effects of bad loans on the profitability and lending
TRANSCRIPT
EFFECTS OF BAD LOANS ON THE PROFITABILITY AND
LENDING POTENTIAL OF VILLAGE COMMUNITY BANK
(VICOBA) IN KIBAHA DISTRICT
By
Sifa Stanslaus Tollano
A Dissertation Submitted in Partial Fulfillment of the Requirement for the
Award of Degree of Masters of Business Administration in Corporate
Management (MBA-CM) of Mzumbe University
2019
i
CERTIFICATION
We, the undersigned, certify that we have read and hereby recommend for
acceptance by the Mzumbe University, a thesis entitled; “Effects of Bad Loans on
the Profitability and Lending Potential of Village Community Bank (VICOBA) in
Kibaha District”, in a partial fulfilment of the requirements for award of the degree
of Master of Business Administration in Corporate Management (MBA-CM) of
Mzumbe University
___________________________
Major Supervisor
___________________________
Internal Examiner
Accepted for the Board of Mzumbe University, Dar es Salaam Campus College
_______________________________________________________
CHAIRPERSON/DAR ES SALAAM CAMPUS COLLEGE
ii
DECLARATION
AND
COPYRIGHT
I, Sifa Stanslaus Tollano, do declare that this dissertation is my own work and that it
has not been presented and will not be submitted to any other university for a similar
or any other degree award.
Signature: ________________________
Date: ____________________________
© 2019
This dissertation is a copyright material protected under the Berne Convention, the
Copyright Act 1999 and other international and national enactments on intellectual
property. It may not be reproduced by any means in full or part, except for short
extracts in fair dealings, for research or private study, critical scholarly review or
discourse with an acknowledgement, without the written permission of Mzumbe
University, on behalf of the author.
iii
ACKNOWLEDGEMENT
Firstly, this study would not have been successfully accomplished without the help
and encouragement of many people:
Secondly, my heartfelt thanks go to the Almighty God for His mercy, kindness and
love to me throughout the whole time in my life and during the time I was
conducting this study.
As such, I am very indebted to thank my parents Mr. and Mrs. Tollano for their
parental care and warmth love. Also to my brothers Stephen, Nickson and Julius I
say thank you for your moral and material support.
My sincere and deepest felt appreciations go to my major supervisor Dr. Faisal Issa,
for his wonderful guidance, valuable contribution and patience that made it possible
for the accomplishment of this task. I have learnt a lot from you and I will continue
learning more from you while doing my PHD in future Thank you so much Sir.
iv
DEDICATION
To my late father, Mr. Stanslaus M. Tollano, who has always believed in my
weirdest abilities to be successful in the academic field, giving me plenty of friendly
encouragements and I’m so thankful that he saw the progression through to
completion and making it possible. You are gone but your belief in me has made my
passage possible. I miss you every day Dad. Rest in peace.
v
ABREVIATIONS AND ACRONYMS
AMCOS - Agriculture Marketing Co-Operative Society
AMCs - Asset Management Companies
CARE - Christian Action Research and Education
CESEE - Central and Eastern and South-Eastern Europe
FGD - Focus Group Discussion
GDP - Gross Domestic Product
MCGE - Mercy Crops Global Envision
MFI - Micro-Finance Institution
MMD - Mata Masu Dubara
NGOs - Non Government Organisations
NPA - Non-Performing Assets
NPL - Non-Performing Loans
ROA - Return on Assets
SACCOS - Saving and Credit Co-Operative Society
SEDIT - Social and Economical Development Initiatives of Tanzania
SPSS - Statistical Package for the Social Scientist
URT - United Republic of Tanzania
VICOBA - Village Community Bank
vi
ABSTRACT
Non-performing loans (NPL)/Bad loans had received major concerns from both
financial and non-financial institutions such as investors from inside and outside
Tanzania. Henceforth, this study is aimed at discovering the effect of bad loans
(NPL) on the profitability and lending potential of VICOBA in Kibaha district.
The research covered five (5) village community banks (VICOBA) in Kibaha
District. The study employed quantitative based and partly used qualitative research
techniques as the research design. In achieving answers to the research objectives the
primary data was collected through organised questionnaire, interviews and focus
group discussions (FGD). Secondary data was collected through VICOBA financial
reports in the recent six (6) years, annual reports and loan procedures, journals and
other publications. Sample size was 145 respondents that comprised of 120 loan
customers and 25 VICOBA officials. Customers were selected by using simple
random sampling technique while VICOBA officials were selected using
convenience sampling techniques.
Data analysis was done through SPSS package where correlation, multiple regression
analysis of variables in the study was prepared in the data collection analysis. The
study found out that Non-Performing Loans (NPL)/ Bad loans in the Six-year period
reviewed serious change as unexpected rise and fall of NPL value. NPL adversely
affected the financial performance of the village community banks by reducing their
operating profits, loanable funds and undermining their liquidity positions. Results
show that (44%) of management’s personnel voted for insufficient credit assessment,
borrower's dishonest, improper mechanism in monitoring activities and occurrence of
unfavourable conditions such as changes in weather conditions since some customers
are farmers. However, causes of non-performing loans related to customer operations
observed (60%) of customers proposed business collapse as the core factor and
others like moral hazards, inadequate business education, management and
entrepreneurship skills, and marketing.
vii
TABLE OF CONTENT
Pages
CERTIFICATION .................................................................................................. i DECLARATION AND COPYRIGHT ................................................................. ii
ACKNOWLEDGEMENT .................................................................................... iii DEDICATION ...................................................................................................... iv
ABREVIATIONS AND ACRONYMS .................................................................. v ABSTRACT .......................................................................................................... vi
TABLE OF CONTENT ....................................................................................... vii LIST OF FIGURES ............................................................................................... x
LIST OF FIGURES .............................................................................................. xi
CHAPTER ONE .................................................................................................... 1 INTRODUCTION.................................................................................................. 1
1.0 Background of the Study ........................................................................ 1
1.1 Bad loans or Non-Performing Loans (NPL) ........................................... 3
1.2 Problem Statement ................................................................................. 5
1.3 Objectives .............................................................................................. 6
1.3.1 General Objective .................................................................................. 6
1.3.2 Specific Objectives ................................................................................ 6
1.4 Research Question ................................................................................. 7
1.5 Justification of the Study ........................................................................ 7
1.6 Organization of the Dissertation ............................................................. 8
1.7 Limitation of the Research ..................................................................... 8
CHAPTER TWO ................................................................................................... 9
LITERATURE REVIEW ...................................................................................... 9 2.0 Introduction ........................................................................................... 9
2.1 Empirical Part ........................................................................................ 9
2.1.1 Microfinance Institutions (MFI’s) .......................................................... 9
2.1.2 Lending ............................................................................................... 10
2.1.3 Concepts of Loans ............................................................................... 10
2.1.3.1 Performing Loan .................................................................................. 11
2.1.3.2 Bad Loans/Non-Performing Loans ....................................................... 11
2.1.4 International Views on Bad Loans or NPL ........................................... 12
2.1.5 Village Community Banks (VICOBA) in the Tanzanian Context ......... 13
2.1.6 Assessment of Loan Portfolio Quality .................................................. 14
2.1.6.1 Overdue Loan Ratio ............................................................................. 14
2.1.6.2 Bad Loan/NPL Ratio ........................................................................... 14
2.1.7 Causes of Bad Loans on VICOBA ....................................................... 15
2.1.8 Loan Repayment .................................................................................. 15
2.2 Theoretical Literature........................................................................... 16
2.2.1 Asymmetric of Information Theory ...................................................... 16
2.2.2 Agency Theory .................................................................................... 16
viii
2.2.3 Stewardship Theory ............................................................................. 17
2.2.4 Mission Drifting Theory of Microfinance............................................. 17
2.2.5 Financial Acceleration Theory ............................................................. 18
2.2.6 Credit Rationing Theory ...................................................................... 18
2.2.7 Bad Management Theory ..................................................................... 19
2.3 Conceptual Framework and Research Model ....................................... 19
2.4 Hypothesis ........................................................................................... 21
CHAPTER THREE ............................................................................................. 23 METHODOLOGY .............................................................................................. 23
3.0 Introduction ......................................................................................... 23
3.1 Type of Study ...................................................................................... 23
3.2 Study Area ........................................................................................... 23
3.3 Research Design .................................................................................. 24
3.4 Variables, their Measurements and Model............................................ 24
3.4.1 Independent Variables ......................................................................... 25
3.4.2 Dependent Variables ............................................................................ 25
3.4.3 Measurement of Variables ................................................................... 25
3.4.4 Econometric Model.............................................................................. 26
3.5 Sampling Techniques ........................................................................... 26
3.5.1 Target Population ................................................................................ 26
3.5.2 Sample Size Selection .......................................................................... 27
3.6 Data Types and Sources ....................................................................... 27
3.6.1 Primary Data........................................................................................ 27
3.6.2 Secondary Data .................................................................................... 28
3.7 Data Collection Sources ....................................................................... 28
3.7.1 Questionnaire ....................................................................................... 28
3.7.2 Focus Group Discussion (FGP) ............................................................ 28
3.7.3 Interview ............................................................................................. 28
3.8 Data Analysis Method.......................................................................... 28
3.9 Reliability and Validity ........................................................................ 29
3.10 Ethical Considerations ......................................................................... 30
CHAPTER FOUR ................................................................................................ 31
DATA ANALYSIS AND DISCUSSION OF RESULTS .................................... 31 4.0 Introduction ......................................................................................... 31
4.1 Membership Criteria and Social Composition of Vicoba ...................... 31
4.2 Demographic Characteristics of Respondents ....................................... 31
4.2.1 Gender of Respondents ........................................................................ 31
4.2.1.1 Members .............................................................................................. 31
4.2.1.2 Management ........................................................................................ 32
4.2.2 Education Level of Members ............................................................... 33
4.2.3 Education Level of Management .......................................................... 34
4.2.4 Occupation .......................................................................................... 35
4.2.4.1 Occupations of Members ..................................................................... 35
4.2.4.2 Occupations of Management ................................................................ 36
ix
4.2.5 Membership Duration .......................................................................... 37
4.2.6 Financial Status of Members ................................................................ 38
4.2.7 Loan Categories Offered by VICOBA ................................................. 39
4.2.8 Popularity of VICOBA in Communities ............................................... 39
4.3 Descriptive Statistics ............................................................................ 40
4.3.1 General Trend of NPLs Ratio ............................................................... 40
4.3.1.1 Trend of NPLs Ratio for Individual Village Community Banks ........... 41
4.3.2 Factors For Bad Loans/Non-Performing Loans .................................... 42
4.3.2.1 Factors for Bad Loans/Non-Performing Loans to Members.................. 42
4.3.2.2 Factors for Bad Loans/Non-Performing Loans to Management ............ 44
4.3.3 Effects of Non-Performing Loans to VICOBA ..................................... 45
4.3.4 Person’s Correlation Coefficient for Three Variables ........................... 46
4.3.5 Correlation Outcomes .......................................................................... 47
4.3.6 Regression Analysis Outcomes ............................................................ 48
4.4 Hypothesis Test Of Impact of NPL on ROA and LP ............................ 50
4.4.1 Research Hypothesis ............................................................................ 50
4.4.2 Research Theory .................................................................................. 51
CHAPTER FIVE ................................................................................................. 52 SUMMARY, CONCLUSION AND RECOMMENDATIONS .......................... 52
5.0 Introduction ......................................................................................... 52
5.1 Summary of the Results ....................................................................... 52
5.1.1 Factors for Bad Loan Default for VICOBA .......................................... 53
5.1.2 Effect of Bad Loans on Lending Activities for the Potential and
Profitability of VICOBA ...................................................................... 53
5.2 Ways to Minimize NPL ....................................................................... 54
5.3 Conclusion ........................................................................................... 55
5.4 Recommendations................................................................................ 55
5.4.1 Management ........................................................................................ 55
5.4.2 Customers/Borrowers .......................................................................... 57
5.4.3 Regulators and Researchers ................................................................. 57
REFERENCES .................................................................................................... 58
APPENDECIES ................................................................................................... 62 Appendix 1: QUESTIONIRE FOR MANAGEMENT .................................... 62
Appendix 2: QUESTIONAIRE FOR MEMBERS ........................................... 66 Appendix 3: INTERVIEW .............................................................................. 71
x
LIST OF FIGURES
Pages
Table 3.1: Measurement of Variables ................................................................. 25
Table 3.2: Names of Five VICOBA and their Respective Management .............. 26
Table 3.3: Reliability Test .................................................................................. 29
Table 4.1: Gender of Respondents for Members ................................................. 32
Table 4.2: Gender of Respondents for Management ........................................... 33
Table 4.3: Education Level of Members ............................................................. 34
Table 4.4: Education Level of Management ....................................................... 35
Table 4.5: Occupation of Members .................................................................... 36
Table 4.6: Occupation of Management ............................................................... 36
Table 4.7: Financial Status of Respondents ........................................................ 38
Table 4.8: Distribution of Various Categories of Loan........................................ 39
Table 4.9: Popularity of Vicoba in Communities ................................................ 39
Table 4.10: NPL Statistics for Individual Community Banks for 6 Years ............. 40
Table 4.11: NPL Statistics for All Community Banks .......................................... 41
Table 4.12: Factors for Bad Loans/Non-Performing Loans to Management .......... 45
Table 4.13: Effects For Bad Loans/Non-Performing Loans to Management ......... 46
Table 4.14: Person’s Correlation Coefficient ........................................................ 47
Table 4.15: Correlation of Variables Influencing ROA ......................................... 48
Table 4.16: Regression Results on NPL vs LP ...................................................... 49
Table 4.17: Regression Results on NPL vs ROA .................................................. 50
Table 4.18: Summary of Hypothesis and Theories................................................ 51
xi
LIST OF FIGURES
Pages
Figure 2.1: Conceptual Framework ................................................................... 21
Figure 4.1: Membership Duration of Respondents in VICOBA ......................... 37
Figure 4.2: Trending NPL Status for Individual Community Banks ................... 42
Figure 4.3: Distribution of Factors for Non-Performing Loans to Members ....... 43
1
CHAPTER ONE
INTRODUCTION
This section contains background of the study, research objectives, research
questions, organisation of the study and limitation of the study.
