credit department for
11 to 15 years. Finally, the study reveals that all (100%) of respondents with above 15
37
years work experience had worked for the organization’s credit department for more than
15 years.
Table 4.4: Experience in the Credit Department
For how long have you worked for your
organization Total
Less than
5 years 5-10 years
11-15
years
Above 15
years
What
is
your
exper
ien
ce i
n t
he
ban
k
cred
it d
epar
tmen
t
Less than 5
years 2 2 0 0 4
50.0% 50.0% 0.0% 0.0% 100.0%
5-10 years 0 28 6 10 44
0.0% 63.6% 13.6% 22.7% 100.0%
11-15 years 0 0 16 4 20
0.0% 0.0% 80.0% 20.0% 100.0%
Above 15
years 0 0 0 2 2
0.0% 0.0% 0.0% 100.0% 100.0%
Total 2 45 7 16 70
2.9% 64.3% 10.0% 22.9% 100.0%
4.4 Credit Risk Management Practices and Prevalence of Non-Performing Loans
The objective of the study was to determine the effects of credit risk management
practices on the prevalence of non-performing loans. The study sought information from
credit scoring, credit manual, credit risk management policy, credit bureau, assessing
borrower, credit risk analysis, loan appraisal, and personal loans. The study employed
coefficient of variation (C.V) to determine the level of significance of the study variables.
38
Table 4.5: Credit Risk Management Practices
N Mean
Std.
Deviation C.V
The bank considers characteristics of the
borrower, capacity, conditions and
Collateral/Security in credit scoring for
business and corporate loans
70 4.79 .413 0.086
The bank has a credit manual that
documents and elaborates the strategies for
managing Credit
70 4.74 .440 0.093
The bank has a well-documented Credit
Risk Management policy 70 4.70 .462 0.098
The banks contacts the credit bureau to
assist in decision making to lend their
customers
70 4.81 .490 0.102
The bank has strategies for granting credits
focus on who, how and what should be done
at the branches and corporate division levels
while assessing borrowers
70 4.43 .604 0.136
The bank conducts a credit risk analysis on
businesses and individuals before lending 70 4.61 .644 0.139
Loan appraisal and subsequent approvals are
based on borrower’s capacity, character,
condition, credit history and collateral
70 4.64 .799 0.172
The bank uses a credit scoring model in
credit risk assessment 70 4.23 .837 0.198
The bank faces intense challenges such as
government controls in managing credit risk 70 3.69 .753 0.204
The bank considers physical and financial
characteristics in credit scoring models for
personal loans?
70 5.16 4.751 0.921
The study in Table 4.5 shows that Kenya Commercial Bank considers characteristics of
the borrower, capacity, conditions and Collateral/Security in credit scoring for business
and corporate loans. The bank has a credit manual that documents and elaborates the
strategies for managing Credit. The study also shows that the bank has a well-documented
Credit Risk Management policy. The policies make the banks to contact the credit bureau
to assist in decision making to lend their customers. The study shows that the bank has
strategies for granting credits focus on whom, how and what should be done at the
branches and corporate division levels while assessing borrowers. The bank conducts a
credit risk analysis on businesses and individuals before lending. The banks’ credit
policies have made the loan appraisal and subsequent approvals based on borrower’s
capacity, character, condition, credit history and collateral.
39
4.4.2 Documented Credit Risk Management Policy
Table 4.6 depicts the cross-tabulation between respondents’ gender and credit risk
management policy. From the table it is shown that 31.3% of male respondents agreed
and 68.8% strongly agreed that the bank has a well-documented credit risk management
policy. On the other hand, 27.3% of female respondents agreed and 72.7 strongly agreed
that Kenya Commercial Bank has a well-documented credit risk management policy.
Table 4.6: Documented Credit Risk Management Policy
The bank has a well-documented Credit Risk Management
policy Total
Agree Strongly Agree
Gen
der
MALE 15 33 48
31.3% 68.8% 100.0%
FEMALE 6 16 22
27.3% 72.7% 100.0%
Total 21 49 70
30.0% 70.0% 100.0%
4.4.3 Credit Manual
The study in Table 4.7 shows the relationship between age group of respondents and
credit manual. From the study, 66.7% of respondents within 18 to 28 years of age agreed
and 33.3% strongly agreed that the bank has a credit manual that documents and
elaborates the strategies for managing credit. The study also shows that 19.2% of
respondents within 29 to 39 years of age agreed and 80.8% strongly agreed to the latter
statement.
The study reveals that 22.2% agreed and 77.8% strongly agreed that the bank has a credit
manual that documents and elaborates the strategies for managing credit. For respondents
with above 50 years of age, 66.7% agreed and 33.3% strongly agreed to the latter
statement.
40
Table 4.7: Credit Manual
The bank has a credit manual that documents
and elaborates the strategies for managing
Credit Total
Agree Strongly Agree
Age
Gro
up
18-28 YRS 2 1 3
66.7% 33.3% 100.0%
29-39 YRS 10 42 52
19.2% 80.8% 100.0%
40- 50YRS 2 7 9
22.2% 77.8% 100.0%
ABOVE 50
YRS 4 2 6
66.7% 33.3% 100.0%
Total 18 52 70
25.7% 74.3% 100.0%
4.4.4 Strategies for Granting Credits
Table 4.8 shows the relationship between respondent’s current position and strategies for
granting credits. From the study all (100%) loan officers agreed that the bank has
strategies for granting credits focus on whom, how and what should be done at the
branches and corporate division levels while assessing borrowers. On the other hand,
10.3% of credit analysts were uncertain to the statement that the bank has strategies for
granting credits focus on who, how and what should be done at the branches and
corporate division levels while assessing borrowers while 30.8% agreed and 59% strongly
agreed to the latter statement.
The study also reveals that 62.5% of recovery and monitoring officers agreed and 37.5%
strongly agreed that the bank has strategies for granting credits focus on who, how and
what should be done at the branches and corporate division levels while assessing
borrowers. The study also shows that all (100%) of credit managers agreed to the latter
statement.
41
Table 4.8: Strategies for Granting Credit
The bank has strategies for granting credits
focus on who, how and what should be done
at the branches and corporate division levels
while assessing borrowers Total
Uncertain Agree Strongly Agree
What is
your
current
Position
Loan Officer 0 2 0 2
0.0% 100.0% 0.0% 100.0%
Credit Analyst 4 12 23 39
10.3% 30.8% 59.0% 100.0%
Recovery/Monitoring
Officer 0 5 3 8
0.0% 62.5% 37.5% 100.0%
Credit Manager 0 13 0 13
0.0% 100.0% 0.0% 100.0%
Total 4 32 26 62
6.5% 51.6% 41.9% 100.0%
4.4.5 Credit Risk Analysis
Table 4.9 depicts the relationship between respondents’ experience in the bank’s credit
department and credit risk analysis. According to the table, 100% of respondents with less
than 5 years in the credit department agreed that the bank conducts a credit risk analysis
on businesses and individuals before lending. The study also shows that 13.6% of the
respondents with 5 to 10 years of experience were uncertain about the statement while
11.4% agreed and 75% strongly agreed to the statement.
The study reveals that 40% of respondents with 11 to 15 years in the credit department
agreed and 60% strongly agreed that the bank conducts a credit risk analysis on
businesses and individuals before lending. All (100%) of the respondents with above 15
years of work experience in the bank’s credit department agreed that the bank conducts a
credit risk analysis on businesses and individuals before lending.
