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CHAPTER I
INTRODUCTION
1.1 Background of the Study.
Non-performing loan is borrowed money from the bank which has not made the
scheduled payments for a specified period is known as non-performing loan. The exact
elements of non-performing means no payment which is known as zero payments of
either principal or interest. Generally, the period is 90 days or 180days. Increase in the
level of gross non-performing loans pause a great risk to banks, the financial sector and
the economy at large. Equally, failure to manage down non-performing loans over a long
period gradually affects profitability of development banks (Bhattarai, 2023).

The non-performing loans of financial institutions are considered as a significant issue in

the context of Nepal for last few decades and macroeconomic variables such as the real
effective exchange rate have significantly negative impact on non-performing loan
(Bhattarai, 2015)

There is no standard form to define non-performing loans globally. Variation may exist in
terms of the classification system, the scope, and contents as per country. As a regulatory
financial institution of Nepal, the central bank, that is, Nepal Rastra Bank has classified
the loan basically into the pass loan, sub-standard loan, doubtful loan and loss or bad
loan. Pass loan is that type of loan whose interest or principal payments are less than
three months in arrears. Sub-standard loans whose interest or principal payments are
longer than three months in arrears of lending conditions are eased. Doubtful is
liquidation of outstanding debts appears doubtful and the accounts suggest that there will
be a loss, the exact amount of which cannot be determined. Loss loans are regarded as not
collectable, usually loans to firms which applied for legal resolution and protection under
bankruptcy laws. Pass loans are under the category of performing loans whereas sub-
standard loan, doubtful loan and loss loan are under the non-performing loans (NRB,
2013)
Banking in present age is the existence blood of whole monetary exercises. It is
instrumental in encircling the financial fate of the nation. Banks activates assets from
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perfect part to profitable division. Since the banks have immense speculation potential,
they can make a critical commitment in wiping out destitution and issue of joblessness. It
can likewise acquire balance the between region, between division and between close to
home differences in creating nation (Nachimuthu & Veni, 2019).

Moreover, the expansion in the productivity of a bank is constantly made a difference by

the synthesis of benefits and risk. Non-performing resources become exceptionally urgent
issues for the banks while expanding credits and generating profitability. Nonperforming
assets (NPAs) can be Gross NPAs and Net NPAs. Non-performing advances raises to
such a degree, that income tumble off and advance misfortune costs, just as working
expenses connect all the incomes that proceed. The reasons for NPAs incorporate
debacle, infection of the ventures, in successful recuperation process, business cycle,
loaning strategy, nonattendance of checking and catch up credit and administrative
issues. Non-Performing Assets show the fitness of the exhibition of the banks and it
influences the money foundation as well as the all-out monetary framework (Dudhe,
2014)

Introduction of Sample Bank

Muktinath Bikas Bank Limited (MBBL)
Muktinath Bikas Bank Limited (MNBBL) was established on 19th Paush 2063 B.S. (i.e.
3rd January 2007 A.D.), The Bank is licensed by the Central Bank of Nepal to operate as
a “B” Class National Level financial institution with its Central Office at Kamaladi,
Kathmandu, Nepal.Today, Muktinath Bikas Bank is known as the leading Development
Bank of Nepal with a history of its own.
The citizens of Syangja District (a hilly district with tough geographical terrain) were
starved for financial needs and the local people were undoubtedly had to travel to
Pokhara (the only nearby metro, with approximately 38 Kilometer mountainous road
linkage) for petty transaction such as withdrawal of mere NPR 5,000/- (approximately
$50). The cost of travelling and other involved security risk, hectic involvements and
more costs thereon. Then, the need for an immediate solution to these problems was felt
and a seed for the same was cultivated. The like-minded group of innovative local
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intellectuals from various sectors joined hands together to establish a local private sector
Bank to resolve the issues being dealt by people of Syangja District.
Likewise, on January 3, 2007, (We) the proposed Bank got license from the Central Bank
of Nepal (i.e. Nepal Rastra Bank) to operate Banking Business initially in three districts
namely Syangja, Kaski and Tanahun of then Western Development Region (currently
Gandaki Province) as a “B” class financial institution.
Since inception, the Bank has been adopting the deep rooted values of financial inclusion
of the community and core principle of “Janata Bank ma Hoina, Bank Janata ma Janu
Pardachha.” i.e. “People should not come to the Bank; Banks should go to the doors of
people”. The Bank prioritized opening branches in the rural areas where in the absence of
any financial institution, people were in dire need for Banking services. The customer
friendly products, services and door-to-door facility are the major factor for the Bank’s
popularity and success among the local people of the area. Within one and half years of
operations in the month of April 2009, the Bank started a Microfinance Program in its
host of services with starting a dedicated department at central office and branches to
serve low income but high potential people with high productivity. The Bank was the
first “B” class Bank with 3 pillars strategy of Modern Banking, Rural Banking & Micro
Banking for serving low-income people with dedicated departments for the same. vision
most preferred robust Bank in Nepal while uplifting socio-economic status of people.

Narayani Development Bank Limited (NDBL)

Narayani Development Bank Limited initially operated its transactions from 28th
September 2001, As a District level “B” class license financial institution with the name
of Narayani Audhogik Bikas Bank Limited. and was renamed Narayani Development
Bank Limited. The bank was established with the aim of providing the best services to
the customer and being their first choice. The bank’s corporate office is located in
Ratnanagar-1, Tandi, Chitwan. The bank has Five branches Tandi, Bharatpur,
Narayanghat, Parsa, and Yagyapuri (Cancer Hospital) respectively. As per the need of
our valued customer’s bank will expand its services to other places under the rules and
regulations of the Nepal Rastra Bank.

Narayani Development Bank provides customer-focused financial services to its valued

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customers in a very friendly environment. Narayani Development Bank Ltd. is equipped

with a team of competent and dedicated management professionals, strong IT
infrastructure and systems, and wider and deeper connections in the market; we now
stand as a very modern & efficient financial institution. Vision is to become a premier
financial institution known for its expertise and services in providing superior financial
solutions to our customers. We are committed to helping our customers achieve their
financial goals through innovative and superior financial solutions. To realize our mission
and goals, each member of the Narayani family believes in teamwork, corporate
governance, and social responsibilities.

Excel Development Bank Limited (EDBL)

Development Banking Sector remained dominated by government owned bank for more
than five decades. With the liberalization of economy private sector started to promote
development banks obtaining license from Nepal Rastra Bank, the central Bank of Nepal.
Excel Development Bank Limited is licensed by Nepal Rastra Bank under banking and
financial Regulation Act 2061.The bank is promoted by a group of experienced and
highly motivated individuals from all walks on life. The promoters include; professional
bankers, Entrepreneurs, Educationalists and Technocrats.
The bank’s central office is located in Birtamode, Jhapa, the far eastern part of Nepal. At
present the banks working area is in Illam, Jhapa, Morang, Sunsari and Panchthar
districts. The bank is committed to deliver its services to the customers through easy
banking procedures. Since the bank is located in the rural area, it indicates to serve the
need of common people by providing simple yet modern banking facilities. It is
transparent in its approach and workings.

The bank gives true value of the depositor’s money by providing a competitive interest
rate. Furthermore, it encourages the entrepreneurs to increase their capacity in productive
sectors. The bank aims to be engine of development with its reliable and trustworthy
banking services-Excel Development Bank Ltd. strives to achieve excellence in the
banking sector through its customer friendly approach. Vision of the bank become the
bank of common Nepalese people and contribute to the national economic development.
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Objective the bank provide loan on agriculture, service sectors, industry, trade and other
potential productive sectors.