1.0 Background of the Study
Village Community Bank (VICOBA) is one among the microfinance
programs/schemes1 designed for providing credit/loan and savings services to low
income earners who need such funds for starting and, or expanding their own
businesses. This program consists of 25-50 members or people mostly women.
Although in recent years men has also started to participate in the program as
discussed by (Kihongo, 2005).
Kihongo (2005); and Lushakuzi et al., (2017) observed this program/scheme as one
of the major system adopted by village community banks by reaching the poorer
through provision of small loans/credits and savings services aiming at improving
their livelihood. Members who obtain funds from VICOBA do the following
businesses: retail shops, food stands, vegetable stalls, tailoring businesses, crop
cultivation, and animal farming activities. Village community banks have helped
people to move from one point to another in making economic improvement, self-
employment, enhancing household income and standards of living (Katondo, 2013).
Mkombe (2005) affirms that Village Community Bank (VICOBA) structure is not
well understood to different communities rather it has been compared to Saving and
Credit Cooperative Society (SACCOS), and other programs which have not yet been
formal such as KIBATI and UPATU to deliver their services to all members.
Ngalemwa (2013) understood that Village community banks are kind of community
banks that aims at reducing poverty, starting and boosting their small businesses,
1 http://kitegacc.org/campaigns/village-community-banking-vicoba/
2
funding various expenses such as school fees for children, paying medical, water and
electrical bills. VICOBA may seem to be like other Micro-finance programs that
have the same aims; but on the other hand, it operates with different ways.
Kihongo (2005) in Nkyabonaki (2017) claims an admiration between VICOBA and
other models similar to Saving and Credit Co-operative Society (SACCOS) and
Agriculture Marketing Co-operative Societies (AMCOS) in Microfinance industry. A
slight difference is seen between them especially in interest rates charges whereby
SACCOS is charging higher than VICOBA. MFI’s are genuinely profit-oriented and
this entails that interest rate charged is ranging from 17-30% while VICOBA is
different due to their operations and charges which are not beyond their theme/aims
ranging from 5-10% such rates seem to be reasonable and well understood by the
members. MFI’s charge high interest rates to cutter for their financial and operational
obligations since they require to have good buildings that are used as offices and to
employ qualified staff who performs the day to day activities. On the other hand
VICOBA have groups which are self-made and self-managed and they don’t require
any staffs to be paid much on doing their daily duties on daily basis (Kihongo, 2005).
Maleko, Liheta, Aikaruwa, Lukas, & Sumari (2013); Muganda (2016) both stipulate
that VICOBA has a great crowd of women as major participants in the scheme, while
Sundet (2006); Sharma & Zhao (2017) demonstrate that almost ninety-five percent
(95%) of the participants are women even though nowadays men are also
participating though in small portion of not more than 15 men out of 50 members
within vicoba. Hence, the participation of women in this scheme has brought such an
enormous development in all aspects like facilitating household income,
collaborating with others and maintaining social connections in the market place as
well as gaining women empowerment within their communities (Maleko et al.,
2013).
3
In Tanzania context, according to Olme & Sköld (n.d) and Mzee wa vicoba (2012)
(as cited by Katondo, 2013) believed that VICOBA was introduced in the year of
2000 through the Jozani-Chwaka Bay Conservation Project by CARE International.
It has brought a good engagement and governance within people’s communities
since it is well organized and engagement is done through sharing of
knowledge/skills that brings about capacity building which has helped the
communities to fight against poverty. This ascertains and assures Vicoba to be the
best lending model in rural and even urban areas in African countries like Niger,
Zimbabwe, Mozambique, Uganda, Tanzania mainland, and Zanzibar (Pemba Island).
Moreover, Kitomari and Abwe (2016) insist on implementation of VICOBA in other
words called ‘Mata Masu Dubara’ (MMD) that it is an ideal programme basing on
the creativity, and withstanding constraints. It has a great effectiveness and
efficiency. MMD operation is well known and seen in the development of its
members. Vicoba management is developed from initiation of members through
improved operations of their products/services offered such as savings, lending,
community work, and social help. Savings and loans that are being provided by
VICOBA are merely reasonable and have easy returns of the poor people. Among
the successful stories of VICOBA mostly made of model implementation agencies
within the country. These models are in areas like Zanzibar Islands, Magu, Misungwi
and in Kibaha district. Several VICOBA members in Kibaha district said that: -
“VICOBA is a good thing for the poor. It helps them to improve their
ability, skills, empowering themselves towards economic and social
prosperity” (Lushakuzi et al., 2017).
1.1 Bad loans or Non-Performing Loans (NPL)
According to Mataba (2018), Bad loans are loans which need more attention because
in the recent year’s financial institutions including credit unions, banking institutions,
microfinance institutions and other non-banking institutions worry much on these
matter due to decrease in revenue and even lowering their performance in the
financial year.
4
Afolabi (2010), Bad loans/ NPL loans are facilitated by members or clients who
sense heavy burdens or circumstances that may be within their power of control and
or beyond their control thus at the end, they cannot make settlement of their debts or
repayments and even make profit.
Non- performing assets/loans are conjointly unremarkably delineating as loans and
advance in arrears for at least ninety (90) days (Guy 2011). According to Michael et
al., (2006) NPL in loan portfolio have an effect on operational potency that in flip
affects gain/profits, liquidity and economic condition position of banks. Kroszner
(2002), states that non-performing loans are closely associated with banking crises.
The occurrence of NPL triggers a vicious result on banking survival, growth and if
not managed properly can leads to banking failure/collapse.
Bad loans don't seem to be occurring every day. However, they incur in an
exceedingly different amount occasionally in a year. Bad loans undoubtedly cause
periodic fluctuation of disposition rates, periodic inflations, interest rates, and
exchange rates among lenders (Makri, Tsagkanos, & Bellas 2014). Financial
institutions are continuously deciding their performance basing on their monetary
statements particularly acknowledging balance sheets, statement of economic
position, and cash-flows. Yet, management doesn’t cross-check Return On Assets
(ROA) which shows presence of unhealthy loans that an institution holds as an
establishment. Through monetary establishments management will take charge of
matters and regain strength/power thus to maintain good financial performances
(Nkyabonaki, 2017 and Mataba, 2018)
According to Sanjeev, (2007) and Messai & Jouin (2013) bad loans/ NPL wisely
considered as bad debt which could not be replaced, not recovered, and precisely
uncertain. Balogum and Alimi (1988) clarify that there are different causes of bad
loans affecting VICOBA and other financial institutions such as delaying in time of
loan delivery, dropping profit margins, highest interest rates per se, absence of loans
in the institution, and insufficient supervision by supervisors especially loan officers.
5
Rajan & Dhal (2003) and Sanjeev (2007) discussed bad loans hinder the performance
of institutions like VICOBA because they diminish profits and lead to risks such as
credit risk and liquidity risk. These occur due to members who are not fulfilling their
obligations towards their commitment to honour the agreement. NPL tends to affect
projects which have been planned by the institutions and even bring financial
instability, poor operations and even liquidity problems (Ollotu, 2017).
1.2 Problem Statement
Many microfinance institutions like VICOBA have encountered plentiful effects of
bad loans due to operations and activity planned by them. When the amount of bad
loans is high in their financial statements then it causes chaos that results collapse of
VICOBA. Bad loans have brought many effects to institution’s procedures such as
unfriendly monetary routine and loaning activities.
Loan portfolio constitutes largest operational measures and supply of revenue in
most business banks. However, some of loans given out become non-performing
loans and adversely have an effect on money performance of business banks.
Analysis studies have shown that loan default have two main impacts on business
banks. These effects are: limitation of vicoba’s financial performance (profits) and
lending potentials. In foreign country context, this proof is acknowledged by
(Obamuyi, 2007 and Karim et al., 2010). In African nations studies are being
performed by (Appiah 2011 and Awunyo 2012) additionally provides this proof in
African nations.
Due to member’s poor collateral for securing the loan, catastrophe events especially
to farmers, poor business plans, deprive economic conditions, poor control systems,
lack of credit appraisals, poor monitoring of members and Vicoba operations, weak
credit management operations, poor adherence of credit regulations and policy
formation. All these aspects are one among many aspects that hold back both Vicoba
and their member during their day to day events. Among these traits mentioned are
inhibiting borrowers to repay a loan on time.
6
Sometimes they do not pay at all which cause NPL. This brings poor performance,
deterioration of profits and even the collapse of institutions.
A performance of Vicoba is being monitored by the flow of loans ans
deposits/savings members hold in the banks. Yet, such performance is poor when
bad loans/Non-performing loans being present. Non-performing loans ends to reduce
profit and lending potential of the Vicoba hence, non-performing loans affect directly
profitability and lending potential of the Vicoba. Although these evidences on the
effect of loan default on commercial banks prevail, it is realized that the general
contribution to academic debate on the subject is weak owing the fact that studies on
study are generally few and they base on commercial banks, Saving and Credit Co-
operative Society (SACCOS). Similarly, they provide certain evidence that there is a
need of analysing the effect of bad loans in VICOBA as part and parcel of the
Microfinance’s programme. This study therefore, assesses the effects of bad loans on
the profitability and lending potential of Village Community Bank (VICOBA) in
Kibaha District.
1.3 Objectives
1.3.1 General Objective
The general objective of this study is to examine effects of bad loans on the
profitability and lending potential of Village Community Bank (VICOBA) in Kibaha
District.
1.3.2 Specific Objectives
(i.) To determine the trend of bad loans of the VICOBA in Kibaha
district.
(ii.) To investigate the factors for bad loan default of VICOBA in Kibaha
district.
(iii.) To examine the effects of bad loans on lending activities for the
potential and profitability of VICOBA in Kibaha district
7
1.4 Research Question
(i.) What is the trend of bad loans of the VICOBA in Kibaha district?
(ii.) What are the factors for the prevalence of bad loans default in
VICOBA in Kibaha district?
(iii.) What are the effects of bad loans on lending activities for the potential
and profitability of VICOBA in Kibaha district?
1.5 Justification of the Study
The results that will be obtained from this study will go to pave manner for several
individuals particularly, within the industry to develop or adopt executable ways that
regulate the matter of growing non-performing loans and improve performance and
gain.
Secondly, the results will serve as a tool to guide credit workers in making correct
credit selections and making quality loan portfolio for their banks thus indirectly
enhancing performance of credit workers in loan appraisals.