42
Table 4.9: Credit Risk Analysis
The bank conducts a credit risk analysis on
businesses and individuals before lending Total
Uncertain Agree Strongly Agree
What
is
your
exper
ien
ce i
n t
he
ban
k
cred
it d
epar
tmen
t
Less than 5
years 0 0 4 4
0.0% 0.0% 100.0% 100.0%
5-10 years 6 5 33 44
13.6% 11.4% 75.0% 100.0%
11-15 years 0 8 12 20
0.0% 40.0% 60.0% 100.0%
Above 15 years 0 2 0 2
0.0% 100.0% 0.0% 100.0%
Total 6 15 49 70
8.6% 21.4% 70.0% 100.0%
4.5 Effects of Non-Performing Loans on Financial Performance
The study aimed at establishing the effects on non-performing loans on financial
performance. The study sought information from non-performing loans, lending capacity,
capital markets, shareholders’ funds, insolvency, undercapitalization and interest rates.
Table 4.10 used mean, standard deviation, total correlation and cronbach’s alpha as a
statistical tool that was used to rank the variables from the highly significant to the lowly
significant.
From the table, it is indicated that the item mean scores ranged from 3.19 to 4.70. The
lowest rating was for the item “to assess the effects of non-performing loans and it was
found that non-performing loans lead to shortening of loan repayment periods” with a
mean of 3.19 (SD=1.308) and the highest score was for the item “Non-performing loans
negatively affects a bank’s lending capacity due to diminished core capital” with a mean
of 4.47 (SD=0.616). The item to total correlations ranged from .389 to .430 which was
acceptable. The Cronbach’s alpha for the effects of non-performing loans on financial
performance scale was 0.838 which is good reliability.
43
Table 4.10: Non-Performing Loans on Financial Performance
Mean Std.
Deviation
Corrected
Item-Total
Correlation
Cronbach's
Alpha if
Item
Deleted
Non-performing loans negatively affects a
bank’s lending capacity due to diminished
core capital
4.47 .616 .430 .811
Non-performing loans have a negative
effect on the bank’s profits through
increased provisions
4.70 .634 .608 .799
High levels of non-performing loans deny
banks easy access to capital markets; both
Debt and Equity.
4.28 .745 .646 .792
Non-performing loans negatively affects
the shareholder’s funds 4.44 .852 .591 .794
Non-performing loans can result to
insolvency thus collapse of banks. 4.38 .917 .536 .799
High levels of non-performing loans can
lead to undercapitalization of the bank
resulting to job losses
3.80 1.042 .621 .788
Non-performing loans leads to revision
upwards of interest rates thus denial of
credit.
3.30 1.049 .206 .834
Non-performing negatively affect a
country’s Gross Domestic Product (GDP) 3.98 1.105 .531 .799
High prevalence of non- performing loans
creates a negative signalling effect in the
stock market thus lower share prices and
market capitalisation.
3.70 1.268 .692 .778
Non-performing loans leads to shortening
of loan repayment periods 3.19 1.308 .389 .821
Reliability Statistics
Cronbach's Alpha
Cronbach's Alpha Based on Standardized
Items N of Items
.818 .838 10
4.5.1 Non-Performance Loans and Profitability
Table 4.11 shows the level at which respondents agreed and disagreed to the statement of
effects of non-performance loans on profitability. From the table, the study confirms that
2.9% of respondents disagreed that non-performing loans have a negative effect on the
bank’s profits through increased provisions, 18.6% agreed and 78.6% strongly agreed to
the statement.
44
Table 4.11: Non-Performing Loans and Profitability
Non-performing loans have a negative effect on the bank’s profits through increased
provisions
Frequency Percentage
Disagree 2 2.9
Agree 13 18.6
Strongly Agree 55 78.6
Total 70 100.0
4.5.2 Access to Capital Market
Table 4.12 shows how high levels of non-performing loans affect banks’ access to capital
markets. From the table, 24.3% of respondents were uncertain that high levels of non-
performing loans deny banks easy access to capital markets; both debt and equity, 34.3%
agreed to the statement, and 41.4% of the respondents strongly agreed that high levels of
non-performing loans deny banks easy access to capital markets; both debt and equity.
Table 4.12: Access to Capital Market
High levels of non-performing loans deny banks easy access to capital markets; both
debt and equity
Frequency Percentage
Uncertain 17 24.3
Agree 24 34.3
Strongly Agree 29 41.4
Total 70 100.0
4.5.3 Lending Capacity
To establish how non-performing loans negatively affects a bank’s lending capacity,
Table 4.13 was used. From the table, 5.7% of respondents were uncertain that non-
performing loans negatively affects a bank’s lending capacity due to diminished core
capital, 45.7% agreed and 48.6% strongly agreed to the statement that non-performing
loans negatively affects a bank’s lending capacity due to diminished core capital.
45
Table 4.13: Lending Capacity
Non-performing loans negatively affects a bank’s lending capacity due to diminished
core capital
Frequency Percentage
Uncertain 4 5.7
Agree 32 45.7
Strongly Agree 34 48.6
Total 70 100.0
4.5.4 Insolvency
Table 4.14 shows how respondents agreed and disagreed to the statement of non-
performing loans and insolvency. From the study, 2.9% of respondents strongly disagreed
that non-performing loans can result to insolvency thus collapse of banks, 10% of
respondents were not sure about the latter statement, and 25.7% of respondents agreed to
the statement. The study also revealed that 52.9% of the respondents strongly agreed that
non-performing loans can result to insolvency thus collapse of banks, while 8.6% of
respondents did not take part in this statement.
Table 4.14: Insolvency
Non-performing loans can result to insolvency thus collapse of banks
Frequency Percentage
Strongly Disagree 2 2.9
Uncertain 7 10.0
Agree 18 25.7
Strongly Agree 37 52.9
Total 64 91.4
0 6 8.6
70 100.0
4.5.5 Shareholder’s Funds
Table 4.15 shows how non-performing loans negatively affects the shareholder’s funds.
From the table, 2.9% of respondents strongly disagreed that non-performing loans
negatively affects the shareholder’s funds, 4.3% of the respondents were uncertain about
the statement. The study also shows that 40% of the respondents agreed that non-
performing loans negatively affects the shareholder’s funds while 52.9% of the
respondents strongly agreed to the statement.
46
Table 4.15: Shareholder’s Funds
Non-performing loans negatively affects the shareholder’s funds
Frequency Percentage
Strongly Disagree 2 2.9
Uncertain 3 4.3
Agree 28 40.0
Strongly Agree 37 52.9
Total 70 100.0
4.6 Credit Risk Management Mechanisms that Reduce Non-Performing Loans
The study aimed at examining the credit risk management mechanisms that reduce non-
performing loans. The study in Table 4.16 reveals the correlations between non-
performing loans and variables that reduce levels of non-performing loans. The study
found that Educating clients on borrowing terms and conditions helps clients make
accurate decisions easing reliance on collateral (r= 0.490**, p<0.01, N= 70). Strict system
related credit performance monitoring ensures better loan performance (r= 0.677**,
p<0.01, N= 70).
Table 4.16: Credit Risk Management
Reducing
Nonperforming Loans
Educating clients on borrowing terms
and conditions helps clients make
accurate decisions easing reliance on
collateral.