1.2 Statement of the problem.

Azzahra et al. (2023) describes the maintenance of asset quality, efficiency and
profitability is a vital requirement for the survival and development of banks. Loans are
the main asset class from which banks generate their major portion of income and also
signify the greatest risk to banks. There has been significant indication that the financial
crises in the USA, Sub-Saharan Africa and East Asia were signaled by high levels of non-
performing loans (NPLs). Due to the detrimental effect that these loans have on a bank‟s
revenue and the economic welfare of a country, it is essential to examine and investigate
the determinants of NPLs in the banking industry of any country.

Kingu et al (2018), found that occurrence of non-performing loans is negatively

associated with the level of profitability in development banks in Tanzania. The results
extend further the information asymmetry theory and bad management hypothesis. The
findings of the study have both theoretical and managerial implications for practitioners
and policy-makers.
1) To describe dependent and independent variable in profitability of development
banks in Nepal?
2) What is the current relation of non-performing assets of development banks in
Nepal?
3) Does non-performing asset impact the profitability of development banks in
Nepal?

1.3 Objective of Study.

The basic objective of the study is to analyze the NPL management of Development
banks as well as to compare it. The specific objectives of the study are given below.
1) To describe of non-performing assets on profitability of development banks in
Nepal.
2) To assess the relation of non-performing assets of development banks in Nepal.
3) To analyze the effect of non-performing assets of development banks in Nepal.
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1.4 Rational of the Study.

This study intends to help the national economy through mobilization of idle capital of
average Nepalese in productive sectors to accelerate the economic growth and to reduce
dependency on foreign assistance and loan. This study will help regulatory authority to
find out liquidity management of the Development bank. It will be a reference to the
concerned personnel and researchers. This study will also show and suggest the available
investment opportunities satisfying the objectives liquidity of Development bank. The
study has various significant. The study is mainly beneficial to the investors, depositors
and other creditors to identify the productivity of their funds in the Development bank.
Then, policy makers at the macro level that is government and Nepal Rastra Bank will
also benefit regarding the formulation of further policies in regard to economic
development through financial institutions. The study also compels the management of
respective Dvelopment Bankfor self-assessment of what they have done in the past and
guides them in their future plans and programs. Moreover, every individual as well as
further researcher will have a good source of literature for review about the findings done
by this study.
1.6 Limitations of the Study.
The study is important document in context of liquidity and profitability in Nepalese
Development Bank. Study is limited to the following:
 The study is limited to only 3 Development Bank of Nepal.
 This study concentrates only their impact on profitability and ignores the other
financial aspects.
 Profitability of an organization is caused by CDR, NPLA, NPLTL, IILA factors
but here we study only those factors, which are directly affected by the non-
performing assets of the commercial banks.
 Only secondary data is used for analysis.
 The study is limited to the past ten years from 2012/13 to 2022/23

Chapter II
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Literature Review
Review of literature means reviewing research studies and other relevant propositions in
the related area of the study so that all the past studies, their conclusions and deficiencies
may be known and further research can be conducted. The literature review may also
serve as a kind of bibliographic index and guide for the readers. It also demonstrates
where the current study fits into the scheme of things. The objective of reviewing the
literature is to develop certain expertise and knowledge in one's area. This chapter is
divided into mainly four parts.
2.1 Theoretical Review.
A theoretical review is an academic work that examines existing theoretical frameworks,
models, and concepts related to a particular research topic. It involves analyzing and
synthesizing relevant literature and critically evaluating the concepts and theories
presented.
The purpose of a theoretical review is to identify the key concepts and theoretical
perspectives related to a research problem, and to evaluate the strengths and weaknesses
of the existing theories. The review can help to identify gaps in current knowledge and
suggest areas for further research.
A theoretical review typically includes a comprehensive overview of relevant literature,
an analysis of key concepts and theoretical perspectives, and a critical evaluation of the
existing theories. The review may also provide suggestions for future research directions
and propose new theoretical frameworks to explain the research problem.

Azzahra et al. (2023) Non-performing loans are considered determinants of profitability

because, high levels of nonperforming loans adversely affect bank net profit through
provisioning of doubtful debts and write offs of bad debts; which normally affect
profitability and capital levels. Subsequently, the moment non-performing loans exceed
bank capital in a relatively large number of banks can compound into a bank crisis, which
eventually turns into a financial crisis. Empirical studies found a possible relationship
between high levels of non-performing loans and low profitability. The theoretical
perspectives that informed this research and the development of the hypotheses used to
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analyze the relationship between NPL and Profitability are information asymmetry theory
and bad management hypothesis.

Information Asymmetry Theory

Information Asymmetry Theory argues that asymmetric information occurs when one
party in a transactional relationship is more informed about the transaction than the other
party. In the financial decision space, asymmetric information literature looks at the
impact of decisions based on the difference in the information available to both
parties .Lenders offering credit facilities to borrowers face uncertainty of loan repayment,
as they cannot observe the characteristics and actions of the borrower, thus making it
difficult to assess the creditworthiness of the borrower. Consequently, adverse selection
leads to whereby high-quality borrowers are displaced by low-quality borrowers, which
in the long run cause deterioration in the overall quality of bank loan portfolios and lead
to accumulation of non-performing loans, decrease in profitability and erosion of capital.
(Do, Ngo and Phung, 2020)

The adverse selection theory

The adverse selection theory describes the situation where the probability of loan default
increases with rising interest rate and the quality of borrowers worsens as the cost of
borrowing rises. The theory is founded on the assumption that banks are not certain in
selecting credit-worthy borrowers from a pool of loan seekers with different credit risk
exposures ex-ante. Thus, financial intermediaries are more likely to lend to high-risk
borrowers who are not concerned about the harsh lending conditions and are prone to
loan default argue that information sharing reduces adverse selection problems by
enhancing information on loan applicants. Document that if banks exchange credit
information on defaults, then borrowers are encouraged to apply more energy in their
projects knowing fully well that loan default carries the penalty of higher interest rates or
no future access to credit facility. (Gabriel, Victor and Innocent, 2019)

Hazard model Theory

Hazard model theory for credit market, the phenomenon of using private information to
benefit from an incomplete contract in the presence of information asymmetry is known
as moral hazard also noted that moral hazard exist where the borrower of bank credit
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takes action that adversely affects the returns to the lender. Posit that a bank that makes
and sells loans is subject to a moral hazard problem with respect to screening borrowers.
The theory is based on the assumption that the likelihood of borrowers engaging in
activities that will guarantee repayment of bank credit extended to them cannot be
determined ex-post by banks.
Several theoretical studies have analyzed the impact of non-performing loans on the
financial performance of commercial banks. Even in recent years, we have had a huge
pool of literature that examines the importance of resource management in determining
the profitability of the bank. Due to the multifaceted effect, it is hard to draw clear and
concise conclusions regarding the impact of NPL on profitability. The banks’ profitability
is measured by different indicators such as liquidity, solvency, (debt/capital ratio), and
common indicators such as Return on Assets (ROA) and Return on Equity (ROE). The
financial performance traditionally has been measured through ROA and ROE, and most
studies prefer ROE more because this indicator combines profit, efficiency, and financial
leverage. Both ROA and ROE are calculated as net profit divided by assets respectively
by bank equity. Banks with greater ROA and ROE have better performance and
financially are more stable (Gabriel, Victor and Innocent, 2019)

2.1.1 Non Preforming Loan

Non-performing loans (NPL) are borrowed amounts that are at the disposal of the debtor.
Failed to make scheduled payments for the specified period. Exact element, but the
percentage of outstanding status depends on the credit terms, "no payment”. Usually
defined as zero principal or interest payments. Specified period It also depends on the
industry and type of loan. However, usually the period is 90 days or 180 days
(Nachimuthu and Veni, 2019)