Provision of education/seminars from financial institutions to members of Vicoba
and other banks regarding the products and services their banks offer such as: credit
and savings. On saving schemes they should understand and learn how to save first
before asking for financial assistance. On credit, members should know their
obligations and make investments on such loan, using wisely their loans to get more
return. This is considered to be a fundamental step in the overall financial system as
pointed out by (Mkombe in Ngalemwa, 2013).
This study will facilitate in adding up the overall body of data on unhealthy loans. It
will also produce awareness to the societies on VICOBA in terms of profit
maximization.
The study findings will give clients/customers understanding of the factors that lead
to unhealthy loans so as to minimize them. Academicians and researchers will also
benefit from such knowledge too.
8
1.6 Organization of the Dissertation
The entire study is convened into five chapters. Chapter one outlines introduction to
the subject matter, background, explanations on bad loans or Non-Performing Loans
(NPL) problem statement, objectives (general and specific), research questions, and
significant of the study. Chapter two centred on Literature review where it will
encompass the theoretical part used to assist the study into profound results similarly,
empirical part which contains concepts of the study that enable the reader to
understand well the study. Chapter three is built on the strategies to be used such as
research design, data collection instruments, and the analysis of data collection and
with an ending a profile of Kibaha district. Chapter three grounded on the strategies
to be used in the study such as research design, data collection instruments, and the
analysis of data collection and with an ending a profile of Kibaha district. Chapter
four focuses on the analysis and discussion of the data collected. Chapter five shares
summary of research results, conclusion and recommendations of the study.
1.7 Limitation of the Research
The key limitation from this study is the inconvenience of VICOBA and their
meeting schedule which was burdensome for going along with because most of them
have same meeting time but different locations and this made hard for researcher to
meet the goal. Inadequate and somehow lack of financial records regarding profits
and dividend obtained, poor record keeping, mismanagement of power and ignorance
of answering question was merely troublesome.
9
CHAPTER TWO
LITERATURE REVIEW
2.0 Introduction
This chapter is all about ideas, views of other researchers and theories which are
appropriate in determining the effects of bad loans on the profitability and lending
potential of the Village Community Banks (VICOBA). This helps to provide
comprehensive background underlying the analysis of bad loans in the Village
Community Banks (VICOBA).
2.1 Empirical Part
2.1.1 Microfinance Institutions (MFI’s)
OI (2009) cited in Ngalemwa (2013) envision Micro-finance intuitions (MFI) as
genuinely as a provision of broad series of financial services and products. MFI offer
credit facilities, repayment services, deposits, savings, money transfer and insurance
services to the poor and low income earners households who own micro-enterprise
and small business that cannot get financial assistance in any financial institutions
like banks. Bangko (2001) concedes with all such services and products, MFI tend to
improve and make better socio-economic conditions of the clients and society in
general. Whilst, the welfare of the people is raised and simultaneously enhanced
capital in various areas of investment is assisted (Kihongo 2005).
According to Mercy Crops Global Envision (MCGE) (2009) MFI is of great
successful story in most of the developing countries. For example, during the recent
years it has been widely recognized and well known for its impact in people’s lives
especially their socio-economic performances. As a portable, reliable and sustainable
solution for many problems such as poverty, unemployment and poor living
standards. Moreover, some people argue that it should be viewed as an essential
element in any country’s financial perspective.
10
2.1.2 Lending
Lending has been outlined by Biney (2006) as associate degree quantity of cash
provided by an investor, taken by a recipient, collectable at some future date on
specific terms and conditions that are ruled by legal contract. Ribeiro (2006) defines
loaning as a supply of cash to a person or entity with the expectation that
compensation would be created with interest either by installments or in one quantity
by a certain date. Wherever necessary an investor can defend himself, by asking the
recipient to give some collateral. Due to intense competition amongst monetary
establishments, some monetary establishments do not take collateral in order to win
purchasers to their banks.
According to Rouse (1989), loaning is genuinely allied with a degree of art rather
than science. It involves expertise and common sense too. This assertion to some
extent is true. It is through science that lenders return out with accounting
procedures, credits and risk’s analysis to assess customer’s ability to pay, regulative
framework among alternative factors. Rouse asserts that there can perpetually be
some risks that a client can be unable to repay, and it is within assessing such risk
that an investor desires to demonstrate each talent and judgment.
2.1.3 Concepts of Loans
A loan is a facility which tends to provide contractual agreement between loan
provider and borrower where the loan is provided to borrower by the consent of the
lender through granting certain amount of money to borrower which is within
prescribed amount and making repayments in either way of (bulk or instalment).
Mabvure et al., (2012) assess that in order for a loan to be provided to borrowers it
should be fixed and given on the spot. Also a loan should be covered with either
collateral security or even without it within specific time/periods. However, there are
two classes of loans as explained below: -
11
2.1.3.1 Performing Loan
Performing loans refers to a principle amount of money that is being given to the
borrower with a backup of collateral security and together with interest which will be
covered and replayed on a timely manner (Louzis, Vouldis, & Metaxas, 2012). This
means that, loans dispatched to borrowers are being replayed back. Contractual
agreement between lender and borrowers is being settled and honoured in time
without any delay. As an overdraft that can be current or termed as a performing
loan. It clearly contributes large part of profitability and quality assets portfolio of
the financial institution2. They take no more than 90 days to honour their obligations
which mean that borrowers can make early repayment of their debts.
2.1.3.2 Bad Loans/Non-Performing Loans
Bad loans are loans that are still in force. That is, they are in the hands of borrowers
and it is uncertain that those loans will be repaid and honoured as they have
stipulated earlier in the contractor note. This clearly states that contractual obligation
that borrowers have already committed themselves are not being fulfilled whether in
small portion or even as whole some. In other words, loans on which they have long
period interests to be paid, more than ninety (90) days or they are past due the
time/period agreed as stated by Alton and Hazen (2001). Even Hannie (2003) and
Alton & Hazen (2001) concluded that bad loans do not provide profits to the
institution rather it brings huge debtors amount and minimal or absence of profit.
Most of NPL’s tend to provide several effects such as economic instability, high
interest rates to be covered, dependency on high-price borrowings, insider borrowing
and the last but not least economic declining. Aballey (2009) further emphasises that
NPL cause adverse effects on the performance and operations of the lenders. There is
borrower’s inability to fulfil the agreement within the repayment schedule or ranged.
Borrowers tend to not give back loan amount (principal) and interest charged on
timely manners.
2 https://financial-dictionary.thefreedictionary.com/performing+loan
12
The amount is constituted with interest and principal which are not to be fully
recovered by the borrower or are delayed more than ninety (90) days. This brings
financial loss which will lower the profit and lead to adverse effects on the
performance of their financial institutions. Also it sometimes leads to impairment of
the institutions not encouraging the customers. This is thus considered to be bad
loans for the institution as said by (Chelagat, 2012; Awunyo-Victor, 2013).
NPLs reflects the profit of any money establishment. A decline in the quantitative
relation of Non-performing loans shows progress in the quality of both public and
non-public sector banks. A mere unit increment in the quantitative relation of non-
performing loans to total loans on the alternative hand ought to worry industrial
banks. A deterioration in gross Non-Performing Assets (NPA) to gross advances
indicates the improvement in the credit portfolios of each the sector banks, (Batra
2003). Non-performing Assets area unit threatening the stability and destruction of
bank’s profit through a loss of interest financial gain, write-off of the principal loan
quantity itself.
2.1.4 International Views on Bad Loans or NPL
Over-all angle on the effects of NPLs reveals unswerving pattern of NPL trend,
particularly, in light of the pre and post universal financial catastrophe. Evidence
from Asia directs that there was more than threefold increase in the volume of NPLs
in Indonesian banks in the period leading up to the financial crisis (Cortavarria et al
in Chimkono, Muturi, & Njeru, 2016).
Park (2003) affirm compassion during the 90’s where he provides that there were
three different methods used by Japan people in defining bad loans/NPL. They bring
views on NPL as they base on “bank’s self-valuation” and lastly during that period
they concluded that NPL can also be associated with “Financial revival laws-based
debt disclosure”.
13
Krueger and Tornell (1999) as cited in Chimkono, Muturi, and Njeru (2016)
concedes that in order to match attribute of the credit crunch in Mexico after the
1995 crisis partially to NPL. Banks and other institutions lapsed and skidded with
credits of negative real value. This reduced the capacity of the banks in providing
fresh funds for new projects ahead. This occurred in Asia, for example both Malaysia
and Singapore where had their growth and innovation been constrained by
institutions which faced the accumulation of NPLs which eroded their capital as said
by (Karim et al., 2010 in Chimkono et al., 2016).
Chimkono et al., (2016) assures occurrence of the NPL tend to make commenting on
the Central and Eastern and South-Eastern Europe (CESEE). Klein (2013) discloses
that high and rising levels of NPLs in most of the CESEE countries exerted a strong
pressure on banks’ balance sheets which is adversely effecting banks’ lending
operations. NPLs in this region increases to an average of 11 percent (at the end of
2011) from just above 3 percent in 2007. This was an impair factor, with the
feedback effects from the banking system to the economic activity undermining a
sustained recovery and posed significant vulnerabilities going forward in future
sources.
2.1.5 Village Community Banks (VICOBA) in the Tanzanian Context
This programme was assisted and established in 2002 by CARE to overcome the
circumstances and empower the poor on their daily operations towards achieving
their social and economic goals Mkombe (2005) as cited in Ngalemwa (2013). This
model is comprised by members of the groups who are the shareholders of the
community bank itself. Members are the sole customers. Each period these sole
clients have a tendency to provide certain investments of share capitals in the bank as
a regular agreed manner for a certain contribution in their savings (Kihongo 2005).
Kahongo (2005) argues that VICOBA as one among the MFI programmes which are
very stable and effective in catalysing developmental initiations. According to
Ngalemwa (2013) request that regarding MFI especially in the remote areas face
14
difficulties in accessing the financial institution services. URT (2009) as cited in
Ngalemwa (2013) states that only 0.14% of the Tanzanian populations had
participated in VICOBA programme until December 2008. This indicates that
VICOBA programme is widely spreading to the country’s regions by different
development agencies (SEDIT 2010).
2.1.6 Assessment of Loan Portfolio Quality
This assessment is merely done through assessing loan portfolio quality where by it
involves several issues; -
2.1.6.1 Overdue Loan Ratio
Overdue loans ratio has a habit of measuring proportion of the overdue loans in the
gross loans as presented in the portfolio outstanding. They are loans, bills of
exchange, and other obligations remaining unpaid past their due (or maturity) date.
This ratio be apt to a desirable ratio for declining or rising or not from new credit
facilities granted3.
2.1.6.2 Bad Loan/NPL Ratio
Bad loans ratio aggregates the standards, doubtful and losses that may be occurring
to the loans which are being offered by the lenders. Also it is referred to as high risk
and derived in relating peculiar total loan portfolio. A loan which the borrower is not
making interest payments or repaying any principal classified as non-performing by
the bank. It then becomes a bad debt depending on the local regulations of the
institutions. Routinely, banks set aside money to cover potential losses on loans
catted (loan loss provisions) and then written-off as bad debt in their income
statements (profit and loss account). In some countries, banks that have accumulated
too many NPLs are able to sell them on - at a discount - to specially established asset
management companies (AMCs) which in turn attempt to recover at least some of
the money owed4.
3 https://www.creditmanagement-tools.com/overdue-ratio-calculation-c5-r52.php 4 http://lexicon.ft.com/Term?term=non_performing-loan--NPL
15
2.1.7 Causes of Bad Loans on VICOBA
Deliberately Kwakwa (2009) observe lack of appropriate appraisal of the facility
which are provided by the loan officers. Loan default rates increase as the rate of
Gross Domestic Product (GDP) falls down. Also, decrease in local currency may
tend to affect the repayment performance of the borrowers. Balogum and Alimi
(1988) shared that there are more to those causes especially affecting the banking
sector as mentioned below:
Erroneous economic decisions: this is undertaken by people and other circumstances
such as occurrence of unfavourable conditions and unexpected price which change
on different occasions.
Other factors are Insufficiency of management practices, loan diversion and reluctant
fulfilling their contractual agreement which are done by debtors. High transaction
costs on loans, moral hazard and high interest rates on loan disbursed by the lenders
may be harmful because debtors won’t get a chance in fulfilling their obligations.