Pearson Correlation .490**
Sig. (2-tailed) .000
N 70
Strict system related credit
performance monitoring ensures better
loan performance
Pearson Correlation .677**
Sig. (2-tailed) .000
N 70
Frequent restructuring of non-
performing loans to good book lowers
the levels of non-performing loans.
Pearson Correlation .426**
Sig. (2-tailed) .000
N 70
Enhanced follow up post migration to
NPL enhances collection and
classification to good book
Pearson Correlation .833**
Sig. (2-tailed) .000
N 70
**. Correlation is significant at the 0.01 level (2-tailed).
The study also shows that frequent restructuring of non-performing loans to good book
lowers the levels of non-performing loans (r= 0.426**, p<0.01, N= 70). Enhanced follow
up post migration to non-performing loans enhances collection and classification to good
book (r= 0.833**, p<0.01, N= 70).
47
4.6.1 Reducing Non-Performing Loans
Table 4.17 shows how different variables reduce non-performing loans. The study shows
that adequate annual budget allocations for loan monitoring ensures good asset quality (r=
0.870**, p<0.01, N=70), collateralized loans perform better and thus managing loan
default (r= 0.663**, p<0.01, N=70), frequent reviews of sector limits in line with the
economy lending ensures a quality book (r= 0.752**, p<0.01, N=70) and writing off
debts problem debts reduces the levels of non-performing loans (r= 0.398**, p<0.01,
N=70).
Table 4.17: Reducing Non-Performing Loans
Reducing
Nonperforming Loans
Adequate annual budget allocations
for loan monitoring ensures good
asset quality
Pearson Correlation .870**
Sig. (2-tailed) .000
N 70
Collateralized loans perform better
and thus managing loan default
Pearson Correlation .663**
Sig. (2-tailed) .000
N 70
Frequent reviews of sector limits in
line with the economy lending ensures
a quality book
Pearson Correlation .752**
Sig. (2-tailed) .000
N 70
Internal Appraisal Credit Rating
Systems assist in reducing the levels
of NPLs
Pearson Correlation .737**
Sig. (2-tailed) .000
N 70
Writing off debts problem debts
reduces the levels of non performing
loans
Pearson Correlation .398**
Sig. (2-tailed) .001
N 70
**. Correlation is significant at the 0.01 level (2-tailed).
4.6.2 Model Summary of Credit Risk Management Mechanisms
When predicting the value of a variable based on the value of another variable, a model
summary is used. The variable being predicted in this case is called the dependent
variable. The variable being used to predict the other variable's value is called the
independent variable.
Table 4.18 depicts the model summary of the study. The model summary provides
information about the regression line’s ability to account for the total variation in the
48
dependent variable. From the table, the value of R2 is 0.820, which means that 82 percent
of the total variance in non-performing loans has been explained by variability in credit
risk management practices.
Table 4.18: Model Summary of Credit Risk Management Mechanisms
Model Summary
Model R R Square
Adjusted R
Square
Std. Error of the
Estimate
1 .906a .820 .812 .24141
a. Predictors: (Constant), Enhanced follow up post migration to NPL enhances collection
and classification to good book, Frequent restructuring of non-performing loans to good
book lowers the levels of non-performing loans. , Educating clients on borrowing terms
and conditions helps clients make accurate decisions easing reliance on collateral.
4.6.3 Anova of Credit Risk Management Mechanisms
The regression model, as indicated in Table 4.19 predicted the outcome variable
significantly well. This is shown at the "Regression" row and at the Sig. column. This
indicates the statistical significance of the regression model that is applied. For this case,
P is 0.000 which is less than 0.01 and indicates that; overall, the model applied is
significantly good enough in predicting the outcome variable.
Table 4.19: Anova of Credit Risk Management Mechanisms
ANOVAa
Model Sum of Squares Df Mean Square F Sig.
1 Regression 17.566 3 5.855 100.467 .000b
Residual 3.846 66 .058
Total 21.412 69
a. Dependent Variable: Reducing Nonperforming Loans
b. Predictors: (Constant), Enhanced follow up post migration to NPL enhances collection
and classification to good book, Frequent restructuring of non-performing loans to good
book lowers the levels of non-performing loans. , Educating clients on borrowing terms
and conditions helps clients make accurate decisions easing reliance on collateral.
4.6.4 Coefficient of Variation of Credit Risk Management Mechanisms
Table 4.20 shows the coefficients that provided the information on the predictor variable.
The coefficients provided the information necessary to predict the levels of non-
performing loans basing on credit risk management mechanisms.
49
From the table, standardized beta coefficients are 0.239, 0.301, and 0.690, and are
significant at 0.000. It means that a unit change in the credit risk management
mechanisms lowers the level of non-performing loans at 0.239, 0.301, and 0.690.
Table 4.20: Coefficient of Variation of Credit Risk Management Mechanisms
Coefficientsa
Model
Unstandardized
Coefficients
Standardized
Coefficients T Sig.
B Std. Error Beta
1 (Constant) .473 .258
1.833 .071
Educating clients on borrowing
terms and conditions helps
clients make accurate decisions
easing reliance on collateral.
.234 .055 .239 4.249 .000
Frequent restructuring of non-
performing loans to good book
lowers the levels of non-
performing loans.
.147 .026 .301 5.661 .000
Enhanced follow up post
migration to NPL enhances
collection and classification to
good book
.461 .038 .690 12.06
1 .000
a. Dependent Variable: Reducing Nonperforming Loans
4.7 Chapter Summary
This chapter has provided the results and findings with respect to the data given out by
the respondents who were employees of Coca Cola Kenya. The chapter provided analysis
on the response rate, background information, experiential marketing on brand awareness,
experiential marketing on brand association and experiential marketing on brand loyalty.
The next chapter provides the summary, discussions, conclusions and recommendations.
50
CHAPTER FIVE
5.0 DISCUSSION, CONCLUSIONS AND RECOMMENDATIONS
5.1 Introduction
This chapter presents the discussion, conclusions and recommendations of the research.
The chapter is separated in different parts. In part 5.2, the summary of the study is
presented. The discussion and conclusion of the study is in part 5.3 and 5.4 respectively.
Part 5.5 establishes the recommendations.
This chapter presents the discussion, conclusions and recommendations of the study. The
chapter is divided in different parts. In part 5.2, the summary of the study is presented.
The discussion and conclusion of the study is in part 5.3 and 5.4 respectively. Part 5.5
demonstrates the recommendations.
5.2 Summary
The objective of the study was to investigate the relationship between credit risk
management practices and related factors and non-performing loans at KCB Group. The
study aimed at examining how Credit Risk Management practices prevalence of non-
performing loans at KCB Group, investigating the effects of Non-Performing Loans on
Financial Performance of KCB Group and to identifying credit risk management
mechanisms to reduce the level of non-performing loans at KCB Group.