Over the last few decades, the literature examining non-performing loans has grown in
step with the attention paid to comprehending the causes of monetary fragility. This
circumstance may result from the fact that As shown by the strong correlation between
NPLs and the financial crises in Argentina, East Asia, and Sub-Saharan Africa countries
during the 1990s, damaged assets have an essential function in financial vulnerability. In
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this section, we examine the available literature in order to provide a theoretical

framework for looking into the factors that influence non-performing loans in Guyana.
2.1.2 Classification of Loans and Advance
Having exercised the powers conferred by Section 79 of the Nepal Rastra Bank Act,
2002, the following Directives have been issued with regard to classification of
credit/advances and provisions to be made for its possible loss by the institutions
obtaining licenses from this Bank to carry out financial transactions. NRB, (2022) Entire
loans and advances extended by a licensed institution have to be classified as follows
based on expiry of the deadline of repayment of the principal and interest of such
loans/advances:-

a) Pass: Loans/advances which have not overdue and which are overdue by a period
up to three months.
b) Sub-standard: Loans/advances which are overdue by a period from three months
to a maximum period of six months.
c) Doubtful: Loans/advances which are overdue by a period from six-months to a
maximum period of one year.
d) Loss: Loans/advances which are overdue by a period of more than one year. The
loans which are in pass class and which have been rescheduled/restructured are
called as "the performing loan, and the sub-standard, doubtful and loss categories
are called non-performing loans.

2.1.3 Additional Provisions Relating to Pass Loans:

1) NRB, (2022) the following loans may be included in the pass loan:-

a) Loans/advances extended against the collateral of gold and silver;

b) Loans/advances of fixed receipts
c) Loans/advances of Government of Nepal securities and loans/advances made
against the collateral of Nepal Rastra Bank bonds; Provided that the cases of the
loans/advances against the fixed receipts or Government of Nepal securities or
Nepal Rastra Bank bond as the additional collateral, such loans and advances
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shall also have to be classified in accordance with the directive referred to into
Point No. 1 above.
2) The working capital loan having the deadline of up to one year for repayment may be
included in the pass loan class. In case the interest to be received from the loans of
working capital nature is not regular, such loans have to be classified on the basis of the
duration of interest to be due.
2.1.4. Additional Provisions Relating to Loss Loans
NRB, (2022) in case there seem any of the following discrepancies in any of the
following loans, whether or not the deadline for repayment of which is expired, such
loans and advances has to be categorized as the loss loan:
(a) The market price of the collateral cannot secure the loans;
(b)The debtor is bankrupt or has been declared to be bankrupt;
(c) The debtor disappears or is not identified;
(d)In case non-fund based facilities such as purchased or discounted bills and L/C and
guarantee which have been converted into fund-based loan, are not recovered within
ninety days from the date of their conversion into loan;
(e) Loan is misused; (f) Expiry of six months of the date of auction process after the loan
could not be recovered or a case is pending at a count under the recovery process;
(f) Providing loan to a debtor who has been enlisted in the black-list of Credit
Information Bureau Ltd;
(g)The Project/business is not in a condition to be operated or project or business is not
in operation
(h)The credit card loan is not written off within 90 days from the date of expiry of the
deadline;
(i) While converting the L/C, guarantee and other possible liabilities into a fund based
loan under the regular process, if the said loan is not recovered within 90 days;
(j) In case of expiry of the deadline of a trust-receipt loan.

2.1.5 Additional Provisions Relating to Term-loan

NRB, (2018) in cases of the term loans extended in installments, if the deadline of
installment of the principal amount expires, remaining entire loan amount has to be
classified based on expiry of the deadline of the installment amount.
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Provided that in cases of the installment of the term loan given by licensed institution not
having the facility of engaging in overdraft transaction, entire loan amount has to be
categorized as loss loan only if the installment amount has crossed the deadline by a
period of more than one year. In case the installment amount has crossed the deadline by
a period of less than one year, only such installment amount has to be classified in the
loss loan with a provision of loan loss. However, this clause shall not be deemed to have
hindered if the licensed institution wants to classify the entire loan amount as the loss
loan.
2.1.6 Provisions Relating to Rescheduling and Restructuring of Loans
(1) In case a licensed institution is convinced on the following bases stated in the written
action plan submitted by the debtor, it may reschedule or retract the loan:-
a) Evidence showing that documents relating to loans and security are adequate;
b) Bases on which the licensed institution is convinced of the possibility that the
rescheduled or restructured loans would be recovered;
c) In addition to submission of written plan of actions for rescheduling and
restructuring loans at least 25 percent of the interest due to be paid until the date
of rescheduling or restructuring of such a loan has been paid;

(2) While rescheduling or restructuring the loans to the industries which have been
recommended by the Sick Industries Preliminary Inquiry and Recommendation
Committee formed under Government of Nepal, a minimum of 12 percent of interest has
to be paid, other procedures need to be fulfilled and rescheduling and restructuring shall
have to be carried out making a provision for twenty-five percent loan loss. Provided that
in the event where the loan has been rescheduled and restructured based on payment of
less than 12 percent of interests, provision for loan loss has to be made based on the
duration upon expiry of the deadline according to the prevailing provisions.
(3) Description of the loans classified pursuant to classes (1) and (2) has to be separately
prepared (NRB, 2022).
2.1.7 Provision to be maintained for Loan Loss
(1) For the loans and bills purchase classified according to these Directives, the
following loan loss provision shall be maintained based on the remaining amount of
principal:
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Loan classification Minimum Provision for loan loss

(a) Pass 1 percent
(b) Sub-standard 25 percent
(c) Doubtful 50 percent
(d) Loss loan/the loan extended to blacklisted 100 percent Persons,

Firms, company or corporate body Provided that in case of the insured loans, it would be
required to make provision of only 25 percent of the provision referred to in sub-clause
(1) (2) In cases of the loans rescheduled and restructured, the following loan loss
provision shall be made:-

(a) The loans classified in the pass class at the time of rescheduling and restructuring
shall, while rescheduling and restructuring, provision of at least 12.5 percent has to be
made as loan loss, while rescheduling and restructuring the loans classified as
substandard, doubtful and loss, no adjustment shall be allowed in the then loan loss
provision except in the cases referred to in clause 10(c). In cases of the loans made
available on an equal monthly installment, no loan loss provision shall have to be made in
case of rescheduling and restructuring of the following of such loans if the principal and
interest is regular:

 In case amount of installment and number of installment is decreased because of

prepayment of installment.
 Due to change in the rate of interest having regard to the market situation, the
duration of the loan and installment amount has been changed. In this context, if
the rate of interest is increased and thereby by the duration and installment
amount is increased, the installment amount determined at the time of sanctioning
the loan is not allowed to be decreased. Similarly, if the rate of interest is
decreased and thereby the duration and number of installment are decreased, the
installment amount determined at the time of sanctioning the loan is not allowed
to be decreased.
(b) In case the installment of principal of the rescheduled and restructured loan and
interest of two years, such loans may be converted into pass loans.
(c) No loans extended having pledged shares shall be rescheduled and restructured.
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(3) In the event of deprive sector lending made by licensed institution Bank and financial
institution to deprived communities according to Directives of this Bank; if such loans
have been secured through Deposit Insurance and Credit Guarantee Corporation or if
other loans have also been insured an exemption of 75 percent has been made and
provision for remaining 25 percent shall be required.
(4) Banks and financial institution shall not provide any type of loan on the security of
the memo (adhakatti) of an application to be submitted for share purchase at the time of
initial public offering. In case of providing loan in such a way, the concerned bank or
financial institution shall have to make cent percent loan loss provision.
(5) While providing loan on personal/institutional guarantee, description of property
equal in value to the amount of the personal guarantee and in sole ownership of the
debtor and free of any claim of anyone else shall compulsorily be obtained. Even the
loans given only on the basis of personal/institutional guarantee shall also be classified as
stated above in pass, substandard and doubtful as may be required and loan loss provision
shall be made 20 percent more in addition to the percentage prescribed for that class.
Even in the cases where personal guarantee has been taken for the collateral of physical
property alone could not secure the loan, the provision for additional loan and stated
above has to be made. Classifications of such loan have to be made separately.