In the industrial sector causal-effects of bad loans are occurring: This shows bad
selection of borrowers, lack of feasibility study of the borrower’s history and
business. Poor collateral security, unrealistic terms, borrowers’ dishonest and
integrity and lastly; improper mechanism in monitoring activities all these are being
well observed and seen clearly.
2.1.8 Loan Repayment
Loan repayment is the process whereby financial institutions are recouping back the
loan facility that was granted to borrowers. This is one among the determinant factor
for the banks to sanction more loans. This occurs due to the fact that financial
institution tries to honour their loan obligation often for some reversible actions. It is
common that banks have a tendency of disburse loans to the public workers whom
are on the government payroll and experience monthly dedications.
16
2.2 Theoretical Literature
2.2.1 Asymmetric of Information Theory
Auronen (2003) as cited in Richard (2011) says that it is difficult to distinguish good
and bad borrowers. This results into adverse selection and moral hazard
consequences. This also tends to provide an outline in a market area/section that
possesses clear information on a specific item to be transacted (to borrower).
Auronen (2003) indicates that there are adverse problems and moral hazards on
which they have a better significance accumulation of NPL in financial institutions
(Bester 1994; Bofundi & Gobba 2003 as cited in Barongo 2013).
Kinju, Macha & Gwahula (2016) say that this occurs when one party in the
transaction relationship made in the contractual agreement between lender and
borrowers is more informed about the transaction than the other party. Thus, Mishkin
(1992) observed financially, the theory practices literature takes impacts in decision
based upon the difference that is seen when one miss’s little information about each
other.
Due to this, many lenders tend to incur uncertainty of loan repayment. They cannot
observe borrower’s character and action well enough. This brings hard decision on
assessing their credit nonetheless Ariccia (1998). Low quality borrowers lead to the
accumulation of bad loans/NPL where they decrease profitability and deprave of
capital as suggested by (Bofondi and Gobbi, 2003; Bofondi & Ropele, 2011; Marki
et al., 2014).
2.2.2 Agency Theory
According to the agency theory, agency risk ascends merely from the association
with managerial practices which makes equity to be less/minimal attractive and
mostly likely than debt financials (Myers & Majluf, 1984). Moreover, this theory
explains that most of the managers do not understand their positions in enabling
things to occur in their risk investments which are not interested by owners.
17
This goes with stewardship theory which purposively lays a foundation and puts
emphasis and beliefs that Agency theory assures a determination/strictness between
risk propensity/incidence of managers and subordinates where it focusses most on
their actions upon the alleviation of the principal risk at the experience of principal
amount.
This normally acquires the oral means owners whereby they must identify the
presence of the tension and avert subordinate’s activity which has a link with moral
hazard by monitoring managers and developing strategies that align the interest with
subordinates and their managers through opportunity action by subordinates5.
2.2.3 Stewardship Theory
Genuinely, stewardship theory is proposing that leaders should act in accordance to
their jobs’ goals and objectives with trustworthiness, stewards of the institution and
formally maintain work ethics on the basis of the collective good of the constituents
which are being made in respect of the leader’s self-centeredness (Donaldson &
David, 1991).
This theory merely indicates that orientation has to be done between managers and
subordinates or owner’s interest this symbolizes that steward manager believe more
on the pursuit of what is the best for the organization’s objective. Owners will be
taken even if such actions which will not be in steward’s immediate self-interest
(Nsobila, 2015).
2.2.4 Mission Drifting Theory of Microfinance
Mission drifting theory indorses more on mission of micro-finance institutions, that
is to provide financial services which are affordable to majority of the poor
populations around the globe. The provision of quality and affordable financial
services which entails that MFI should be providing loans at a low percentage of
interest rates.
5 https://www.investopedia.com/terms/a/agencytheory.asp
18
Hence, they lay more emphasis on the poor client whom appear to be riskier to lend
them and to those who cannot get any financial assistance from any other recognised
financial institutions like banks. This triggers suggestions which may tend to drift the
MFI’s ideal mission and vision of providing services and affordable financial
performance (Winters, 2010).
2.2.5 Financial Acceleration Theory
Largely, this theory elaborates the relationship between institution’s borrowing and
lending activities performed by the institution and how it is widely affected by small
economic tremors. It is backed up by the idea of interaction between external finance
premium’ which rises due to the unbalanced flow of information between borrowers
and lenders as economic agent’s net worth.
Bernake et al., (1999) advocate debt-financing activities to borrowers whom are
highly motivated to undertake projects which are risky and likely to have high/large
returns than projects offering lower returns. This is due to economic tremors
problems in which borrowers may not have the right kind of aptitude to borrow and
then having a probability of avoiding the repayment of their loans and external
finance matters.
2.2.6 Credit Rationing Theory
The Credit rationing scheme acknowledges that there should be an equal portion
regarding the lenders on providing interest rates and collateral/substitutes for security
for the aim of controlling the amount of credit they lend borrowers. Decision should
be made by lenders to either lend or not. This is conditional on the kind of assurance
that borrowers put a lot of effort to present them. Although, Financial institutions
should make a balance or presentable equal treatment and look at avoiding riskier
investment and chances that may arise due to fulfilling their contractual obligations.
Interest rate is merely an important factor in borrowing activities especially in
determining the ability of borrowers to pay the loan on timely manners.
19
2.2.7 Bad Management Theory
Due to immediate increase in NPL it results to an adverse selection and moral
hazard. Bad management theory entails to put more emphasis on managing,
collecting loans and close monitoring of NPL. Investing in a long run gives positive
results where there is an increase in general and operating expenses over an increase
in interest income from the loan. The higher the cost of income in monitoring,
controlling credit assessment, controlling credit portfolio the lower/weak the
management of Vicoba (Berger and De Young, 1997 cited in Rob, 2018).
Henceforth, there is an expectancy of significant relationship between NPL, and
ROA. The higher NPL is the lower ROA and LP too.
2.3 Conceptual Framework and Research Model
Diagrammatical representation of the framework (conceptual) which is related with
the study that shows factors being encountered by the bank and borrowers that lead
to bad loans/NPL are the independent variables and profitability of VICOBA and
lending potential as dependent variables.
There are several factors which tend to cause bad loans default to both VICOBA
staff and borrowers such as:
Insufficient credit assessment: This is a service which tends to determine
customer’s credit ratings (customer’s database) in a sense that staffs use certain
systems that help them in identifying and understanding the borrower whether he/she
has the ability of paying back. Sometimes the system provides a credit history and
distinctive details about the borrower as a good borrower or a bad debtor. This helps
them to gather reports on their clients. If the reports show presence of poor history
and low or no credit rating this symbolises bad borrower/defaulters.
Business collapse: Based on customer, due to business being insolvency,
bankruptcy, hindered by illegal activities, rise and fall of financial markets
investments and sometimes government bailout this may hamper the bank and bring
defaults that affect the wellbeing of the bank.
20
Change of credit allocation to former business plan: This means a system on
which financial resources are being distributed to various sectors to increase
efficiency and effectiveness. It is changed because of tough circumstances the
customer encounters for making him /her change mind-set of the business plan.
These are: location, customer preferences, market, declining or no Return on
Investment (ROI) even rise of expenses.
Change in business allocative environment: Is among the key factors that cause
bad loans default this includes: presence of poor leadership, occasional success
which are no longer there, poor progression toward goal attainment, poor project
implementation, poor or no communication and commitment and inefficient skills. It
also involves shortfalls in expertise, experience, technology and societal changes
which brings out market evolves.
Both insufficient credit assessment, business collapse, change of credit allocation to
former business plan and change in business allocative environment contribute
highly to bad loans defaults and therefore affect VICOBA through reducing
profitability and hindering lending activities for their potential clients.
21
Figure 2.1: Conceptual Framework
Independent Variables Dependent Variables
Source: Researcher’s own source, (2019).
2.4 Hypothesis
For objective 2:
H10: Insufficient credit assessment, business collapse, change of credit allocation to
former business plan and change in business allocative environment does not cause
bad loans default in VICOBA in Kibaha district
H11: Insufficient credit assessment, business collapse, change of credit allocation to
former business plan and change in business allocative environment cause bad loans
default in VICOBA in Kibaha district
Insufficient credit
assessment
Business collapse
Change of credit
allocation to former
business plan
Bad loans
default in
VICOBA
Profitability of
VICOBA
Lending
activities for
the potential
customers
Change in business
allocative environment
22
For Objective 3:
H20: The bad loans do not affect lending activities for the potential and profitability
of VICOBA in Kibaha district
H21: The bad loans do affect lending activities for the potential and profitability of
VICOBA in Kibaha district
23
CHAPTER THREE
METHODOLOGY
3.0 Introduction
This section contains sampling techniques, sizes, validity and reliability, data
collection instrument.
3.1 Type of Study
The study was conducted in Kibaha district using five (5) different VICOBA
available in the district. It was a case study for that particular area. Krishnaswami
(2005) in Barongo (2013) defines such case study as an in-depth comprehensive
study of people, social groups, episodes, processes, situation, program and much
more like community or social unity.
The majority of Kibaha district residents have moderate development. Many of them
are working in Dar-es-salaam. Others are retired personnel, nurses, doctors, teachers,
farmers, entrepreneurs or government workers. Kibaha district is considered to be a
good geographical setting. Economic activities such as fishing, agriculture activities,
livestock keeping, business activities, social interaction, sufficient geographical
setting and better infrastructure attract people to settle in this district.
3.2 Study Area
In URT (2013) found Kibaha district is one among marvellous district located in
Pwani region. It is among 6 districts in Pwani region with 706 km2 and a population
density of 182.1/km square6. Kibaha district is populated with more women than men
by 50.8% as targeted 35,694 women and 49.2% as targeted 34,515 men URT (2012).
Kibaha is a bliss district due to the fact that it is surrounded with natural wealth and
other resources such as arable land, agriculture, livestock keeping, irrigation scheme,
6 https://www.citypopulation.de/php/tanzania-admin.php?adm2id=0602
24
and industries of many varieties7. Kibaha district is connected with different ethnicity
but local tribes include the Wazaramo, Wakwere, Wamatumbi, Wandengereko and
other tribes which come from different parts of the country.
3.3 Research Design
The analysis used by this study is quantitative based and partly assisted with
qualitative analysis techniques. According to Saunders et al., (2007), these two
strategies are in term of numeric or non-numeric. That is the knowledge collected
from the field analyses each numerically and qualitatively.
Exploratory analysis approach additionally used to describe a lot of concerning the
drawback of loan defaults, particularly the result of loan default on bank’s
performance. Robson (2002) cited in Saunders et al. (2007) showed that this analysis
has as valuable findings that will provide information on what is happening in order
to request new insights, to raise queries and assess development in a new state of
affairs. Saunders et al. (2007) indicated that informative studies establish the
causative relationship between variables. For example, this approach established the
link between charge for default loans, loaning potential and profitableness of the
community bank.
Furthermore, five (5) Village Community Bank was used as a case study. The case
study approach helped to notice answers to the analysis question by focusing on
simply a single unit i.e. Five (5) vicoba in Kibaha District. A case study strategy is
principally used in beta and informative analysis (Saunders et al., 2007).
3.4 Variables, their Measurements and Model
There are two kinds of variables which are independent and dependent variables.
7 http://www.pwani.go.tz/storage/app/uploads/public/58d/7c3/486/58d7c3486de84696296462.pdf
25
3.4.1 Independent Variables
These are variables that are manipulated either by the researcher or by nature. This
shows independent of the outcome being measured that is for example; what causes
or what influences the outcome normally called ‘stimulus’, input’, or ‘predictor’
(Polit & Beck, 2010). From the study, these variables are namely as: Insufficient
credit assessment, business collapse, change of credit allocation to former business
plan and change in business allocative environment.
3.4.2 Dependent Variables
These are categories of variables that cannot stand on their own rather depend on the
occurrence of certain issues and gain effect whether it is positively or negatively
affected. Thus in this study profitability dependent variable is Lending activities for
the potential customers and ‘profitability’ that is termed as Return on Asset (ROA).