The study adopted a descriptive research method in order to obtain the data that is
necessary, which facilitated the collection of the primary data as a way of getting into the
research objectives. The descriptive research design helped in observing the relationship
between Credit Risk Management practices and the prevalence of non-performing loans,
Non-Performing Loans and Financial Performance, and credit risk management
mechanisms and non-performing loans. The study utilized the use of questionnaires to
collect data from the respondents. The study concentrated on 100 credit managers in
KCB head office and branches in Kenya. Non-Probability sampling technique was
utilized embracing judgmental sampling technique attempted to obtain relevant
information from respondents. Data analysis was conducted using Statistical Package for
the Social Sciences (SPSS) on the information gathered to generate descriptive and
51
inferential statistics. Presentation of results was done in tables and figures and
recommendation and conclusion given. The study examined how Credit Risk
Management practices affect the prevalence of non-performing loans at KCB Group. The
study found that the bank considers characteristics of the borrower, capacity, conditions
and Collateral/Security in credit scoring for business and corporate loans. The bank has a
credit manual that documents and elaborates the strategies for managing credit. To reduce
on non-performing loans, the study found that the bank has a well-documented Credit
Risk Management policy. These policies help the bank to contacts the credit bureau to
assist in decision making to lend their customers. The study also reveals that the bank has
strategies for granting credits focus on who, how and what should be done at the branches
and corporate division levels while assessing borrowers.
The study established that non-performing loans negatively affects a bank’s lending
capacity due to diminished core capital. The study found that non-performing loans have
a negative effect on the bank’s profits through increased provisions. From the study, it
was revealed that high levels of non-performing loans deny banks easy access to capital
markets; both debt and equity. High levels of non-performing loans can lead to
undercapitalization of the bank resulting to job losses. The study also found that high
prevalence of non- performing loans creates a negative signalling effect in the stock
market thus lower share prices and market capitalisation. Non-performing loans leads to
shortening of loan repayment periods hence enhances the revision upwards of interest
rates thus denial of credit. The study revealed that non-performing loans negatively
affects the shareholder’s funds and this can loans can result to insolvency thus collapse of
banks.
The study assessed different credit risk management mechanisms that reduce the level of
non-performing loans. The study found that educating clients on borrowing terms and
conditions helps clients make accurate decisions easing reliance on collateral. Strict
system related credit performance monitoring ensures better loan performance. The study
established that frequent restructuring of non-performing loans to good book lowers the
levels of non-performing loans. Internal Appraisal Credit Rating Systems assist in
reducing the levels of NPLs. The study reveals that frequent reviews of sector limits in
line with the economy lending ensure a quality book. Adequate annual budget allocations
52
for loan monitoring ensure good asset quality. The study also found that collateralised
loans perform better and thus managing loan default.
5.3 Discussion
5.3.1 Credit Risk Management Practices and Prevalence of Non-Performing Loans
The study analyzed how credit risk management practices affect the prevalence of non-
performing loans at Kenya Commercial Bank (KCB). From the study, it was found that
the bank considers characteristics of the borrower, capacity, conditions and collateral or
rather security in credit scoring for business and corporate loans. Nafula (2009) agrees
with the findings of the study by asserting that to understand risk levels of credit users,
credit providers normally collect vast amount of information on borrowers. Statistical
predictive analytic techniques can be used to analyse or to determine risk levels involved
in credits, finances, and loans. This makes the credit providers to understand the default
risk levels. On the other hand, Mwirigi, (2009) concluded that credit risk profiling is very
important. The author found from Pareto principle that 80%-90% of the credit defaults
may come from 10%-20% of the lending segments. Mwirigi (2009) believed that
profiling the segments can reveal useful information for credit risk management. Credit
providers often collect a vast amount of information on credit users. To support the
findings of the study, Mwisho (2011) affirms that personal credit scores are normally
computed from information available in credit reports collected by external credit bureaus
and ratings agencies.
The study found that the bank has a credit manual that documents and elaborates the
strategies for managing credit. Gweyi (2013) noted that the banking industry in Kenya is
still growing with new entrants into the market still finding space in this competitive
sector. This according to the author calls for great effort to be enhanced to ensure
comprehensive and effective strategies are developed that minimize risk and maximize
loan performance at any particular point while in operation. Gweyi (2013) confirmed that
appropriate set of tools should be determined and sustained in time to avoid the likelihood
of loss and avoid banks being subjected to penalties of illiquidity and downsized
profitability. Miller (2007) confirms that credit scoring is a credit management technique
that analyses the borrower’s risk. The author revealed that a good credit scoring model
has to be highly discriminative, high scores reflect almost no risk and low scores
53
correspond to very high risk or the opposite depending on the sign condition. The more
discriminative the scoring system is, the better are the customers ranked from high to low
risk.
The study showed that the Kenya Commercial Bank has a well-documented credit risk
management policy. In support of the findings of the study, Mwisho (2011) asserts that
credit unions should have a written loan policy that is approved by the board of directors
of the financial institutions. The author adds that the board should review the policy on an
annual basis and revise where necessary. According to Mwisho (2011), the loan policy
should include the policy objective, eligibility requirements for receiving a loan,
permissible loan purposes, acceptable types of collateral, loan portfolio diversification
requirements, loan types, interest rates, terms, frequency of payments, maximum loan
sizes per product type, maximum loan amounts as a percentage of collateral values,
member loan concentrations, restrictions on loans to employees and officials, loan
approval requirements, monetary loan limits, loan documentation requirements and co-
signer requirements. Gestel and Baesen (2009) believe that loan concentration limits is
one of the critical element of the loan policy. Gestel and Baesen (2009) argue that the
credit unions should not issue a loan to a member or related parties if such loan would
cause that member or group of related parties to exceed the less of 10% of total assets or
25% of the credit union’s institutional capital.
From the study, it is well noted that the bank contacts the credit bureau to assist in
decision making to lend their customers. FSD (2013) considers CRB to refer to a
company licensed to collect and combine credit information on individuals from different
sources and provide that information upon the request of a bank. The study done by CBK
(2013) found that the reason for the development of a robust CRB is as a result of loan
default and NPL. CBK (2010) contend that Credit Reference Bureaus (CRB) supplements
the focal role acted by banks and other financial instituions in developing money services
an economy.They collect, manage and disseminate customer information to lenders
within a provided regulatory framework. The central role played by banks and other
financial institutions in extending financial services within an economy.
The study reveals that the bank has strategies for granting credits focus on who, how and
what should be done at the branches and corporate division levels while assessing
54
borrowers. Chen (2009) explained five techniques of credit vetting known as the five Cs
framework used in assessing a customer’s application for credit. According to Chen
(2009), among the five Cs framework is the character that assesses the willingness of the
customer to pay the loan by looking at the past credit history, credit rating of the firm, and
reputation of customers and suppliers. Rose (2008) found that the borrower’s honesty,
integrity and trustworthiness are assessed.
5.3.2 Effects of Non-Performing Loans on Financial Performance
The study established that non-performing loans has an impact on the performance of
financial institutions especially the banks. According to the study, it was found that non-
performing loans negatively affects a bank’s lending capacity due to diminished core
capital. Ogubunka (2007) confirms that it is regrettable that most banks are
undercapitalized which could be attributed to the fact that many of the banks were
established with little capital in place. Ogubunka asserts that this situation has further
worsened due to huge amount of non-performing loans which has taking up the capital
base of most of the banks. Inability to recover the non-performing loans, effect of
inflation and low level of initial capital has also worsened the situation. On the other
hand, the study found that high levels of non-performing loans deny banks easy access to
capital markets; both debt and equity. Ogundina (2009) confirms that non-performing
loans can affect the capital mobilization since investors will not invest in a bank with
huge non-performing loans.