Provided that in cases of loans and advances made to the institutions referred to in sub-
clause (b) of clause 4 of the Directives No. 3, Nepal Oil Limited and Nepal Food
Corporation, no additional loan loss provision of 20 percent shall be required to be made.
(6) No additional loan loss provision of 20 percent shall be required to be made in the
loan loss provision referred to in sub-clause (3) above in cases of education loan and
loans extended to micro-credit financial institutions and cooperative financial institution
under the deprived sector lending by banks and financial institution on personal
guarantee.
(7) There is no restriction to classify loans and advances of higher class to lower class in
case licensed institution so wishes. For an example, substandard loan may be classified as
doubtful or loss loan and doubtful loan may be classified as loss loan. (8) Loans/advances
also include bills purchase and discounts.
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2.1.8 Conditions for Adjustment in Loan Loss Provision

NRB, (2018) No loan loss provision shall be allowed for adjustment except in the
following conditions:-
a) In case the loan is written off;
b) In the event where repayment of loan is in installment or in partial basis, the loan
loss provision made to the extent of the loan so repaid may be written back and
adjusted while maintaining loan loss provision according to loan classification;
c) In the event of the loan is reclassified after loan rescheduling and restructuring, if
the repayment of the principal and interest of the loan so rescheduled and
restructured is regular for a consecutive period of two years. Details of such loans
shall be separately prepared.
2.1.9 Loss Provisions and Auction of Non-banking Assets
(1) In case of the non-banking assets accepted by the licensed institution, cent percent
loss provisions shall be made from the date of the acceptance.
(2) In case of sale of the non-banking assets, necessary adjustment in the accounts of loss
provision maintained for such property shall immediately be made.
(3) While accepting collateral security as non-banking assets by licensed institution, the
following provisions shall be applicable while selling the non-banking assets so accepted:
a) While accepting the collateral property of a customer as non-banking assets
whose outstanding loan amount is more than 2.5 million, the concerned party
shall compulsorily be black-listed.
b) Prior to auctioning the non-banking assets in the name of the institution, it shall
have to be evaluated by an independent evaluator. No excessive/less evaluation
shall be allowed.
c) Transparent and clear provisions shall be made with regard to auction sale of
collateral security/non-banking assets in Financial Administration Byelaws and
sales shall have to be carried out in such a manner to serve interest of the bank or
financial institution.
d) While accepting the non-banking assets in such a manner, entire property
mortgaged as collateral that could not be sold by auction shall have to be accepted
and it may not be accepted in part.
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e) The property so accepted shall have to be sold at the earliest to the extent
possible. In case it is necessary for own purpose of the licensed institution, the
same shall have to be approved by the Board of Directors and information thereof
shall be made available to this Bank as well.
2.1.10 Cause of Non-performing loans
Brownbridge (1998) most of the bank failures were caused bynon- performing loans.
Arrears affecting more than half the loan portfolios were typical of the failed banks.
Many of the bad debts were attributable to moral hazard: the adverse incentives on bank
owners to adopt imprudent lending strategies, in particular insider lending and lending at
high interest rates to borrowers in the most risky segments of the credit markets.

Inside Lending
According to Brownbridge, the single biggest contributor to the bad loans of many of the
failed local banks was insider lending. In at least half of the bank failures, insider loans
accounted for a substantial proportion of the bad debts. Most of the larger local bank
failures in Kenya, such as the Continental Bank, Trade Bank and Pan African Bank,
involved extensive insider lending, often to politicians. The threat posed by insider
lending to the soundness of the banks was exacerbated because many of the insider loans
were invested in speculative projects such as real estate development, breached large-loan
exposure limits, and were extended to projects which could not short term returns.
High Interest Rates
In the study the second major factor contributing to bank failure was lending, at high
interest rates, to borrowers in high-risk segments of the credit market. This involved
elements of moral hazard on the part of both the banks and their borrowers and the
adverse selection of the borrowers (Jathurika, 2019) it was in part motivated by the high
cost of mobilizing funds.

Macroeconomic Instability
Brownbridge cited macroeconomic instability as the third most important cause. During
the l990s, inflation reached 46% in Kenya. High inflation increases the volatility of
business profits because of its unpredictability, and because it normally entails a high
degree of variability in the rates of interest, there is increase of the prices of the particular
 17

goods and services which make up the overall price index. This intensifies both adverse
selection and adverse incentives for borrowers to take risks, and thus the probabilities of
loan default.
Liquidity Support and Prudential Regulation
The fourth most important factor is liquidity support and prudential regulation. The
Willingness of the regulatory authorities to support distressed banks with loans, rather
than close them down, was probably an important contributor to moral hazard.
Inadequate Management of Credit Risk
Singh et al. (2021) state that the growth of bank credit in Spain and its prudential
implications is an ever-present item on the agenda of banking supervisors, since most
banking crises have had as a direct cause the inadequate management of credit risk by
institutions. They further assert that even though bank supervisors are well aware of this
problem, it is however very difficult to persuade bank managers to follow more prudent
credit policies during an economic upturn, especially in a highly competitive
environment. They claim that even conservative managers might find market pressure for
higher profits very difficult to overcome.
Economic Mismanagement and Political Interference
One important impact that non-performing loans have had on banks is the attempted
improvement on the management of credit risk. In China for example, in a bid to help the
banks get rid of the NPLs accumulated over past years, the Chinese government in
1998established four state-sponsored asset management companies to take over bad debts
from the banks‟ balance sheets. On top of that, the government injected 270billion into
the four major banks to strengthen their capital bases (Ding et al., 2000) To help address
credit risk management in Ugandan banks, the government has introduced a statute that
deals with several issues such as insider lending, following the recent scandal in which
billions of shillings were lent without sufficient collateral to Greenland Bank by the
newly privatized Uganda Commercial Bank Ltd. The statute further seeks to reduce
owner concentration (Shaban, 2018)
2.1.11 Concept of Profitability
Balasubramaniam (2012) NPL means booking of money in terms of bad asset, which
occurred due to wrong choice of client. Because of the money getting blocked the
 18

prodigality of bank decreases not only by the amount of NPL but NPL lead to
opportunity cost also as that much of profit invested in some return earning project/asset.
So NPL does not affect current profit but also future stream of profit, which may lead to
loss of some long-term beneficial opportunity. Another impact of reduction in
profitability is low ROI (return on investment), which adversely affect current earning of
bank. (Nachimuthu and Veni, 2019)NPL means booking of money in terms of bad asset,
which occurred due to wrong choice of client. Because of the money getting blocked the
profitability of bank decreases not only by the amount of NPL but it lead to opportunity
cost also as that much of profit invested in some return earning project/asset. So NPL
does not affect current profit but also future stream of profit, which may lead to loss of
some long-term beneficial opportunity.
Relationship between non-performing assets and profitability
Angela et al. (2020) Commercial banks operate in very sensitive markets with
considerable risk and uncertainty. The study was carried out with a view of investigation
the problems of non-performing loans in Kenyan commercial banking sector and the
likely effect on their profitability and returns. To achieve the objective of the study,
regression model was developed with return on asset as the dependent variable and the
amount of credits, level of non-performing loan, and the level of shareholders equity as
the independent variables. The weak relationship between dependent variable and the
chosen independent variables indicates there more factor that affect banks profitability.
Other measures such as improving the credit information sharing platform and
developing robust monetary policies will go a long way in making the returns the banks
better. Impacts of NPL over the banking profitability are as follow:

 It is adversely affect the image of the banks.