3.4.3 Measurement of Variables
Table 3.1: Measurement of Variables
VARIABLES MEASUREMENT
DEFINITION
ACRONYM EXPECTED
SIGNS
DEPENDENT VARIABLE
PROFITABILITY/ (ROA)
Net profits/assets × 100
ROA
-
LENDING POTENTIAL
Savings, deposits and other
income generated during the
period
LP
INDEPENDENT VARIABLE
BAD LOANS/NPL
Non-performing loans and
total gross loans ratio × 100
NPL
-
BUSINESS COLLAPSE CONTROL VARIABLES BC -
CHANGE OF CREDIT ALLOCATION
TO FORMER BUSINESS PLAN
CCAFBP +
CHANGE IN BUSINESS ALLOCATON
ENVIROMENT
CBAE -
INSUFFICIENT CREDIT ASSESMENT ICA +
Source: Researcher’s own source, (2019).
26
3.4.4 Econometric Model
Econometric model is a tool showing relationships of variables to be forecasted in
future. It comprises of equations seeking to develop a meaningful behaviour patterns
for the groups in economic perspective8. Based on the theoretical relationships of
such variables multiple regression mode may be developed as per objectives present
and at the end providing a developmental relationship between NPL, ROA and
Lending potential. The model is expressed as:
BAD LOANS/NPL = α + β1(BC) + β2(CCAFBP) + β3(CBAE)+β4(ICA)+e…….(i)
LP = α + β1(NPL) + e…….(ii)
ROA= α + β1(NPL) +e…….(iii)
α = constant parameter/intercept
β = coefficient of independent variables
“e” = represents the unexplained residuals or error terms
3.5 Sampling Techniques
3.5.1 Target Population
The targeted population of the study is 5 Village Community Banks (VICOBA)
which are present in the District.
Table 3.2: Names of Five VICOBA and their Respective Management
Name of VICOBA Chair -
person/
manager
Assistant
chair
person
Secretary Loan
officers/
accountants
Assistant
accountant
TOTAL
Amani 1 1 1 1 1 5
Amka ‘A’ 1 1 1 1 1 5
Faraja 1 1 1 1 1 5
Tumaini (KEC) 1 1 1 1 1 5
Ushikamano 1 1 1 1 1 5
Customers /Borrowers 40 38 40 41 43 195
TOTAL 45 43 45 46 48 227
Source: Researcher’s own source, (2019).
8 https://www.kbmanage.com/concept/econometric-forecasting-model
27
3.5.2 Sample Size Selection
The best technique to fit here will be the non-probability technique (Saunders, 2007).
There will be no certain to the members whom will be chosen as sample size. This
will be done using Slovin's formula9 which is used in statistical analysis as a tool to
determine the sample size of a population that must be taken for a specific study.
Where by it is written as;
n = N/(1+Ne^2).
In the formula;
n = the number of samples needed which is unknown,
N = total population which is 227 members in the total of 5 VICOBA and;
e = error tolerance taken 5%.
n = 227 / [1+ 227 (0.05^2)].
n = 144.8165869
n = 145 sample size, this sample size will be divided to the 5 institutions so as to
accumulate the whole population. And the end result 29 members to each vicoba.
3.6 Data Types and Sources
The researcher used primary and secondary data as sources in perusing the study.
3.6.1 Primary Data
This data used questionnaires that was distributed twenty-nine (29) to the
customers/borrowers and the management personnel of VICOBA. Also interview
(face to face) which helped to give definite expressions of the questions and provided
to them and focus group discussion the both parties so as to get more information
regarding the matter.
9 https://www.reference.com/math/slovin-s-formula-fb8e208a01cd104c
28
3.6.2 Secondary Data
This involved VICOBA financial reports in recent years, brochures, policy manuals,
newspaper, articles, loan procedures, journals, internet materials and other
publications relating to the study.
3.7 Data Collection Sources
3.7.1 Questionnaire
This consist of numbers of questions which are typed and presented to the clients and
management respectively. This is a popular technique which is being mostly used
elaborated by (Kothari, 2004).
3.7.2 Focus Group Discussion (FGP)
Saunders et al., (2007) as cited in Ngalemwa (2013) points out that Focus Group
Discussion (FGP) involves four to twelve participants depending on the interviewer’s
skills and subject matter. This enable one to study people in a more natural
conversation where one-to-one interview is done. It may depend on interview skills
and subject matter.
The discussion involved researcher, chosen one (1) member to represent their bank,
likewise to management personnel. At the end gaining a total of Ten participants (10)
Vicoba.
3.7.3 Interview
Face to face personal interviews was conducted as regards to respondents’ sample.
This helped researcher in obtaining information that was not obtained in the
questionnaires.
3.8 Data Analysis Method
The data was analysed by the statistical software called Statistical Package for The
Social Scientist (SPSS) where we can be able to understand the correlation, multiple
regression analysis through (econometric model), and descriptive analysis.
29
All these assisted in the data collection analysis. Inferences were made from the data
collection analysis. Also, content analysis was done though Focus Group Discussion
(FGD) for understanding and analysing key information obtained in the quantitative
data and making good interpretation on the existing content and internal feature of
the written text (Muganda & Muganda, 2012).
3.9 Reliability and Validity
According to Drost (2011) reliability is a major concern when it comes to
psychological test that is used to measure attributes, features and behaviour of
variables within the study findings. Therefore, this study ensures that reliability of
data collection instruments, researcher conducted pilot study to 10 members and 5
management personnel in order to test questionnaires if they are capable of collecting
and giving required information and they can be answered easily to suit and
ensemble the study of effects of bad loans on profitability and lending potential of
Village Community Banks (VICOBA) in Kibaha District. Improvements made were
used to guarantee questionnaire that are reliable for the study.
Researcher confirmed that data obtained from sources through questionnaire,
interview and Focus Group Discussion (FGD) are valid to depict what is going on
the field. To ensure validity, researcher used triangulation approach in collecting and
comparing outcome. The study conducted reliability test using Cronbach’s Alphaa
value to magistrate reliability of variable used in the study and findings were as
follows:
Table 3.3: Reliability Test
Cronbach's Alphaa Cronbach's Alpha Based on Standardized Items N of Items
.897 .759 15
Source: Researcher’s own source, (2019).
30
3.10 Ethical Considerations
Ethical considerations ensure and establishes an important communicative
relationship that can be managed and planned where risks may be minimized and
well as improved benefits. From this study researcher ensured that respondents rights
are being protected as the study is beneficial to respondent towards economic
development, information was protected and kept privacy, disclosed at all level that
they can be able to understand that they can refuse or agree to participate in informed
content. Respondents were treated fairly and equally yet no harm was being
conducted to participants ensuring privacy and anonymity, confidentiality of
information on questionnaires and interview. Based on veracity (truthfulness) of
information, justice and inclusiveness to all participants (vulnerable and whom are
not vulnerable)
31
CHAPTER FOUR
DATA ANALYSIS AND DISCUSSION OF RESULTS
4.0 Introduction
4.1 Membership Criteria and Social Composition of Vicoba
Findings revealed that there is a presence of mutual relationships and support among
members. They live nearby. Sometimes they share similar plans for certain specific
matters economically and socially. One of Vicoba members said the composition of
group does not consider religion and beliefs, tribe or ethnicity nor political
circumstances. All they need is a level of trust to each other to avoid confusion and
default on the loans they get.
4.2 Demographic Characteristics of Respondents
4.2.1 Gender of Respondents
This study used sample size of 145 respondents that was allocated from two groups
which involved 120 members and 25 managements/personnel. From both groups
composition of gender consisted of 59 males and 86 females from all 5 vicoba.
4.2.1.1 Members
Table 4.1 below, indicates the genders of members. Male formed 47 respondents that
is 39.2% and 73 female respondents formed 60.3% of the total 120 respondents. The
data illustrate that more women are engaged in vicoba than men. This is due to the
fact that vicoba was developed under a primarily privilege of its women participants
whom could plan to easily attend, shifting and shaping their schedule to attend the
regular meetings and incorporated into their daily chores/duties at home
(Nkyabonaki, 2017).
Nonetheless, the participation of men and women is barely increased due to
combined gender groups and even unfavourable economic conditions. These include:
- family units for instance; unemployment, catastrophic reasons for those whom
32
practice agriculture and poverty. This also demonstrates the importance of vicoba to
society as a positive change for men to engage in activities which were considered to
be for women only. This shows that VICOBA is important in developing socio-
economic growth and reducing poverty in society (SEDIT, 2008).
Women have a tendency of feeling secured and vested when they are allowed and
accurately accessing money. Besides, when women are given loans they make huge
effort in repaying back in definitive period or even minimal than men do. Jasson
(2014) stated that previously women were not given priority in getting individual
loans due to poor collateral security, and other conditions which were cumbersome
for them to obtain loans.
Table 4.1: Gender of Respondents for Members
Particulars Frequency Percent
Male 47 39.2
Female 73 60.8
Total 120 100.0
Source: Analysis of Field Data 2019.
4.2.1.2 Management
The management play a great role in managing affairs of the bank and members in
general. Management is comprised of 5 people in each community bank:
chairperson, secretary, treasurer/accountant, key holder and discipline leader. They
supervise and undertake responsibilities for managing shares, safe keeping keys,
credit management and maintaining responsive discipline. Table 4.2 beneath,
portrays that male respondents are 48% and the remaining 52% for females. Female
respondents are now on the edge more than men in a sense that they now try to have
tittles, responsibilities, authority in Vicoba.
33
One among the leaders stated that:
…and that is a good thing because when a woman is being given a
chance to prove herself in the community, being educated, given first
priority, termed as equal to men then she can and will do greater things
in future as for our management we prefer more women than men
because we believe that they have a wide and good judgment in
managing and monitoring affairs not only at home but in money matters
as well” Interview April, 2019.
Table 4.2: Gender of Respondents for Management
Particulars Frequency Percent
Male 12 48.0
Female 13 52.0
Total 25 100.0
Source: Analysis of Field Data 2019.
4.2.2 Education Level of Members
Education is a vital tool for developing human skills, knowledge and liberating
people from financial condition.
According to this study, 41.7% of the respondents have attained university or higher
education, 18.3% attained primary education, 22.5% attained secondary education,
and 8.3% attended non-formal education as seen in Table 4.3 underneath. This
indicates that VICOBA involve members who are educated and are generally
government workers and retired officers. Jasson (2014) asserts that various entities
with government support have acknowledged that not only men but also women and
girls need to be educated and empowered so as to eradicate economic problems,
ignorance to rights and enhancing employment to them.
34
Table 4.3: Education Level of Members
Particular Frequency Percent
Primary 22 18.3
Secondary 27 22.5
Collage institution 11 9.2
Bachelor / higher education level 50 41.7
Illiterate 10 8.3
Total 120 100.0
Source: Analysis of Field Data 2019.
According to Regnar et al., (2002) as cited in Haule (2015) there is certain required
level of education for management for the development and growth of their
institutions. That is to say, education is a tool for increasing productivity, ensuring
group supervision, overseeing money making decisions especially dividend shared,
utilizing efficient and effective resources, information and development of self-help.
4.2.3 Education Level of Management
Table 4.4 beneath portrays 20% of the respondents, have attained university or
higher education which was same as respondents who had collage education, while
24% attained primary education, 28% attained secondary education, and 8% attended
non-formal education. This shows that Vicoba is a great formal institution. Its
microfinance institution is comprised of personnel who are well educated too.
A member from one of the VICOBA groups stated that:
“We have elected leaders who are educated, having good humanitarian
skills, knowledge and well-mannered with centred of good priorities and
decision for the bank’s wellbeing to attain growth for bank itself and
members too’ Interview April, 2019.
Furthermore, she said that:
‘This ensures that, there will be no confusion and problems in decision
making, selfishness, and inequality to disrupt peace because when you
are educated you can do greater things. Interview April, 2019.
35
During focus group discussions, a man among the vicoba members described a who
can obtain or get a position as one among management team or leaders;
‘We only need someone to guide, support, make good decision, supplying
democracy, and defend us in time of need…through all that, he or she
should work hard just like president’s slogan “hapa kazi tu”’ Interview
April, 2019.
Table 4.4: Education Level of Management
Particular Frequency Percent
Primary 6 24.0
Secondary 7 28.0
Collage institutions 5 20.0
University/ higher education level 5 20.0
Non formal education 2 8.0
Total 25 100.0
Source: Analysis of Field Data 2019.