The study also found that non-performing loans have a negative effect on the bank’s
profits through increased provisions. Altman and Sauders (2011) revealed that non
performing loans have a direct effect on the profitability of banks. Muritala and Taiwo
(2013) concluded that banks’ profitability is inversely influenced by the levels of loans
and advances, and non-performing loans thereby exposing them to great risk of illiquidity
and distress. Berger and De Young (2007) revealed that due to non-performing loans,
banks have to raise provisions for loan loss that decreases bank’s revenue reducing funds
for lending. According to the author, the corporate sector is then impaired due to the
cutback on loans making them unable to expand their working capital blocking their
chances of growing and continuing with their normal operation. This then triggers the
second round of business failure if banks are not able to finance firm’s working capital
55
and investments questioning the quality of bank loans that can lead to banking or
financial failure.
The study found that non-performing loans negatively affects the shareholder’s funds. To
support the point, Bennardo, et al. (2007) found that a sound and profitable banking
sector is able to withstand negative shocks and contribute to the stability of the financial
system. Barr, et al. (2009) believes that the economic efficiency and growth of the banks
can be impaired if non-performing loans remain existing and are continuously rolled over
locking the resources of the banks in unprofitable sectors. Contrary, Berger and De
Young, (2007) affirm that efforts to deal with non-performing loans have been put in
place with banks shortening the period when loans become past due. This puts loans on
borrowers’ schedule sooner requiring them to start paying immediately ensuring loan
losses do not worsen since lenders are at a risk of being forced to take full write-down if
borrowers go bankrupt. The study found that non-performing loans can result to
insolvency thus collapse of banks.
From the study, it was found that high levels of non-performing loans can lead to
undercapitalization of the bank resulting to job losses. Ogubunka (2007) confirm that
undercapitalized banks are not able to sustain their operation as a result of overtrading
and due to losses arising from their functions leading to job losses of their employees.
Ogubunka found that when a bank is undercapitalized, it becomes difficult for it to
continue with their operations due to fewer funds. On the other hand, Ogundina (2009)
asserts that in any business, capital serves as a mean by which losses may be absorbed. It
provides any business with security to withstand losses not covered by current earnings
pattern.
The study revealed that through information sharing improves bank’s information on
credit applicants. Pagano and Jappelli (2013) argue that if banks exchange information
about their client’s credit worthiness, they can assess also the quality of non-local credit
seekers, and lend to them as safely as they do with local clients. According to Coyle
(2010) when banks exchange information about borrowers’ types, the increase in lending
to safe borrowers may fail to compensate for an eventual reduction in lending to risky
types. Information sharing can also create incentives for borrowers to perform in line with
banks’ interests.
56
From the study, it is revealed that bank management need to be cautious in setting up a
credit policy that will not negatively affect profitability and also to know how credit
policy (and strategy) affects the operations of their banks to ensure judicious utilization of
deposits and maximization of profit. Muritala and Taiwo (2013) affirm that improper
credit risk management reduces the bank’s profitability, affects the quality of its assets
and increase loan losses and non-performing loans which may eventually lead to financial
distress.
5.3.3 Credit Risk Management Mechanism and Reduction of Non-Performing
Loans
The study confirms that educating clients on borrowing terms and conditions helps clients
make accurate decisions easing reliance on collateral. Rouse (2009) on the other hand
found that occurrence of bad debts can be reduced if lenders pay attention to monitoring
and control. Rouse identified internal records, visits and interviews, audited accounts and
management accounts as some of the ways that help in the monitoring and control
process. Noeton and Andenas (2016) believe that occurrence of non-performing loans can
be reduced through ensuring the utilization of the loan for the agreed purpose, identifying
early warning signals of any problem relating to the operations of the customer’s business
that are likely to affect the performance of the facility; ensuring compliance with the
credit terms and conditions and enabling the lender discusses the prospects and problems
of the borrower’s business.
From the study, it is revealed that strict system related credit performance monitoring
ensures better loan performance. Norton and Andenas (2007) affirm that through the
monitoring and control process, a lending decision can be made on sound credit risk
appraisal and assessment of creditworthiness of borrowers. Though past records of
satisfactory performance and integrity serve as useful guide to project trend in
performance they don’t guarantee future performance. Leply (2007) in his study, advise
lenders to have proper follow up and monitoring aspects which are essential. This
include; ensuring compliance with terms and conditions, monitoring end use of approved
funds, monitoring performance to check continued viability of operations, detecting
deviations from terms of decision and making periodic assessment of the performance of
the loans.
57
The study found that frequent restructuring of non-performing loans to good book lowers
the levels of non-performing loans. Jappelli and Marco (2007) found that for banks to
minimize the level of non-performing loans, credit unions must have in place written
guidelines on credit approval process, approval authorities of individuals or committees
as well as decision basis. The board of directors should always monitor loans. Approval
authorities will cover new credit approvals, renewals of existing credits and changes in
terms and conditions of previously approved credits particularly credit restructuring
which should be fully documented and recorded. Greuning and Iqbal (2007) assert that all
credit approvals should be at an arm’s length, based on established criteria. Credits to
related parties should be closely analysed and monitored so that no senior individual in
the institution is able to override the established credit granting process.
From the study, it was confirmed that adequate annual budget allocations for loan
monitoring ensures good asset quality. The study found that adequate resources help in
enhancing effective credit approval process. Kaplin (2009) found out that credit approval
technique helps to build savings-led institution and allows institution to learn about the
discipline and economic capacity of a client by observing frequency of deposits. Mwisho
(2011) found that prudent credit practice requires that persons empowered with the credit
approval authority should not have customer relationship responsibility. Approval
authorities of individuals should be commensurate to their positions within management
ranks as well as their expertise. Mwisho affirms that depending on the nature and size of
credit, it would be prudent to require approval of two officers on a credit application in
accordance with the Board’s policy. The approval process should be based on a system of
checks and balances.
From the study, it is well shown that writing off debts problem debts reduces the levels of
non-performing loans. Haneef et al., (2012) argue that writing off loans helps banks
clean their accounting entry recognizing that a loan has become un-collectable but does
not in any way impair a bank’s ability to take action against a borrower by taking assets
belonging to the borrower to recover the loan. An exception is when a compromise
agreement is arrived at or in the case of settlements made under banks own schemes.
Rose and Hudgins (2011) found out that write-offs are in recognition of reality that the
original asset has diminished in value and that it needs to be carried on the balance sheet
at its realistic value.
58
The study found that that just because you may have a low credit score because you are
listed as a defaulter does not mean that you cannot access credit for seven years. KBA
(2013) advise that that the lenders to take extra caution when dealing with borrowers with
low credit score and may charge a higher interest rate or request additional collateral for
the facility you are seeking from the banks. This shows that the CRB increases the cost of
borrowing for people who have been unfortunate to have their names with the bureau as
well as deny the banks the much needed facility therefore lowering the ability of lenders
to make more profits.
5.4 Conclusions
5.4.1 Credit Risk Management Practices and Non-Performance Loans
The study concludes that the bank considers characteristics of the borrower, capacity,
conditions and collateral in credit scoring for business and corporate loans. The bank has
strategies for granting credits focus on whom, how and what should be done at the
branches and corporate division levels while assessing borrowers. The study concludes
that Kenya Commercial Bank has a well-documented credit risk management policy. The
study also concludes that the bank contacts the credit bureau to assist in decision making
to lend their customers. Loan appraisal and subsequent approvals are based on borrower’s
capacity, character, condition, credit history and collateral. It is concluded from the study
that the bank has a credit manual that documents and elaborates the strategies for
managing credit. The Kenya Commercial Bank also has a credit manual that documents
and elaborates the strategies for managing Credit.