 NPL do not earn any income but it can earned profit by making performing assets.
 NPL have direct impacts on ROA and ROE of the commercial banks.
 Moreover NPL inversely affects the balance sheet of banks.

2.2 Empirical Review.

 19

Azzahra et.al (2023) investigated the influence of non-performing loans and interest rates
on company profits with profitability levels as intervening in a Case Study at Medan. The
approach of this research was quantitative method and used Smart PLS. The sample of
this research was the financial reports of PT. BPR Duta Adiarta Medan. The sourced of
data in this research is using secondary data, obtained from the internal of the sub-
banking financial sector company. The methods used in this research are data collection
and analysis of reports. The analyzed result showed three accepted hypotheses, which are
the influence of non-performing loans towards profitability levels, influence of non-
performing loans towards company profits, and the influence of interest rates towards
company profits.
Pokharel and Pokharel (2022) examined the impact of non-performing assets on
profitability in Nepalese commercial banks. The study cover the period 2013 July 16 to
2018 July 16. Further, the examined is made to investigate the impact of various
gatherings of banks. In particular, Government owned bank and private area banks on the
financial business in such manner. Five out of twenty four individual private division
banks and one out of three, government claimed banks have been considered with the end
goal of the investigation for as sample. Data are collected from annual report Descriptive
statistic, Panel data regression analysis used. Findings of this studied concluded that
impact of nonperforming loan on profitability in Nepalese commercial bank shows the
positive impact.

Angela, Baidoo and Ayesu (2020) analyzed the study tinvestigate the impact of credit
risk with focus on non-performing loans on the financial performance of commercial
banks in Ghana. Return on asset and economic value-added are used as measures of
financial performance. Panel data spanning the period 2013 to 2018 on 15 commercial
banks in Ghana is used for the analysis. The resulted was random effect estimation
technique show that non-performing loans have a negative impact on both measures of
financial performance. Also, monetary policy rate has a negative impact on both
measures of financial performance, albeit insignificant for economic valueadded
measure.
Singh, Basuki and Setiawan (2021) investigated the main objective of research is to find
out the effect of Non-Performing Loan (NPL) of Nepalese conventional banks. The
 20

population of this studied is major commercial banks in Nepal and the data obtained for
this study was from the period 2015–2019. The research used secondary data and it is
collected from each bank’s annual report and GDP and Inflation taken from the World
Bank database. The method used for data analysis in this study is multiple regression
analysis. The study used NPL as a dependent variable and Return on Asset (ROA),
Capital Adequacy Ratio (CAR), Bank Size, GDP growth, and Inflation as
independent/explanatory variables. The result research was showed that ROA, Bank Size,
GDP, and Inflation have a significant effect on NPL but CAR does not have a significant
effect on the NPL of banks. In other words, the GDP effect on NPL in this study shows a
positive and significant effect while most studies show a negative effect.

Do, Ngo and Phung (2020) studied the effect of non-performing loans on profitability of
commercial banks Vietnam. Investigated aim impact of non-performing loans on the
ability to make profit of Vietnamese commercial bank. Profit always was the top priority
of banking operation over the years. Secondary data, growth rate of gross domestic
product (GDP) is taken from the Vietnam section of World Ban. The study found that
Studies found that non-performing loans have negative impact on the bank’s profitability.

Jathurika (2019) purposed investigation is to the impact of Non-Performing Loans on

financial performance. The study confines only nine listed commercial banks in Sri
Lanka through the purposive sampling due to the minimize of missing data and links
secondary data derived from the annual financial reports of commercial banks using the
CSE’s database.. Regression and Correlation analysis have been employed for the study
to investigate the effects of non-performing loans on financial performance. The resulted
of the analyzed have revealed that attribute of Non-Performing Loans which is Non-
Performing Loan ratio have a negative and significant impact on Financial Performance.
The fined of the research utterly reveals that, non-performing loans significantly
influences the financial performance of listed commercial banks in Sri Lanka with the
negative relationship.

Gabriel, Victor and Innocent (2019) examined the effect of Non-Performing loans on the
financial performance of commercial banks in Nigeria between the periods of 1985 to
2016. The study employed the multiple regression techniques to analyze data collated
 21

from the central bank of Nigeria statistical bulletin and Nigeria deposit insurance
corporation publications for various years. The result of the study showed that Non-
Performing loans to total loans ratio and cash reserve ratio had statistically negative
significant effect on Return on Asset. These result showed that a high level of non-
performing loans would reduce the financial performance of commercial banks in
Nigeria. Consequently, the study recommends that the regulatory authorities in Nigeria
should create and support an environment where commercial banks in Nigeria can have a
strong risk management practices.

Shaban (2018) examined the Non-Performing assets and their impact on the profitability
of commercial banks public banks, private banks and foreign banks in India. The data
collected from RBI database, for the period of eleven years from 1st April 2006 to 31st
March 2017. Regression analysis has been used in the study where; return on assets and
return on equity have been used as proxy variables for profitability of the banks while
Gross NPA to Gross advances ratio and Net NPA to Net advances ratio has been used as
independent variables to denote the non-performing assets of the banks.

Gautam (2018) examined the impact of non-performing loan on profitability of Nepalese

commercial banks. ROA (return on assets)and ROE (return on equity) are dependent
variables whereas non-performing loan to total loan (NPTL), credit to deposit ratio
(CDR), net profit to loan and advance(NPLA), and interest income to loan and advance
(IILA) are the independent variables. Data are collected from annual report of the
respective banks. The study was based on 100 observations from different 10 commercial
banks of Nepal. The regression models have been employed to test the impact of non-
performing loans on profitability of Nepalese commercial banks. The result showed that
beta coefficient for credit to deposit ratio, net profit to loan and advances, non-
performing loan to total loan, interest income to loan and advance are positive on return
on assets.
Mitai (2017) investigated the effect of non-performing loans on the financial performance
of commercial banks in Kenya. Profitability measured by return on assets used as
dependent variable and non-performing loans measured by non-performing loans ratio,
capital adequacy, management efficiency and liquidity are used as independent variables.
 22

The independent variables used of CAMEL factors that also affect profitability of
commercial banks. The study used secondary data to analyze. The study indicates that
there negative effect of non-performing loans ratio on return on assets, confirming that
non-performing loans negatively affects profitability of commercial banks in Kenya.

Dhodary (2023) analyzed determinants of stock price of Nepalese commercial banks. The
study is conducted use quantitative method followed by descriptive research to make
brief and accurate study on selected variables and pooled cross-sectional data that are
collected from NEPSE listed banks at one point in time. The data are collected covering
the period from the F/Y 2011/12 to 2020/21. Ten commercial banks are selected as
representative of target population of 26 commercial banks. The research variables are
book value per share, PE ratio, firm size, dividend payment, return on equity and market
price per share. Under the statistical analysis, descriptive statistics, correlation and
multiple regression analysis are conducted. Descriptive statistics show the book value
per share and firm size of Nepalese commercial banks have been found steadily growing
whereas the profitability, dividend and stock performance in market are quite volatile.
The P/E ratio is found to be nil in some of the year due to no earnings per share of
particular bank. Share price of Nepalese commercial banks is positively correlated to
BVPS, PE, ROE and DIV whereas negative relationship with firm size (FS). Among the
independent variables, all variable except firm size (FS) are statistically significant.
Regression results reveals that BVPS, PE, ROE and DIV have positive and significant
impact on MPS whereas firm size (FS) has significant and negative impact on
MPS.