4.2.4 Occupation
4.2.4.1 Occupations of Members
The mixed composition of vicoba members demonstrates the presence of mixed
individuals such as workers from recognised institutions (formal) and unrecognised
(informal sector). For instance: tailors, petty traders, shopkeepers, housewives and
unskilled workers, government workers like teachers, nurses, agriculture officers and
security guards (Table 4.5). All individuals play an important role in socio-economic
transformation and the building up of positive vicoba spirits. Nkyabonaki (2017)
argues that most financial institutions like banks do not fulfil the needs of every
customer or individual.
36
Table 4.5: Occupation of Members
Particular Frequency Percent
Small or medium business owner 37 30.8
Farmer 9 7.5
Hair dresser 7 5.8
Housewife 11 9.2
Nurse 10 8.3
Teacher 26 21.7
Plumber 3 2.5
Seller and shopkeeper 7 5.8
Tailor 4 3.3
Unskilled worker 4 3.3
Garage worker 2 1.7
Total 120 100.0
Source: Analysis of Field Data 2019.
4.2.4.2 Occupations of Management
This entails that formal financial system does not fulfil the needs of these people
regardless their professions. This brings them together to form these groups for
helping each other to get out in socio-economic matters. Teachers, government
agencies, retired officers and others who are recognised by the government’s system
and they can be easily traced (Table 4.6).
Table 4.6: Occupation of Management
Particular Frequency Percent
Manager 5 20.0
Dept. Manager 2 8.0
Accountant 5 20.0
Assistant accountant 3 12.0
Secretary 5 20.0
Discipline master 5 20.0
Total 25 100.0
Source: Analysis of Field Data 2019.
37
4.2.5 Membership Duration
Most of the respondents showed that they have experiences in vicoba due to the fact
that they have a long duration of membership in their bank. Others participants
expressed that:
‘Many members of these vicoba are participating to more than one bank
at a time. They have different times for gathering at meetings in a week
like Wednesday and Friday or Monday and Friday depending on the
number of community banks that a person has joined. Many individuals
are present from the initial stages of the formation of the bank and the
continuation of their participation is not inclusive. This causes
destruction and loan default’ Interview April, 2019.
‘The longer the existence of vicoba in the area the more efficient and
effective it is in its operations but somehow other vicoba are not quite as
they seem because they have problems. Others cannot survive for long so
they develop others for the aim of uplifting the individuals who need
financial services’ Interview April, 2019.
Figure 4.1: Membership Duration of Respondents in VICOBA
0-4 years51%
5-10 years42%
11-15 years
7%
Membership duration in years
Source: Field data 2019.
38
4.2.6 Financial Status of Members
The evidence reveals that members of the Vicoba seek for financial services in order
to improve their daily socio-economical living standards. Respondents say that they
have a good life due to their financial stability at around 25.8% while others at
around 51.7%. Only 20% considered themselves to have ordinary economic status
while the rest 2.5% Said that they had bad financial status. Those individuals whose
incomes may fluctuate from time to time have bad financial status as shown by these
respondents in the discussion:
‘I have been a member of this vicoba for six years now. This bank has
done a lot to me and my family. I pay school fees for three kids, buying
food, operate my business and up to now I have three different businesses
that I own. I thank vicoba for all such development and my husband for
the support’ Interview April, 2019.
‘I am a widow and retired civil servant. Vicoba has brought me great
things and companionship without forgetting financial support for my
grandchildren’s fees, uniforms and other school accessories; improved
my business investments which were in bad conditions at that time but
after getting loans from them I have been more sure of financial growth’
Interview April, 2019.
The argument shows that Vicoba is one among important programmes which helps
community members in enhancing their lives and through such testimonials it proves
that Vicoba are important towards economic and social reliefs.
Table 4.7: Financial Status of Respondents
Particular Frequency Percent
Good 62 51.7
Ordinary 24 20.0
Very good 31 25.8
Bad 3 2.5
Total 120 100.0
Source: Analysis of Field Data 2019.
39
4.2.7 Loan Categories Offered by VICOBA
These banks obviously provide varieties of loans to their clients such as: salary loans,
commercial loans. The members and management have managed to deliberately
measure economic status of every member and provided a solution to their problem
by providing new loan product which will go according to their needs. Members
were applying for loan for their own purpose and preferred the new product.
Table 4.8 beneath display the 52% of respondents they choose loan depending on
their need. Others choose commercial loans about 40% and 8% on salary loans.
Table 4.8: Distribution of Various Categories of Loan
Particular Frequency Percent
Salary loans 2 8.0
Commercial loans 10 40.0
Depending on member's need 13 52.0
Total 25 100.0
Source: Analysis of Field Data 2019.
4.2.8 Popularity of VICOBA in Communities
The importance of vicoba is generally widespread. The results indicate that vicoba is
more popular in their communities. About 62.5% of the respondents are aware of
such community banks. On the other hand, only 37.5% said that vicoba was not
popular. Poor and negative information is being spread to them regarding vicoba.
Table 4.9: Popularity of Vicoba in Communities
Particular Frequency Percent
Yes 75 62.5
No 45 37.5
Total 120 100.0
Source: Analysis of Field Data 2019.
40
4.3 Descriptive Statistics
4.3.1 General Trend of NPLs Ratio
Table 4.10 below, shows NPL trend of individual community banks. Amani
VICOBA have uppermost NPL of 17.27% while Faraja VICOBA obtained the
lowest NPL of 10.4%. This means that Amani VICOBA should take certain measure
to reduce Non-performing loans (NPL) level, especially the credit management so as
to minimize bad loans. On the other hand, Faraja VICOBA also needs to take control
of its Non-performing loans (NPL) level to maintain and lessen the level of bad loans
on their vicoba members.
Table 4.10: NPL Statistics for Individual Community Banks for 6 Years
Community Banks
Amka A Amani TumainiKEC Faraja Ushikamano
NPL
Mean 12.05 17.27 13.5 10.4 11.2
Max 15.03 20.87 20.82 15.7 19.7
Min 7.2 6.23 7.02 6.12 5.1
Std. Dev. 3.16 5 5.3 3.7 5.2
Source: Analysis of Field Data 2019.
The results above display maximum Non-performing loans (NPL) of 15.35% while
the minimum Non-performing loans (NPL) for all five VICOBA for the period of
2013 to 2018 as 5.28%. The standard deviation of 3.73 which leaves a concise
answer that such five VICOBA’s values do not have to deviate knowingly from the
general mean. Hence results are higher than financial institutions’ average of 3%.
This demonstrates that something should be done by Vicoba so as to remain gainful
and reasonable (Table 4.11).
41
Table 4.11: NPL Statistics for All Community Banks
Particular NPL
Mean 10.76
Median 9.92
Maximum 15.35
Minimum 5.28
Std. Dev. 3.73
Source: Analysis of Field Data 2019.
4.3.1.1 Trend of NPLs Ratio for Individual Village Community Banks
Generally, from the results NPL trend is increasing over the period especially 2014
to 2015 as seen in Figure 4.2 below. NPL increased from 7.2% in 2013 and falls into
8.1% in 2015 then goes rapid increase up to 13.7%, 15.03% in 2016 and 2017 which
maybe resulted from financial crisis that affected performance of member’s
businesses this is for Amka A. Amani started-off with more NPL ranging to 20.87%
in 2013 which was severely going to collapse but in the following year it drops hasty
to 6.23% and ongoing trend increased and remain at 12.83% and 13.05% over 2015-
16 and make up a fall 8.2% and a rise up 12.4% of NPL during 2018.
Tumaini KEC’s NPL shoots from 0 to 11.42% and increase speedily to 17.5%
(2014), 20% (2015), and 20.82% (2016) and thereafter drops to 7.02% in 2017 and
rise to 14.71% in 2018. Faraja in December 2013 showed result of 9.4% as a balance
and an increase towards 10.07% in 2014 with a small fall of 6.8% in 2015 and a
briskly increase to 13.28% (2016), 15.7% (2017) and a drop to 6.12% in 2018. In
Ushikamano, increase from 11% (2013) to 14.3% (2014) and a fast fall of NPL to
5.1% in 2015 and experienced a prompt increase in 2016, 2017 and 2018 with
18.03%, 12.8% and 19.7% respectively.
42
Figure 4.2: Trending NPL Status for Individual Community Banks
Source: Generated from the Reports and Summary of Rural Banks 2013-2018.
4.3.2 Factors For Bad Loans/Non-Performing Loans
Despite the efforts made by the management of the vicoba to reduce loan defaults,
the situation is still persisting and somehow increases from time to time. In order to
achieve their goals management’s opinions and objectives needs to be settled and
sought out.
4.3.2.1 Factors for Bad Loans/Non-Performing Loans to Members
The response presented in Figure 4.3 below shows that majority of members (60%)
believe that business collapse is the core factor seen by members in their banks. It
causes threats towards their goals.
Many respondents Also majority of them explained that businesses fail because of
irresponsiveness to economic changes, poor implementation of the business plan,
lack of accuracy in business operations. Short and long term plans are crucial on how
business will be performed. There has to be measurable goals. So as to avoid damage
in the business progress.
43
Figure 4.3: Distribution of Factors for Non-Performing Loans to Members
Source: Analysis of Field data 2019.
Dr. Graeme Edwards (n.d) who was a scholar shared views regarding facts for failure
of businesses:
“It’s not the plan that is important, it’s the planning”.
This means that bad management of loans make the members fail to understand or be
aware of the situation of losing and collapsing until it is too late.
One among the treasurer from the vicoba commented that:
“There is business failure because of lack of good leadership” Interview,
23 March, 2019.
-During the session with members one among loan borrowers said this:
“My business failed due to poor implementation. Most of money from the
loan caters for any family up-keep: fees, transport, rent, food. This
causes failure in my loans repayment” Interview 23 March, 2019.
44
“My business was located along the Morogoro road. Demolishing of our
sites affected and forced us towards making failures in generating daily
income of Tshs. 180,000/- now” Interview 23 March, 2019.
The argument shows an occurrence of economic and infrastructure reforms
occurred recently have discouraged many areas and affected a lot of people.
Thus persona efforts are being highly needed for the improvement of person’s
lives. Thus Vicoba is one among choices that they saw to get economic and
social reliefs.
4.3.2.2 Factors for Bad Loans/Non-Performing Loans to Management
About 44% of management’s personnel respondents said Insufficient credit
assessment, borrower's dishonest, improper mechanism in monitoring activities and
occurrence of unfavourable conditions are the causes for bad loans. High loans
transaction costs, moral hazard, high interest rates on loan disbursed, and business
failure rated 24% while others rated 20% and 12% for the other members in the
management. (Table 4.12).
Apparently insufficient credit, dishonesty, and other factors tend to provide an alert
that the business might not be able to continue. Poor or lack of fulfilment of financial
commitments such as loans from vicoba and other financial institutions jeopardize
the day to day operations of community banks. Nonetheless, high loan transaction
costs, moral hazards and business failure also bring down the repayment of loans in
time. This is due to family problems such as: conflicts, poor trainings.
According to Berger and De Young (1997) as cited in Abaidooo (2015) weak
management is also a cause for loan default. It is in their power to determine whom
to give loan to and whom not to. Rouse (1989) also added that due to factors such as
poor judgement, indecisive, and lack of proper management and interpersonal skills
led towards defaults. Nonetheless, Balogun and Alimi (1988) acknowledges
contribution made by Ahmad (1997); Bloem and Gorter (2001).
45
They and advocate that shortage of funds to form-up loans for borrowers, high rates
for the loans offered, government intervention through credit programmes offer are
causes for default too. Thomas (2000) cited in Abaidooo (2015); Akinwumi and
Ajayi (1990) and Fofack (2005) continued saying that due to family expenses being
high, economic circumstances and poor education. Loan defaults thus occurs.
Table 4.12: Factors for Bad Loans/Non-Performing Loans to Management
Particular Frequency Percent
Bad selection of borrowers, lack of feasibility study of the
borrower's history and business, poor collateral security and
unrealistic terms.
3 12.0
Insufficient credit assessment, borrower's dishonest, improper
mechanism in monitoring activities and occurrence of
unfavourable conditions.
11 44.0
Unexpected priced which changed due to different occasions,
insufficient of management practices, loan diversion and
reluctant fulfilling their contractual agreement.
5 20.0
High loans transaction cost on loan, moral hazard and high
interest rates on loan disbursed, business failure.