5.4.2 Effects of Non-Performing Loans on Financial Performance
The study concludes that non-performing loans negatively affects a bank’s lending
capacity due to diminished core capital. Non-performing loans also have a negative effect
on the bank’s profits through increased provisions. The study confirms that high levels of
non-performing loans deny banks easy access to capital markets; both debt and equity.
The study emphasizes that non-performing loans negatively affects the shareholder’s
funds hence resulting to insolvency thus collapse of banks. The study concludes that high
levels of non-performing loans can lead to undercapitalization of the bank resulting to job
losses. The study also concludes that high prevalence of non- performing loans creates a
negative signalling effect in the stock market thus lower share prices and market
59
capitalisation. Non-performing loans leads to revision upwards of interest rates thus
denial of credit and this may affect a country’s Gross Domestic Product (GDP).
5.4.3 Credit Risk Management Mechanism to Reduce Level of Non-Performing
Loans
The study concludes that educating clients on borrowing terms and conditions helps
clients make accurate decisions easing reliance on collateral. From the study, it was learnt
that strict system related credit performance monitoring ensures better loan performance.
The study concludes that the frequent restructuring of non-performing loans to good book
lowers the levels of non-performing loans. Adequate annual budget allocations for loan
monitoring ensure good asset quality. The study also concludes that writing off debts
problem debts reduces the levels of non- performing loans. The study found that
collateralized loans perform better and thus managing loan default. The study concludes
that frequent reviews of sector limits in line with the economy lending ensure a quality
book.
5.5 Recommendation
5.5.1 Recommendation for Improvement
5.5.1.1 Credit Risk Management Practices and Non-Performing Loans
The study recommends the commercial banks to develop proper credit manual that
documents and elaborates the strategies for managing credit. The study found that an
effective commercial bank considers characteristics of the borrower, capacity, conditions
and security in credit scoring for business and corporate loans. The study recommends
commercial banks develop and execute strategies for granting credits focus on who, how
and what should be done at the branches and corporate division levels while assessing
borrowers. The study also recommends banks to conduct credit risk analysis on
businesses and individuals before lending. From the study, it was found out that loan
appraisal and subsequent approvals should be based on borrower’s capacity, character,
condition, credit history and collateral. The study recommends commercial banks to use
credit scoring model in credit risk assessment.
60
5.5.1.2 Effects of Non-Performing Loans on Financial Performance
The study recommends commercial banks to reduce on the levels of non-performing
loans because they negatively affect a bank’s lending capacity due to diminished core
capital and the bank’s profits through increased provisions. The study recommends the
management of commercial banks to develop strategies to reduce level of non-performing
loans because high levels of non-performing loans deny banks easy access to capital
markets; both debt and equity. The study found that non-performing loans can result to
insolvency thus collapse of banks and this may affect a country’s Gross Domestic Product
(GDP). Because high levels of non-performing loans can lead to undercapitalization of
the bank resulting to job losses, the study recommends the commercial banks to be on the
lookout on the loans they give out to their customers. Non-performing loans leads to
revision upwards of interest rates thus denial of credit and this may cost the bank of its
customer base and market share.
5.5.1.3 Credit Risk Management Mechanisms to Reduce Non-Performing Loans
The study recommends commercial banks to educate their clients on borrowing terms and
conditions as this helps clients make accurate decisions easing reliance on collateral. The
study also recommends strict system related credit performance monitoring as it ensures
better loan performance. The study found that frequent restructuring of non-performing
loans to good book lowers the levels of non-performing loans hence the study
recommends the commercial banks to frequently review of sector limits in line with the
economy lending ensures a quality book. Internal Appraisal Credit Rating Systems assist
in reducing the levels of non-performing loans hence the study recommends commercial
banks to allocate adequate resources for loan monitoring to ensure good asset quality.
Collateralized loans perform better and thus managing loan default hence the study
recommends the banks to secure their loans with collaterals from the clients.
5.5.2 Recommendation for Further Research
The study aimed at investigating the relationship between credit risk management
practices and related factors on non-performing loans at KCB Group. The study
recommends future researchers and scholars to determine the best approaches commercial
banks should use to get minimize the increasing levels of non-performing loans.
61
REFERENCES
Abul, H. (2009). "Risk management practices of Islamic banks of Brunei Darussalam",
Journal of Risk Finance, 10(1), pp.23 – 37
Aduda, J., and Gitonga, J. (2011). The Relationship Between Credit Risk Management
and Profitability Among the Commercial Banks in Kenya. Journal of Modern
Accounting and Auditing, 934-946.
Al-Khouri, R. (2011). Assessing the Risk and Performance of the GCC Banking Sector.
International Reserach Journal of Finance and Economics, 72-78.
Altman, E. I., & Sauders, A. (2011). An Analysis and Critique of the BIS Proposal on
Capital Adequacy and Ratings. Journal of Banking and Finance, 25-46.
Barr, R. S., & Siems, T. (2009). Forcasting Banking Failure:A Bon-Parametric Frontier
Estimation Approach. Researches Economiques de Lovain, 417-429.
Bennardo, A., Pagano, M., & Piccolo, S. (2007). Multiple Bank Lending,Creditor Rights
and Information Sharing. University of Saleno, Mimeo.
Berger, N. A., & De Young, R. (2007). Problems Loans and Cost Efficience in
Commercial Banks,Washington DC. Journal of Banking and Finance, 507.
Business Daily. (2015, February 24). Stocks. Retrieved February 24, 2015, from
http://www.businessdailyafrica.com/stocks/-/1322440/1371880/-/sgardf/-
/index.html
Business Dictionary. (2015, 2 25). Retrieved 2 25, 2015, from Business Dictionary.com:
http://www.businessdictionary.com/definition/risk.html
Castillo, J. J. (2009, November 15). Explorable. Retrieved from Explorable Website:
http://explorable.com/research-population
Central Bank of Kenya. (2007). Bank Supervision Annual Report. Central Bank of
Kenya.
Chen, C. (2009). Bank Efficiency in Sub-Saharan African Middle-Income Countries. IMF
Working Paper No. WP/09/14.
Coyle, B. (2000). Framework for Credit Risk Management. Chartered Institute of
Bankers: United Kingdom.
Cooper, D. R., & Schindler, P. S. (2006). Business Research Methods. New York,NY:
McGraw-Hill.
Currivan, D. B. (2004). Sampling Frame.In T.L.Futing, A Bryman, & M.S. Lewis-Beck.
The SAGE of Social Science and Research Methods.
62
Credit Risk Assesment. (n.d.). In GARP, Credit Risk Management (pp. 2-30). Global
Assosciation of risk professionals.
Dr Wyk, B. V. (2014). Research design and methods. CapeTown: University of the
Western Cape.
Fofak, H. (2011). Non-Performing Loans in Sub-Saharab Africa:Causal Analysts and
Macroeconomic Implications. World Bank Policy Research.Working Paper, 3769.