Pandey and Joshi (2023) examined the impact of credit risk management on profitability
of Nepalese commercial banks. Default rate, cost per loan assets and capital adequacy
ratio are the independent variables used in this study. The dependent variables are return
on assets (ROA) and return on equity (ROE). The secondary sources of data have been
used from annual reports of selected commercial banks and supervision report of Nepal
Rastra Bank. The regression models are estimated to test the significance and effect of
credit risk management on profitability of Nepalese commercial banks. The beta
coefficient of default rate and cost per assets with profitability (ROA, ROE) has been
 23

found negative and statistically significant. The negative sign indicates that there is
statistically negative relationship between default rate and cost per loan assets with
profitability. Likewise, the beta coefficient of capital adequacy ratio with ROA and ROE
is found to be positive and statistically significant. The positive sign of beta coefficient
indicates that there is statistically positive relationship between capital adequacy ratio and
profitability.

Kattel and Pradhan (2023) investigated the effect of firm specific factors affecting stock
price of Nepalese insurance companies. Stock return and market price per share are
selected as the dependent variables. The selected independent variables are premium
growth, return on assets, return on equity, dividend per share, earnings per share, price
earnings ratio and company size. The study was based on secondary data of 20 insurance
companies with 140 observations for the study period from 2014/15 to 2020/21. The data
were collected from the annual reports of Rastriya Beema Samiti, reports published by
NEPSE and annual reports of selected Nepalese insurance companies. The regression
models was estimated to test the significance and effect of firm specific factors on the
stock price of Nepalese insurance companies. The study showed that earnings per share
have positive impact on market price per share and stock return. It indicated that increase
in earnings per share leads to increase in market share price and stock return. The study
showed that price earnings ratio has a positive effect on market price per share. It reveals
that higher the price earnings ratio, higher would be the market share price.

Luitel (2023) examined the impact of macro-economic variables on the profitability of

Nepalese commercial banks. Return on assets and return on equity are selected as the
dependent variables. Similarly, inflation, money supply, unemployment rate, gross
domestic product, exchange rate and interest rate are selected as the independent
variables. This study is based on secondary data of 16 commercial banks with 128
observations for the study period from 2013/14 to 2020/21. The data were collected from
Banking and Financial Statistics published by Nepal Rastra Bank, annual reports of the
selected commercial banks and reports published by Ministry of Finance. The correlation
coefficients and regression models are estimated to test the significance and importance
of macro-economic variables on the profitability of Nepalese commercial banks. The
 24

study showed that exchange rate has a negative impact on return on assets and return on
equity. It indicates that increase in exchange rate leads to decrease in return on assets and
return on equity.

Shrestha (2023) investigated impact of firm-specific factors on the financial performance

of Nepalese Microfinance institutions. The Objectives of the study to analyze the impact
of firm-specific factors on the financial performance of Nepalese Microfinance
Institutions (MFIs). The method applied descriptive and causal comparative research
design. The annual panel data of 29 microfinance companies listed in the Nepal stock
exchange for the period of 2010/11 to 2020/21 has been used. To identify the impact of
firm-specific factors on the financial performance of Nepalese MFIs, an appropriate
multivariate regression model is selected based on the result of the Breusch and Pagan
Lagrangian multiplier test and the Hausman test. The result fixed effect regression model,
this paper found the significant influence of firm-specific factors on the financial
performance of Nepalese MFIs. Further, this study found a significant positive impact on
deposit ratio, management efficiency, and weighted average interest rate spread and a
significant negative impact of asset quality on the financial performance of Nepalese
MFIs.

Bhatt and Jain (2022) examined the effects of Economic Policy Uncertainty (EPU) on
dividend distribution strategy to provide some evidence from developing country
prospect. Use a sample of 19 commercial banks for 2009–2020 and the Baker, Bloom,
and Davis Index as a proxy of EPU, our key finding demonstrates EPU has no significant
direct relationship with the dividend decision of the banking firm. The empirical result
reveals that the banking firms in Nepal neither terminate nor initiate dividends during
EPU. The found evidence of no precautionary incentive of banking executives as a
reaction to policy distress. The dividend payment decision is intuitive for the banking
firm in Nepal rather than uncertainty prone by the change in economic policy. The
precautionary motive dominates the firms, banks are supposed to distribute lower cash
dividend once there is a more considerable degree of policy uncertainty as a buffer
against adversity. Other firm-specific variables, such as corporate earnings, past year
 25

dividend, ownership structure, and bank size, affect the dividend decision of banking
firms in Nepal.

Gyawali (2022) purposed of this research is to examine the impact of factors influencing
the stock price of Nepalese commercial banks. This research uses MPS as the dependent
variable and independent variables are DPS, EPS, P/E ratio, ROA, GDP, and inflation
rate. The secondary data was collected from the annual reports of selected commercial
banks for five year study period from 2017 to 2021. Descriptive and causal-comparative
research design has been used to analyze and interpret this data using SPSS 23 version.
Ten commercial banks are taken as a sample out of 27 banks. The convenience sampling
method is used. Multiple linear regression models have been used to show the impact of
independent variables on the dependent variable. The result showed that there is a
positive and statistically significant effect of DPS, EPS, and P/E ratio on the stock price.
ROA and GDP have a positive but not significant effect on the stock price but the
inflation rate has a negative and insignificant impact on the stock price.

Gautam (2021) investigated determining firm value in commercial banks is challenging

because its value is affected by various internal and external determinants. Using a
structured questionnaire, the study objective to assess a survey on the perception of firm
value in Nepalese commercial banks. Three hundred questionnaires were distributed
equally among depositors and investors. Among them, 183 questionnaires were collected
into usable form. The finding revealed that depositors and investors perceive that deposit,
profitability, capital adequacy and good governance affect bank value. Publication of
financial reports is one of the major influencing factors of bank value. Credit risk has a
negative effect on firm value in banks. The study concludes that firm value primarily
depends on managerial efficiency followed by market information, strong liquidity
position, credit risk, earnings position, use of the loan, leverage and size, respectively, in
Nepalese commercial banks.

Yitayaw (2021) investigated the bank-specific and macroeconomic determinants of

commercial banks’ liquidity in Ethiopia using secondary unbalanced panel data. The
empirical analysis was carried out through the use of the generalized method of moments
 26

(GMM) estimation of dynamic panel data from 15 commercial banks from 2009–2019.
The model result showed that lagged value of liquidity and deposit had a positive and
statistically significant effect on commercial banks’ liquidity. On the other hand, capital
adequacy, bank size, interest rate margin, and gross domestic product had a negative and
statistically significant effect on the commercial bank’s liquidity.

Bhattarai (2020) examined the factor that has affecting the market share price of
commercial banks from 2013/14 to 2017/18 of Nepalese commercial banks. The bank
specific secondary panel balance data were collected from 12 sample commercial banks
byusing convenient sampling technique and the data of macroeconomic variable were
collected through the economic survey which was published by Ministry of Finance,
Nepal. Market share price was proxy of dependent variable. The dividend payout ratio,
dividend yield, earnings per share, price earnings ratio, bank size and gross domestic
products growth rate and inflation rate were used as independent variables. The study was
employed descriptive, correlational and casual comparative research design. The data
were analysis through the Pooled OLS and Fixed Effects model as directed by model
diagnosis test. The finding from both models was more or less same. The dividend payout
ratio has negative and statistically significant with market share price. The dividend yield,
earnings per share, price earnings ratio were positive and statistically significant with
market share price. The ban size, gross domestic products growth rate and inflation rate
were not role to determine the market share price.
Silwal and Napit (2019) investigated the determinants of the stock market price in
Nepalese commercial banks for the period of 2065/66 to 2074/75. It is based on pooled
cross-sectional data of ten banks for 10 years whose stocks are listed in Nepal stock
exchange. The study employed correlational and causal comparative research design and
result reveals that book value per share, price earnings ratio, returns on equity have
positive relationship with stock price. Dividend yield has positive but minimum influence
on the price of the stock whereas size has negative relationship and is statistically
insignificant with stock price.
Summary Table
 27