6 24.0
Total 25 100.0
Source: Analysis of field data 2019
4.3.3 Effects of Non-Performing Loans to VICOBA
During the focus discussion session chairperson among community banks said that:
‘Many borrowers have been dreaming of being successful in their
businesses overnight thus they join more than one VICOBA or multiple of
them. At the end they fail to repay back and endure to wandering to other
VICOBA dwellings to avoid such effects’
Karim, Chan and Hassan (2010) argue that increase of NPL lead to a decrease of
financial growth for vicoba. Vicoba need funds to coop with daily operations. Such
funds are being distributed to borrowers to get returns but when borrowers default
then financial growth is being stagnant.
46
Vicoba need income resources that will help them to sustain and perform well in
their day to day operations if not then they will experience shortfall in financial
success.
Reducing vicoba’s lending potential: This means that from the idea that vicoba needs
to generate income from repaid loan amount with interest so as to have an audacity
of making more profits and lending to other borrower who need financial support.
When there is no income generated from the loans disbursed to borrowers
financially, vicoba start to collapse. Their lending capacity lessens to minimal points
finally that they cannot even support themselves (Karim et al., 2010).
Thus all researchers have contributed their views and hence many respondents opt
for Misunderstanding and confusion; bad image of the bank by 46.7% and followed
by Mismanagement of funds and seize, auctioning all assets owned by clients to
cover loan amount covered up with 42.5% of the respondents while the rest was
covered by Unstable operations and mistrust between bank and clients by 10.8% as
seen in Table 4.13 beneath:
Table 4.13: Effects For Bad Loans/Non-Performing Loans to Management
Particular Frequency Percent
Misunderstanding and confusion; bad image of the bank 56 46.7
Unstable operations and mistrust between bank and clients 13 10.8
Mismanagement of funds and seize, auctioning all assets
owned by clients to cover loan amount
51 42.5
Total 120 100.0
Source: analysis of field data 2019.
4.3.4 Person’s Correlation Coefficient for Three Variables
Person’s correlation analysis was calculated to investigate significant correlation
which was present amongst variables presented in Table 4.14. Results shows that
there is a significant negative relationship between NPL/bad loans and lending
potential.
47
This insures that an increase in NPL lead to decrease in amounts of loan to be
disbursed to members/to be offered by the VICOBA. Also, there is a positive
relationship between ROA and LP. This is said to be insignificant.
Table 4.14: Person’s Correlation Coefficient
Particular LP NPL ROA
LP Correlation
Significance (2-tailed)
1
NPL Correlation
Significance (2-tailed)
-.631
.002
1
ROA Correlation
Significance (2-tailed)
.280
.008
-.256
.005
1
N - 120 120 120
Correlation is significant at the level of 0.01 (2-tailed test)
Source: analysis of field data 2019.
4.3.5 Correlation Outcomes
Person’s correlation was calculated. It showed significant correlation which was
present amongst NPL (Non-Performing Loans); BC (Business Collapse), CCAFBP
(Change of Credit Allocation to Former Business Plan); CBAE (Change in Business
Allocative Environment) and ICA (Insufficient credit assessment). Findings showed
NPL, BC, ICA, CCAFBP and CBAE are substantially related with ROA, while LP is
not correlated with ROA. The matrix shows independent and dependent variables
where portrays NPL, BC, ICA, CCAFBP, and CBAE as negative momentous
correlated with ROA. Such results expose LP have obtained positive figure although
it is insignificantly correlated with ROA as in Table 4.15 below.
48
Table 4.15: Correlation of Variables Influencing ROA
ROA NPL LP BC CCAFBP CBAE ICA
ROA 1
NPL -0.6319 1
LP 0.2803 -0.562 1
BC -0.0621 -0.035 0.072 1
CCAFBP -0.384 -0.131 0.165 0.154 1
CBAE -0.044 -0.044 0.032 -0.045 0.390 1
ICA -0.081 -0.081 0.227 0.006 0.371 0.593 1
Source: Researcher’s Own Construction Using Village Community Banks Data,
2019; Significant at 5% Level.
4.3.6 Regression Analysis Outcomes
NPL has a substantial negative effect on the lending potential (LP) of all five vicoba
at (β=-0.561, t= -3.793, P≤0.05). This implies that NPL is inversely affected by
lending potential which means, suppose 1% of NPL increases this leads to 0.561%
decrease in funds in the vicoba. This is likely to be comparable results also obtained
from correlation field. The R-square value of 0.318 this denotes that 31.8% of
variables in lending potential of vicoba is generally expressed by NPL.
In other words, a negative and statistically insignificant figure indicates that a rise in
NPL is frankly related with a decrease in the ability of giving loans to borrowers
(Lending potential) of certain bank. As a result, this does not have explanatory power
over the bank’s profitability levels. This is due to the economic activities and
business that the borrower holds and operates which may play a role and may be
associated with a low rate of defaults as seen in Table 4.16 below.
49
Table 4.16: Regression Results on NPL vs LP
Variables Coefficients Std. Error t-statistics Prob.
C
NPL
0.525
-0.561
0.071
0.148
7.419
-3.793
0.0000
0.003
R-squared 0.318
Adjusted R-Squared 0.312
F-statistics 5.504
Prob (F-statistics) 0.024
Dependent variable: LP (Lending Potential)
The reason behind this relationship is customer default on interest and principal
payments. Both of these affect VICOBA’s financial statements. This cause a
decrease of asset base of the bank. The principal loan is being written off as expenses
because they are not sure whether those loans will be repaid back or not. All these
reduce profits of the bank. These findings support information of asymmetry theory
and bad management hypothesis that argue; an increase in NPL results in an adverse
selection which is merely linked with management inability to maintain and control
operations efficiency that is applicable in log run and this decreases profitability.
This supports hypothesis that states: Bad loans do affect lending activities for the
potential and profitability of VICOBA which means the higher the NPL the lower the
ROA (Kithinji (2010) and Kagri, 2011).
Albeit the results of NPL with LP are inversely, to get outcomes for the effects of
NPL into profitability (ROA); NPL is treated as proxy for independent variable and
ROA as dependent variable. A negative but insignificant effect on the ROA (β=-
0.6319, t= -2.742, P≥0.05); The R-square value of 0.066 this denotes that 6.6% of
variables in lending is not potential for these vicoba as detailed by NPL. It is
observed that F-statistics (2.261) is not significant at 5 percent confidence interval
(P=0.083≥0.05) which means that this model will not provide meaningful inferences
as seen in Table 4.17 below.
50
Table 4.17: Regression Results on NPL vs ROA
Variables Coefficients Std. Error t-statistics Prob.
C
NPL
0.525
-0.6319
0.071
0.148
7.419
-2.742
0.0000
0.453
R-squared 0.066
Adjusted R-Squared 0.058
F-statistics 2.261
Prob (F-statistics) 0.083
Dependent variable: ROA (Return on Assets)
4.4 Hypothesis Test Of Impact of NPL on ROA and LP
4.4.1 Research Hypothesis
The following are the results of hypothesis seen below:
It is true that insufficient credit assessment, business collapse, change of credit
allocation to former business plan and change in business allocative environment are
the core factors causing bad loans default therefore (Figure 4.3 Ibid);
H11: Insufficient credit assessment, business collapse, change of
credit allocation to former business plan and change in business
allocative environment cause bad loans default in VICOBA in Kibaha
district
It is seen through regression analysis results that bad loans (NPL) affect lending
potential negatively and statistically insignificant indicate that a rise in NPL is
frankly related with a decrease in ability of giving loans to borrowers (Lending
potential) (Table 4.16 Ibid). Similarly, bad loans (NPL) have a negative influence but
insignificant effect on ROA (Table 17 Ibid). Thus this is to say that; bad loans do
affect both ROA and Lending Potential in a negative way but significant to LP and
insignificant towards ROA.
H22: The bad loans do affect lending activities for the potential and
profitability of VICOBA in Kibaha district
Objective 2
Objective 3
51
4.4.2 Research Theory
Table 4.18: Summary of Hypothesis and Theories
Hypothesis
number
Hypothesis/theory Hypothesis
sign
Actual sign
of result
Statistical
significance
Conclusion
(hypothesis/theory)
1 Asymmetric of
information theory
- - significant Supported
2 Agency theory - - significant Supported
3 Stewardship theory - - significant Supported
4 Mission drifting
theory of microfinance
+ + insignificant Not supported
5 Credit rationing theory + + insignificant Not supported
6 Financial acceleration
theory
+ + insignificant Not supported
7 Bad management
theory
- - significant Supported
Source: Analysis of field data 2019.
52
CHAPTER FIVE
SUMMARY, CONCLUSION AND RECOMMENDATIONS
5.0 Introduction
This chapter provides a summary of the main findings obtained from the analysis a
general conclusion of the study and recommendations.
5.1 Summary of the Results
The study was conducted to find the effects of bad loan on the profitability and
lending potential of Village Community Bank (VICOBA) in Kibaha District. The
samples include selected five VICOBA in the area. Banks selected consist of Amka
‘A’, Amani, Tumaini-KEC, Faraja, and Ushikamano. Three objectives were used in
the survey. The trend of bad loans (2013-2018) of VICOBA; investigating factors for
bad loan default of such VICOBA and inspecting effect of bad loans on lending
activities for the potential and profitability of VICOBA in Kibaha district. All these
were employed for the purpose of acknowledge findings.
From the results it has been seen that these five community banks are facing a series
of NPL (bad debts). Vicoba have to step up and make improvements on their bad
loans situation. The occurrence of high NPL means that VICOBA will be forced to
write off some of their loans as bad debts resulting to deduction of profits.
Hitherto, a high rate of NPL constantly means that these community banks will not
have the capacity of lending more loans to members. This will destroy the
profitability sane since they rely mostly on interest income to regenerate profits of
their own and meet their day-to-day tasks. This means that there is a need for Vicoba
to take a step towards improving their status in loan since results are showing there is
an implications of profits for the banks. They need to maintain low levels of bad
loans so that profits can be elevated to comprehend with lending potential factors.
53
Rapid increase in NPL may also result from negligence in close loan monitoring and
ineffective credit appraisals. For Vicoba to overcome these catastrophes; they have to
regularly maintain clear monitoring of their activities done by borrowers, improving
credit recovery rates and make a clear search of information regarding borrowers
through credit scoring.
This study revealed that VICOBA had scarce credit assessment, borrower's
dishonest, improper mechanism in observation activities and incidence of
unfavourable conditions. Ahmad (1997) discovered that dangerous loans are a true
drawback in banking sector. Negligence in observation of borrowers could bring
distress towards the economic conditions of the banks.
5.1.1 Factors for Bad Loan Default for VICOBA
About (44%) of respondents concisely said there is insufficient credit assessment as a
major factor bad loans. Other factors include: Borrower's dishonest, borrower’s
dishonest, and Improper mechanism in monitoring activities.
5.1.2 Effect of Bad Loans on Lending Activities for the Potential and
Profitability of VICOBA
NPL have obtained significant negative effects under lending potential to banks. This
implies that a mere increase of percentage of NPL draws a decrease in the amount of
funds that are available for giving credit to borrowers expressed by Appia (2011) and
Nawaz et al., (2012). Yet is being revealed that NPL have a negative but insignificant
effects on ROA.
Reducing vicoba’s lending potential: this means from the idea that vicoba needs to
generate income from repaid loan amount with interest so as to have an audacity of
making more profits and lending to other borrower who need financial support.
When there is no income generated from loans disbursed to borrowers financially,
vicoba start to collapse and lending capacity is being lessen to minimal point that
they cannot even support themselves.
54
An increase of NPL lead to a decrease of financial growth for vicoba. As the fact that
management need funds to coop with daily operations and such funds are being
distributed to borrowers to get returns but when borrowers default then financial
growth is being stagnant.
5.2 Ways to Minimize NPL
Acquisition of collateral security: this will reduce bad loans. Loan given to customer
should be secured by collateral with the capacity to recover their loan in case of
default. In addition to that, pledged securities should be covered by insurance to
secure them against fire, flood and all associated risks during credit period.
Introducing credit life insurance: this will be helpful to cover the loan when defaulter
will not be able to for example; death of a borrower and a total disability.
Developing appropriate credit systems: through diversification of loans, control
systems and detection of bad borrowers this will reduce NPL level.
Use of methodologies like CAMPARI and 6 Cs that are being practiced to borrower
to see if he/she is trustworthy or even worthy of getting that loan. Thus through
testing them this will filter good from bad borrowers hence reducing bad loans.