FSD Kenya. (2012). Retrieved December 27, 2012, from https//:www.fsdkenya.org
Gaithi , E. W. (2010). A Survey of the Causes of Non-Performing Loans of Commercial
Banks in Kenya . Nairobi: University of Nairobi.
Gestel T and Baesen, B. (2009), Credit Risk Management, Basic Concept, Firm
Economic, Risk Compound, Regulating, Rating Analysis and Capital, Oxford
Press, New York,
GoK, (2008). Statistical Abstract, Kenya National Bureau of Statistics, Nairobi,
Government Printer.
Greuning, H & Iqbal, Z. (2007), Banking and Risk Environment in Archer, S. and Karim,
R. A. A. 2007, Finance: The Regulatory Challenge, John Wiley and Son (Asia)
Pte Ltd.
Gweyi, M. O. (2013). Credit Risk Mitigation Strategies Adopted By Commercial Banks
in Kenya. International Journal of Business and Social Science, 71-78.
Haneef, S., Riaz, T., Ramzan, M., Rana, M. A., Ishaq, H. M., & Karim, Y. (2012). Impact
of Risk Management on Non-Performing Loans and Profitability of Banking
Sector of Pakistan. International Journal of Business and Social Science, 307-315.
Hardy, D. (1998). Are Banking Crisis Predictable? . Finance & Development, IMF.
Harris, P. (2007). A banker’s view of BEE. Briefing to Business Map Foundation
members, Johannesburg. Retrieved on 20 March 2015 from:
http://www.businessmap.co.za.
Hoque, M.Z. & Hossain, M.Z., (2008). Flawed Interest rate policy and loan default:
experience from developing country. International review of business research
papers, 5(5), 235- 246.
Jansson, T. (2012), Performance Indicators for Microfinance Institutions: Technical
Guide, Micro Rate and Inter-American Development Bank, Washington, DC,
available at: www.microrate.com
63
Jappelli, T & Marco, P. (2007), Information Sharing, Lending and Defaults: Cross-
Country Evidence, Journal of Banking and Finance 26(10), 2017-45.
Jappelli, T., & Pagano, M. (2013). Public Information : A European Perspective, ''in
Credit reporting Systems and International Economy. (M. Miller, Ed.)
Kaplin, A., Levy, A., Qu, S., Wang, D., Wang, Y. and Zhang, J., (2009). The relationship
between default risk and interest rates: An empirical study. Moody’s Analytics,
Moody’s KMV Company.
Kargi, H. S. (2011). "Credit risk and the Performance of Nigeria banks". Ahmadu Bello:
University Zaria
Kenya Bankers Association. (2013). Retrieved from http://www.kba.co.ke
Kenya Credit Information Initiative. (2011). Credit Reporting on Global Best Practises.
Nairobi: Kenya Bankers Association.
Kipyego, D. K., and Wandera, M. (2013). Effects of Credit Information Sharing on Non-
Perfoming Loans: The Case of Kenya Commercial Bank Kenya. European
Scientific Journal, 168-193.
Kipyegon, L. R. (2011). Relationship between Credit information Sharing and
Performace of commercial Banks in Kenya. Unpublished BBAM Research
Paper,Makerere University.
Kithinji, A. M. (2010). Credit Risk Management and Profitability of Commercial Banks
in Kenya. Unpublished MBA Research Project,University of Nairobi.
Kurawa, J. M., & Garba, S. (2014). An Evaluation of the Effect of Credit Risk
Management (CRM) on the Profitability of Nigerian Banks . Journal of Modern
Accounting and Auditing, Vol 10. 104-115.
Koch, T.W., & MacDonald, S. (2007). Bank Management (5th ed.). Ohio: South-Western
Thompson Learning.
Kwambai, D. K., & Wandera, M. (2013). Effects of Credit Information Shairing On
NonPerforming Loans : The Case of Kenya Commercial Bank Kenya. European
Scientific Journal, 168-193.
Labaree, R. (2015, March 9). USC University of Southern California. Retrieved from
USC Libraries Website:
http://libguides.usc.edu/content.php?pid=83009&sid=818072
Malhotra. (2011, April 7). Malhotra, Business Process Redesign.
64
Marshal , I., and Onyekachi, O. (2014). Credit Risk and Performance of Selected Deposit
MoneyBanks in Nigeria: An Empirical Investigation. European Journal of
Humanities and Social Sciences, 1684-1694.
McColgan, P., (2009), Agency Theory and Corporate Governance: A Review of the
Literature from a UK Perspective, Available:
accfinweb.account.strath.ac.uk/wps/journal.pdf
McManus, S. (2010). A Guide to Credit Management in South Africa. Durban:
Butterworths.
Mikiko, F., (2007), Mounting Weigh Heavily on Bank Management; Stock Prices
Continue to fall, China, and the United, 2nd Editions, New York,
Miller, M, J. (2009), Credit Reporting Systems and the International Economy (Ed.).
Cambridge: MIT Press.
Misati, R. N., Njoroge, L., Kamau, A., & Ouma, S. (2010). Financial innovation and
monetary policy transmission in Kenya. International Research Journal of
Finance and Economics, 123-136.
Muritala, T. A., & Taiwo, A. S. (2013). Credit Management Spur Higher Profitability?
Evidence from Nigerian Banking Sector. Journal of Applied Economics and
Business, 46-53.
Mwangi, G. N. (2012). The Effect pf Credit Risk Management on the Financial
Performance of Banks in Kenya. 1-69.
Mwaniki, C., and Gachiri, J. (2014, February 23). KCB makes comeback to the capital
markets. Business Daily.
Mwengei, K. O. (2013). Assessing the Factors Contributing to Non –Performance Loans
in Kenyan Banks. European Journal of Business and Management, 155-162.
Mwirigi P. K (2009), An Assessment of Credit Risk Management techniques adopted by
micro finance institutions in Kenya. Unpublished MBA research project UoN.
Mwisho, A.M. (2011), “Basic lending conditions and procedures in commercial banks”.
The Accountant, 13(3), pp.16-19
Nafula, M. (2009). Factors Affecting Loan Repayment in Micro Finance Institutions: A
Case Study of Faulu Kenya, Nairobi Branch. UON. Unpublished Research
Project.
65
Nathenson, J.L. (2009). A Primer on Deals for Middle-Market Bankers. The RMA
Journal, 86(8), 46-54.
Ngigi, G. (2013, May 13). High interest rates leave banks with Sh70bn in bad loans.
Business Daily.
Ngigi, G. (2014, February 24). Banks feel the heat of new CBK order on bad loans.
Business Daily.
Norton, J., & Andenans, M. (2007). Emerging Financial Markets and Secured
Transactions. Kluwer Law International, London.
Padilla, A. J., & Pagano, M. (2010). Sharing Default Information as a Borrower
Discipline Device. Journal of Economics, 44, 1951-1980.
Pagano, M., & Jappelli, T. (2008). Information sharing in Credit Markets. Journal of
Finance, 43(5), 1693-1718.
Pagano, M., & Jappelli, T. (2012). Information Sharing,Lending and Defaults: Cross-
Country Evidence. Journal of banking and Finance, 26(10), 2017-2045.
Rouse, C. N. (2009). Banker’s Lending Techniques, London. Chartered Institute of
Bankers#
Risk Management Group of the Basel Committee. (1999). Principles for the Managament
of Credit Risk. Basel: Bank for International Settlements.