Date of Writer/ Objective Dependent Methodology Finding

Publica Article/ and
tion Journal Independent
Variable
2023 Azzahra, Research Dependent The source of data The analysis
Gunawan, aim the Variable in this research was result showed
Aditya, influence of Company used secondary three
Nasution, non- Profits. data, obtained from accepted
2023) performing Independent the internal of the hypotheses,
Influence loans and Variable: sub-banking which are the
of Non- interest rates Non- financial sector influence of
performin on company Performing company. non-
g loans profits with Loans, performing
and profitability Interest loans towards
interest levels as Rates, profitability
rates on intervening Profitability levels,
company in a Case Laves. influence of
profits Study. non-
with performing
profitabili loans towards
ty levels company
as profits, and
intervenin the influence
g. / of interest
Global rates towards
Economic company
s profits.
Developm
ent

2022 (Pokharel To Dependent Data are collected Findings of

& examined Variable: from annual this studied
Pokharel,20 the impact Return on report Descriptive concluded that
22) of non- assets statistic, Panel impact of
Impact of performing Independent data regression nonperformin
non- assets on Variable: analysis used. g loan on
performing profitability Earning per profitability in
assets on of share; Credit Nepalese
profitability commercial deposit ratio commercial
in Nepalese banks in bank shows
Commercial Nepal. the positive
Banks / impact.
Patan
Pragya
(Volume: 7
Number: 1
 28

2020)
2020 Dependent Panel data The random
(Angela, Investigate Variable: model, effect
Baidoo d the return on Sampling estimation
& impact of asset, Descriptive technique
Ayesu,2 credit risk economic statistic, Panel show that
020) with focus value-added. data regression non-
on non- Analysis used. performing
Investiga performing Independent loans have a
ting the loans on Variable: negative
impact the capital impact on
of credit financial adequacy both measures
risk on perfor ratio, loans of financial
financial mance of and advances performance.
performa commercial ratio, size
nce of banks in and age of
commer Ghana banks
cial
banks in
Ghana
2021 (Singh, The main Dependent The method used The result of
Basuki & objective Variable: for data analysis this research
Setiawan,2 of this Return on in this study is shows that
021) research is Asset multiple ROA, Bank
The Effect to find out (ROA) regression Size, GDP,
of Non- the effect analysis and Inflation
Performin of Non- Independen have a
g Loan on Performin t Variable: significant
Profitabilit g Loan Capital effect on
y: (NPL) of Adequacy NPL but
Empirical Nepalese Ratio CAR does
Evidence conventio (CAR), not have a
from nal banks. Bank Size, significant
Nepalese GDP effect on the
Commerci growth, and NPL of
al Banks/ Inflation banks.
Journal of
Asian
Finance,
Economic
and
Business
2020 ( Do, Ngo Investigate Dependent Secondary Studies
& Phung, d the Variable: data, growth found that
2020) The impact of ROA rate of gross non-
effect of non- domestic performing
 29

non- performing Independent product loans have

performin loans on Variable: (GGDP) is negative
g loans on the ability Non- taken from the impact on
profitabilit to make performing Vietnam the bank’s
y of profit of loan ratio, section of profitability.
commerci Vietnamese Loans to World Ban.
al banks: commercial deposits
Case of bank. ratio, Size of
Vietnam bank, GDP
growth rate
2019 (Jathurika, Purposed Statistical tools The research
2019) of this Dependent used utterly
Impact of investigati Variable: include the revealed
non- on is to ROA, ROE person’s that, non-
performin extend correlation performing
g loans on earlier Independent analysis loans
financial research Variable: and regression significantly
performan on the Non- analysis. influences
ce: A case impact of performing the financial
of Sri Non- loan Ratio performance
Lankan Performin of listed
listed g Loans commercial
commerci on banks in Sri
al banks/ financial Lanka with
Internation performan the negative
al Journal ce relationship.
of
Accountin
g&
Business
Finance
2019 (Gabriel, Identify the Dependent Multiple Multiple
Victor & effect of Variable: regression regression
Innocent, Non- ROA techniques to techniques to
2019) Performing analyze data analyze data
Effect of loan to total Independent collated from the collated from
Non- loans ratio Variable: Central Bank of the Central
Performing on the Non- Nigeria Bank of
Loans on financial Performing Nigeria
the performanc loan, Cash
Financial e of Reserve
Performanc commercial Ratio,
e of banks in Inflation
Commercia Nigeria. Rate
l Banks in
Nigeria
 30

American
Internation
al Journal
of Business
and
manageme
nt Studies
2019 (Nachimuth The Dependent Study is based The
u & Veni, purpose of Variable: on census profitability
2019) the study ROA method. The of the banks
Impact of is to Independent secondary data has reduced,
non- measure Variable: were collected due to rise
performing the impact Ratio of from the in the non-
assets on the of NPAs Gross NPA annual reports performing
profitability on the to Gross assets of the
in Indian profitabilit Advances, scheduled
scheduled y of Indian Ratio of Net commercial
commercial scheduled NPA to net banks in
banks commerci advance, India.
African al banks Ratio of
Journal of gross NPA
Business to total
Managemen assets.
t
2018 (Shaban, Examined Dependent Regression The results
2018) the Non- Variable: analysis demonstrate
Non- Performing Return on Descriptive that the
Performin Assets and Asset statistic , Panel profitability
g Assets their impact Independent data regression of the
and on the Variable: analysis used foreign
Profitabilit profitability Net Non- banks is
y: commercial Performing least
Commerci banks viz. Assets to affected by
al Banks public and Net the NPAs
in India private Advance compared to
SCMS banks and and Gross public and
Journal of foreign Non- private
Indian banks in Performing banks.
Managem India. Assets to
ent, Gross
Advance
2018 (Gautam, The
2018) Examined Dependent Data are concluded
Impacts of the impact Variable: collected from that the non-
non- of non- Return on annual report performing
performing performing Assets Descriptive loan to total
 31

loans on loan on (ROA) , statistic, Panel loan, credit to

profitability profitability Return on data regression deposit ratio,
of Nepalese of Nepalese equity analysis used. net profit to
Commercia commercial (ROE) loan and
l banks banks advance and
national Independent interest
journal of Variable: income to
arts, Total credit loan and
commerce to deposit advance are
& scientific ratio (CDR, important
research Net profit to variables to
review loan and influence the
advance(NP profitability
LA), Non- of the
performing commercial
loan to total banks of
liability Nepal.
(NPLTL),
Interest
income to
total loan
and advance
(IILA)
2017 (Mitai ,20 What is the The study used The study
effect of Dependent secondary data indicates that
17) The
ownership Variable: to analyze there negative
effect of on the ROA, ROE effect of non-
impact of performing
non-
NPL? Independent loans ratio on
performin Variable: return on
Capital assets,
g loans on
Adequacy, confirming
the Assets that non-
Quality, performing
financial
Liquidity, loans
performan Operational negatively
Cost affects
ce of
Efficiency profitability of
commerci commercial
banks in
al banks in
Kenya
Kenya.
Journal of
Economic
s, Fiancé
 32