Close monitoring customer’s and vicoba operations: it will be effective when vicoba
will make sure that their clients has good education regarding loans and even other
products offered, customer being monitored frequently, giving advice during
monitoring session so that when they notice any sign of default then they will make
appropriate measures.
Reducing moral hazard and its consequences. Developing credit risk management
that will help vicoba to reduce their credit risks but also other risk when they
introduce risk management.
55
5.3 Conclusion
Bad loans/NPL are one among the problems that any financial and even non-
financial institution experience, this leads to stagnation and banks failure. NPL tends
to reduce profitability of the banks. These rural banks have been unable to remain
reasonable in the turbulent financial section.
There has been a firm change over the years but more likely the results presented say
in this study there has been rise and fall of NPL in those six (6) years. NPL have
negative significance on lending potential. Similarly, NPL have a negative impact on
profitability of the banks. The study gives an open discussion on causes of bad loans
within the banks. These involves: insufficient credit assessment, borrower’s
dishonest, and improper mechanism in monitoring activities. Effects of NPL to
Vicoba were mentioned. Others were: misunderstanding and confusion; bad image of
the bank, mismanagement of funds as a result Vicoba tend to seize/auctioning all
assets owned by clients which was pledged as collateral to cover loan amount.
5.4 Recommendations
This sub-section provides the recommendations basing on analysis:
5.4.1 Management
Effective credit monitoring team: clear monitoring on a day to day basis activities of
borrower is highly needed. The team will be responsible of developing credit systems
that helps to distinguish bad and good borrowers through computerising systems.
Nonetheless, they should have an effective recovery strategy which will back-up the
financial status of the banks.
The management will have to take responsibility using modern technology: Credit
assessment systems is used by financial institutions like commercial banks to get
borrower’s information. Asymmetric of information theory it demonstrates how
adverse problems. and moral hazard on which they have a better significance
accumulation of NPL in financial.
56
Reducing confusion on good and bad borrowers caused by borrower's dishonest:
Dishonesty occurs when personal characters affect VICOBA’s situation. VICOBA
as an institution accompanied with varieties of human beings they need to learn to
live with each other: yet learn for the best using models such as 6Cs and CAMPARI.
Education to internal customers: Vicoba need to be updated with recent systems and
information. Likewise training customers in relevant fields to enhance their skills and
capacity so that they can be serve borrower’s according to their needs in appreciable
level.
Reducing the NPL rate, ensuring effective and efficient credit systems have to be
reviewed. Credit systems like credit worthiness, building commitment faith to
borrowers, employing cost efficient mechanisms, reducing information gap towards
managing loans to reduce such NPL rate need to be considered too.
Closer monitoring of VICOBA’s operations: This should be done by the registrar and
team or the government’s directory responsible for overlooking their daily
operations. Also, there should be efficiency ratios, liquidity ratios and checking on
capital adequacy for understanding the general vicoba status/trend and managing the
costs and incomes (capital positon) of VICOBA. This will help banks to initiate early
warnings and weaklings for the betterment of the bank and the reduction of NPL.
Securing customer’s information during credit assessment. This will help Vicoba to
reduce the occurrence of information asymmetry.
Introduce credit life insurance: NPL also is contributed by death and total disability
of members. It is very unfortunate that most of VICOBA do not insure their
customers with credit life Insurance hence lose money when death/total disability
occurs. I therefor advice VICOBA to introduce credit life insurance for reducing
NPL.
57
5.4.2 Customers/Borrowers
Education: this is another endorsement for both borrowers and internal customers. To
borrowers they should understand the audacity of loans provided by bank. Also,
giving education continuously has to be practiced and not by the period of getting
loan. Nonetheless, how to operate their businesses and career to inhibit their debt
from increasing.
Close monitoring of customer’s operation on daily, weekly and bi-weekly periods.
This will help customer to be more keen in performing his/her business. Getting
immediate assistance during such monitoring period which will benefit for both
parties customer and Vicoba.
5.4.3 Regulators and Researchers
Regulators should watchfully monitor Vicoba operations especially in their
computations regarding efficiency ratios, liquidity ratios and capital adequacy.
Giving advice on the regulations, policy practice and effective monitoring of credit
management in Vicoba.
Future researchers should make effort on analysis of bad loans/NPL. Accompanying
more studies on NPL situations not only in Vicoba but also in other Micro-finance
institution and financial institutions in rural and urban areas. Since this study abides
on effects of bad loans on profitability and lending potential of Vicoba, researchers
should carryout comprehensive study on bad loans to benefit others in their further
studies.
58
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APPENDECIES
Appendix 1: QUESTIONIRE FOR MANAGEMENT
The questionnaire is meant to collect data for academic purposes only. All responses
shall be entrusted and treated strictly very confidential. Your response to the
following questionnaire would be highly cherished.
District __________ Ward ____________ Village __________
Institution_________________ Date ________________
PART ONE: GENERAL INFORMATION
Please put a tick mark in the box corresponding to the correct answer against each
question according to your option below and fill in the space provided.
1. Sex
(a) Male
(b) Female
2. Education level
(a) Primary
(b) Secondary
(c) Certificate
(d) Diploma
(e) Bachelor
3. Occupation
(a) Manager
(b) Dept. Manager
(c) Accountant
(d) Assistant Accountant
(e) Secretary
(f) Discipline master
63
4. Work experience or membership in years.
0 – 4 5 – 10 11 – 15 16 – above
PART TWO: QUESTION RELATED TO THE STUDY.
5. What categories of loan facilities are being offered in your bank?
(a) Managed loans
(b) Salary loans
(c) Commercial loans
(d) Funeral loans
(e) Overdraft
(f) Others…………………………………………………………….......
6. What are the causes of bad loans in the VICOBA?
(a) Bad selection of borrowers, Lack of feasibility study of the borrower’s
history and business, Poor collateral security and Unrealistic terms
(b) Insufficient credit assessment, Borrowers’ dishonest, Improper
mechanism in monitoring activities and Occurrence of unfavourable
conditions
(c) Unexpected priced which changed due to different occasions,
Insufficient of management practices, Loan diversion, Reluctant
fulfilling their contractual agreement
(d) High transaction costs on loans, Moral hazards and high interest rates
on loan disbursed, Business failure
7. What are the effects of bad loans in lending activities of VICOBA?
(a) Risk management and Declining of Portfolio Asset Quality
(b) Poor screening of borrowers and Stagnation of loan performances
(c) Reducing of profit and Humiliation of the bank
(d) Poor performance financially and Declining of its operations
64
8. What kind of documents that are normally requested before a loan is
disbursed a client?
…………………………………………………………………………………
…………………………………………………………………………………
9. What is the range of a normal loan duration facility?
(a) 6 months
(b) 12 months
(c) 24 months
(d) Other……………………………………………………………………
10. How does your bank rank a loan facility to be bad loans/Non-performing
loans?
(a) 6 months and above
(b) 12 months and above
(c) 24 months and above
(d) Others…………………………………………………………………
11. Have bad loans affected your VICOBA operation’s profitability?
(a) Yes
(b) No
(c) Give other details if any;
…………………………………………………………………………
…………………………………………………………………………
12. Have bad loans affected your VICOBA in lending activities?
(a) Yes
(b) No
(c) Give other details if any;
…………………………………………………………………………
…………………………………………………………………………
65
13. In your opinion, which of the following factors causes NPL in your bank?
(a) Ineffectiveness in loan monitoring
(b) Delay in recovery
(c) Diversion of loans
(d) Unwillingness to repay loans
Others; …………………………………………………………………
…………………………………………………………………………
14. What problems are associated with loan recovery in your bank?
…………………………………………………………………………………
…………………………………………………………………………………
15. Do you think non-compliance with credit policy of the bank accounts for the
bad loans in the bank?
(a) Yes
(b) No
If yes, which are the following accounts for that?
(a) Customer pressure
(b) Management pressure
(c) Board pressure
(d) All the above
(e) If Others, please specify
…………………………………………………………………………
…………………………………………………………………………
…………………………………………………………………………
66
Appendix 2: QUESTIONAIRE FOR MEMBERS
The questionnaire is meant to collect data for academic purposes only. All responses
shall be entrusted and treated strictly very confidential. Your response to the
following questionnaire would be highly cherished.
District __________ Ward ____________ Village __________
Institution_________________ Date ________________
PART ONE: GENERAL INFORMATION
Please put a tick mark in the box corresponding to the correct answer of your choice
against each question according to your option below and fill in the space provided.
1. Sex
(a) Male
(b) Female
2. Education level
(a) Primary
(b) Secondary
(c) Certificate
(d) Diploma
(e) Bachelor
(f) Others……………………………….………………………………….
3. Occupation……………………………………………………………………
4. Duration of membership in years.
0 – 4 5 – 10 11 – 15 17 – above
67
5. Financial status
(a) Good
(b) Ordinary
(c) Very good
(d) Bad
PART TWO: QUESTION RELATED TO THE STUDY.
1. Is VICOBA popular in your area?
(a) Yes
(b) No
2. Which area the institution makes more contribution in socioeconomic
development through products they offer?
(a) VICOBA
(b) Banks
(c) UPATU
(d) SACCOS
3. What kind of loans ae being offered by the bank?
(a) Salary loans
(b) Commercial loans
(c) Funeral loans
(d) Overdraft
(e) Managed loans
(f) Others…………………………………………………………..………
68
4. What are the causes of bad loans to you as a client to the bank?
(a) Borrowers’ dishonest, Poor collateral security, Funds diversification
and poor investment
(b) Occurrence of unfavourable conditions, Improper mechanism in
monitoring activities, Bad screening of borrowers and Business
collapse
(c) Change of business environment, Change of credit allocation in
former business plan, High transaction costs on loans, Moral hazard
and high interest rates on loan disbursed
(d) Poor monitoring techniques, Reluctant fulfilling their contractual
agreement
5. What are the effects of bad loans/NPL to bank?
(a) Misunderstandings, confusion and Bad image of the bank
(b) Unstable operations, Mistrust between bank and clients
(c) Mismanagement of funds, Seize and auctioning all assets owned by
clients to cover loan amount
6. What hinders credit officers in performing effective monitoring of bad loans
/NPL?
(a) Lack of logistics and Under staffing
(b) Bad road to project sites and Ineffective supervision by management
(c) Inadequate motivation, Poor attitude of staff, Ineffective supervision
by external monitors
(d) All the above
7. What are the causes of delays in loan approval by the bank?
(a) Rigid approval procedures
(b) Customers inability to meet approval requirement
(c) Liquidity problems
(d) Poor credit appraisal
69
8. What reasons account for loan diversion on clients like you?
(a) Inadequate proper monitoring, Expectancy of high in order business
ventures
(b) Ignorance of terms and conditions attached, Differences in interest
rate on loans different sectors
(c) Inadequate financing sometimes Late disbursement of loan
9. What ways can a member/borrower prevent bad loans?
…………………………………………………………………………………
…………………………………………………………………………………
…………………………………………………………………………………
10. What kind of attitude would you have towards loan repayment?
(a) Better
(b) Good
(c) Poor
(d) Worse
11. What kind of attitude would you have towards overdue loans?
(a) Better
(b) Good
(c) Poor
(d) Worse
12. Is the amount sanction for disbursement enough to your expectation?
(a) Better
(b) Good
(c) Poor
(d) Worse
70
13. As an individual, what will you do to reduce the bad loans or overdue loans
on your views?
…………………………………………………………………………………
…………………………………………………………………………………
…………………………………………………………………………………
71
Appendix 3: INTERVIEW
Checklist of Focus Group Discussion for the Groups
All Responses Shall Be Entrusted and Treated Strictly Very Confidential. Your
Response to the Following Questionnaire Would is Highly Cherished.
1. What do you understand regarding the trend of bad loans?
2. What circumstances hinders you as a client during late loan repayment or
delinquency loans?
3. What are the factors for bad loan default?
4. Explain ideas and concepts that may be done for eradicating bad loans to
enhance institution’s performance?
5. What are the effect of bad loans on lending activities for the potential and
profitability of VICOBA?
6. What are the additional costs that associated with bad loans?
7. How the changes in overall profitability of the VICOBA affect the
institution?
8. Why there is Ineffectiveness of following up the clients’ obligation?
9. How multiple borrowing (meeting demand of client) facilitates growth of
VICOBA?
10. When do you think there might be an increase of commercial funding in the
institution?