Sinkey, J.F. (2008). Commercial Bank Financial Management in the Financial-Services
Industry (6th ed.). New Jersey: Prentice Hall.
Obiero. (2002). The banking sector regulatory framework in Kenya Its adequacy in
reducing bank failure . Unpublished MBA project, University of Nairobi.
Ogubunka, U. M. (2007). Walking Ahead of Bank Distress:The scecrets of Safeguarding
Your Money in Banks,Lagos. Rhema Enterprises, 19-26.
Ogundina, A. (2009). The Nigerian Banking and Financial Environment.
Ibadan,Immaculate Press, 138-151.
Ogboi, C., and Unuafe, O. K. (2013). Impact of Credit Risk Management and Capital
Adequacy on the Financial Performance of Commercial Banks in Nigeria. Journal
of Emerging Issues in Economics, Finance and Banking, 701-717.
Ombaba, K. M. (2013). Assessing the Factors Contributing to Non- Performance Loans in
Kenyan Banks. European Journal of Business and Management, 155-162.
66
Rose, P. S. (2002). Commercial Bank Management. McGraw-Hill.
Shubhasis, D. (2005). Lines of credit and consumption smoothing: The choice between
credit cards and home equity lines of credit. Working Paper, 05-18.
Wanjira, L. T. (2010). The relationship between non- performing loans management
practices and financial performance of commercial banks in Kenya. unpublished
MBA project, University of Nairobi, 1-74.
67
APPENDICES
Appendix 1: Study Questionnaire
This study is a requirement for the partial fulfilment for the degree of Masters in Business
Administration (MBA). The purpose of this research is to investigate on the relationship
of credit risk management and non-performing on commercial banks in Kenya a case
study of KCB Group. Please note that any information you give will be treated with
confidentiality and at no instance will it be used for any other purpose other than for this
project. Your assistance will be highly appreciated. I look forward to your prompt
response.
SECTION A: BIO-DATA
Kindly answer all the questions by ticking in the boxes or writing in the spaces
provided.
1. Gender : Male Female
2. Age Group?
18-28 yrs
29-39 yrs
40-50 yrs
Above 50 yrs
3. What is your current Position?
Loan Officer Relationship Manager
Credit Analyst Recovery/Monitoring Officer
Credit Director Credit Manager
Other (Please Specify): ___________
4. For how long have you worked for your organization?
Less than 5 years 5-10 years
11-15 years Above 15 years
5. What is your experience in the bank credit department?
Less than 5 years 5-10 years
11-15 years Above 15 years
6. Are the determinants of nonperforming loans obvious?
Strongly Agree Agree
Disagree Strongly Disagree
68
SECTION B: PROCESS/PRACTICE OF CREDIT RISK MANAGEMENT AT
KCB
Kindly indicate the extent to which the following process of credit risk management is
applied at KCB Group. Please (√) tick appropriately on a scale of 1-5. 1-Strongly
Disagree, 2-Disagree, 3-Uncertain, 4-Agree, 5-Strongly Agree
Str
on
gly
Dis
agre
e
Dis
agre
e
Un
cert
ain
Agre
e
Str
on
gly
Agre
e
1. The bank has a well-documented Credit Risk
Management policy
1 2 3 4 5
2. The bank has a credit manual that documents and
elaborates the strategies for managing Credit
1 2 3 4 5
3. The bank has strategies for granting credits focus on
who, how and what should be done at the branches
and corporate division levels while assessing
borrowers
1 2 3 4 5
4. The bank faces intense challenges such as
government controls in managing credit risk
1 2 3 4 5
5. The bank conducts a credit risk analysis on
businesses and individuals before lending
1 2 3 4 5
6. The bank uses a credit scoring model in credit risk
assessment
1 2 3 4 5
7. The bank considers physical and financial
characteristics in credit scoring models for personal
loans?
1 2 3 4 5
8. The bank considers characteristics of the borrower,
capacity, conditions and Collateral/Security in credit
scoring for business and corporate loans
1 2 3 4 5
9. Loan appraisal and subsequent approvals are based
on borrower’s capacity, character, condition, credit
history and collateral
1 2 3 4 5
10. The banks contacts the credit bureau to assist in
decision making to lend their customers
1 2 3 5 6
69
SECTION C: EFFECTS OF NON-PERFORMING LOANS ON PERFORMANCE
OF KENYAN BANKS
Kindly indicate the extent to which the following effects of non-performing loans affect
the performance of KCB bank. Please (√) tick appropriately on a scale of 1-5. 1-Strongly
Disagree, 2-Disagree, 3-Uncertain, 4-Agree, 5-Strongly Agree
Str
on
gly
Dis
agre
e
Dis
agre
e
Un
cert
ain
Agre
e
Str
on
gly
Agre
e
1. Non-performing loans have a negative effect on
the bank’s profits through increased provisions
1 2 3 4 5
2. High levels of non-performing loans deny
banks easy access to capital markets; both Debt
and Equity.
1 2 3 4 5
3. Non-performing loans negatively affects a
bank’s lending capacity due to diminished core
capital
1 2 3 4 5
4. Non-performing loans negatively affects the
shareholder’s funds
1 2 3 4 5
5. Non-performing loans can result to insolvency
thus collapse of banks.
1 2 3 4 5
6. Non-performing negatively affect a country’s
Gross Domestic Product (GDP)
1 2 3 4 5
7. Non-performing loans leads to shortening of
loan repayment periods
1 2 3 4 5
8. Non-performing loans leads to revision upwards
of interest rates thus denial of credit.
1 2 3 4 5
9. High prevalence of non- performing loans
creates a negative signalling effect in the stock
market thus lower share prices and market
capitalisation.
1 2 3 4 5
10. High levels of non-performing loans can lead to
undercapitalization of the bank resulting to job
losses
1 2 3 4 5
70
SECTION D: MECHANISMS TO REDUCE NON PERFORMING LOANS
Please tick the extent to which you agree with the following statements on mechanisms to
reduce non-performing loans. Please (√) tick appropriately on a scale of 1-5. 1-Strongly
Disagree, 2-Disagree, 3-Uncertain, 4-Agree, 5-Strongly Agree
Str
on
gly
Dis
agre
e
Dis
agre
e
Un
cert
ain
Agre
e
Str
on
gly
Agre
e
1. Educating clients on borrowing terms and
conditions reduces the levels of non–performing
loans.
1 2 3 4 5
2. Strict system related credit performance monitoring
ensures better loan performance
1 2 3 4 5
3. Frequent restructuring of non-performing loans to
good book lowers the levels of non-performing
loans.
1 2 3 4 5
4. Enhanced follow up post migration to NPL
enhances collection and classification to good book
1 2 3 4 5
5. Adequate annual budget allocations for loan
monitoring ensures good asset quality
1 2 3 4 5
6. Collateralised loans perform better and thus
managing loan default
1 2 3 4 5
7. Strict adherence to loan on-boarding and approval
levels as per credit policy enhances loan
performance
1 2 3 4 5
8. Frequent reviews of sector limits in line with the
economy lending ensures a quality book
1 2 3 4 5
9. Internal Appraisal Credit Rating Systems assist in
reducing the levels of NPLs
1 2 3 4 5
10. Writing off debts problem debts reduces the levels
of non performing loans
1 2 3 4 5
THANK YOU FOR YOUR RESPONSE