and
Business
2.3 Research Gap
Researchers can identify research gaps by reviewing the existing literature, analyzing
current theories and practices, and assessing the limitations of previous studies. Once
identified, researchers can formulate research questions and hypotheses that address the
research gap and design studies to collect data to fill the gap (Shaban, 2018).
Many researchers have conducted the research on the topic of non-performing loan of
Development banks in Nepal but they were based on determinant, causes, factors of the
non-performing loan and were not able to analyses the impact of non-performing loan on
profitability of Development bank in Nepal (Angela, Baidoo & Ayesu,2020). The
previous researcher conducted could not explain the Total credit to deposit ratio (CDR),
Net profit to loan and advance (NPLA), Non-performing loan to total liability (NPLTL),
Interest income to total loan and advance (IILA). This study fulfilled the gap by
analyzing the impact of Non-performing loan on profitability (Gautam, 2018). This
research has tried to study the impact of non-performing loan on profitability of the three
banks in Nepal i.e. MBBL, NDBL, EDBL. While reviewing through previous research
there is no study found that has used the profitability indicator profit margin ratio and
loan ratio.so, this study fulfilled the gap by analyzing the relationship of NPL and
Profitability.The previous research is only limited to financial and statistical analysis of
profitability position of Development banks of Nepal. It has been unable to clarify on
profitability and demonstrate on whether there exists a significant profitability in
Nepalese banking industry. It is therefore the first attempt to make research on these
ratios relationship in overall banking industry (Singh, Basuki & Setiawan, 2021).
Chapter III
Research Methodology
Research is essentially a systematic inquiry seeking facts through objective verifiable
methods in order to discover the relationship among them and to deduce from them broad
principles or laws. It is really a method of critical redefining problems formulating
hypothesis or suggested solution. Collecting, organizing and evaluating data, making
deductions and making conclusions to determine whether they fit the formulated
 33

hypothesis. Thus the term ‘research’ refers to a critical, careful and exhaustive
investigation or inquiry or examination or experimentation having as its aim the revision
of accepted conclusion, in the light of newly discovered facts.

Research methodology is a systematic way to solve a problem. It is a science of studying

how research is to be carried out. Essentially, the procedures by which studies go through
their work describing, explaining and predicting phenomena are called research
methodology. This chapter therefore explains the methodology that is employed in this
study, which includes various sections describing research plan and design, description of
the sample, instrumentation, data collection procedure and time frame, validity and
reliability of the study, and analysis plan. In the absence of methodology, it is likely that
the conclusions drawn may be misunderstood.

This research methodology sets out overall plan associated with a study. It provides a
basic framework on which the study is based. Before presenting the analysis and
interpretation of data, it is necessary that research methodology be described first. In the
absence of methodology, it is likely that the conclusions drawn may be misunderstood.
This chapter therefore explains the methodology employed in this study. This study
attempts to have an insight into the impact of assets and liabilities management on
profitability of Nepalese Development banks. A sound and systematic methodology is
required to carry out any study, if it is to be worthwhile.

This chapter is designed to throw light on the methodology used to undertake this study,
which aims at analyzing the overall impact of assets and liabilities management on
profitability of Nepalese commercial banks and drawing some patient conclusion from
this. For this purpose, the following research methodology has been adopted which
includes research design, procedures of gathering data, data collection, processing of
data, procedure of analysis and the various profitability indicators used.

3.1 Research Design

The research design is based on descriptive and causal comparative research. The
descriptive research design has been adopted for fact-finding and operation searching for
adequate information the fundamental issues associated with banks assets and liabilities
 34

management and profitability in Nepalese commercial banks. The descriptive research

design has been adopted for fact finding and searching adequate information about
factors affecting financial performance. Such design involves the systematic collection
and presentation of data to give clear picture of a particular situation. It describes the real
and actual condition, situation and facts. The descriptive research includes multiple
variables for analysis such as descriptive statistics, correlation matrix and regression
analysis from which the best fitted models are developed and then analyzed. Hence, the
research design adopted in this is of descriptive type.

3.2 Population and Sample

The population of this study is all Development banks in Nepal. There are 17
Development banks in Nepal out of them; three banks are taken as sample for the study.
For the purpose of the study convenience sampling under non-probability sampling
method was used to analysis. The sample banks are. Muktinath Bikas Bank Limited
(MBBL) Narayani Development Bank Limited (NDBL) Excel Development Bank
Limited (EDBL)

3.3 Nature and Sources of Data

The study based on the secondary data which are gathered for Development banks in
Nepal for the period of 10 years from 2012/13 to 2022/23. The data for independent
variables like Total credit to deposit ratio (CDR), Net profit to loan and advance (NPLA),
Non-performing loan to total liability (NPLTL), Interest income to total loan and advance
(IILA) are taken from the respective websites and annual reports of the selected
Development banks.

3.4 Methods of Data Analysis

This section deals with statistical and econometric models used for the purpose of
analysis of secondary data. Descriptive, co-relation and regression methods of analysis
are used in the study. The descriptive statistics contains mean, standard deviation,
minimum and maximum values of variables which used to explain the characteristics of
sample firms. The correlation analysis is used to measure the direction and magnitude of
relationship between dependent and independent variables. The regression analysis is
 35

used to find out the influence of independent variable over dependent variable solely and
combined with other variables. It explains the different statistical tests of significance for
validation of model like t-test, F-test, detection of and linear regression analysis. All
models are tested for individual effects by running F-test using statistical package for
social science (SPSS).

Return on Assets
Return on assets is the relationship between profit and total assets of a firm on a given
date. It measures the profitability of a firm’s assets or the amount of net income it earns
in relation to the assets available for use. The return on total assets ratio indicates how
well a company’s investments generate value, making it an important measure of
productivity for the business. It is calculated by dividing the company’s earnings after
taxes (EAT) by its total assets, and multiplying the result by 100%.
Return on assets (ROA) =
Total credit to deposit ratio (CDR)

The CD ratio refers to the credit-deposit ratio in banking parlance. It tells us how much of
the money banks have raised in the form of deposits has been deployed as loans. The
loan-to-deposit ratio (LTD) is a commonly used statistical tool for assessing a bank's
liquidity by dividing the bank's total loans by its total deposits. This number is expressed
as a percentage.

Total credit to deposit ratio (CDR) =Total Deposits/Total Credit

Net profit to loan and advance (NPLA)

The ultimate goal here is to ensure that the bank is being adequately compensated for the
risks it is taking in its lending business. It is used mainly for computing a risk-adjusted
return.

Net Profit to loan and Advance(NPLA) = Net Profit / Total Loan

Non-performing loan to total liability (NPLTL)

The net NPA to loans (advances) ratio is used as a measure of the overall quality of the
bank's loan book. A nonperforming loan (NPL) is a loan that is in default due to the fact
 36

that the borrower has not made the scheduled payments for a specified period. Although
the exact elements of nonperforming status can vary depending on the specific loan's
terms, "no payment" is usually defined as zero payments of either principal or interest.

Interest income to total loan and advance (IILA)

This ratio shows how much a bank has earned by the way of net interest income after
deducting all the costs incurred on earning the interest income. Higher the spread higher
will be the efficiency of the banks and affects positively the profitability of the banks
(Sharma, 2016)

Interest income to total loan and advance (IILA) = Interest income / total loan and
advance

Statistical Tools

3.5.2 Statistical Tools

Various statistical tools may be used for the evaluation of financial performance of the
banks such as Correlation Analysis, Measure of Central Tendency, Theory of Dispersion,
and Estimation whatever is required. "Statistical analysis is one particular language
which describes the data and makes possible to talk about the relations and the difference
of the variables. Statistical tools are the mathematical techniques used to analyze and
interpret performance. It is used to describe the relationship between variables and
interpret the result. Statistics is also used to test the hypothesis that is set to know the
information of population. In this study, the following statistical tools are used:
3.5.2 Statistical Tools
Various statistical tools can be used to assess a bank's financial performance, including:
Correlation analysis, central tendency measurements, scattering theory and estimation,
whatever you need. “Statistical analysis is a specific language that allows us to describe
data and talk about relationships and differences between variables. Statistical tools are
mathematical techniques used to analyze and interpret performance. Used to describe
relationships between interpretations. Statistics are also used to test hypotheses that are
set to learn information about a population. The following statistical tools were used in
this study.
 37

Standard Deviation
The measurement of the scatterings of the mass of figures in a series about an average is
known as dispersion. S.D. is an absolute measurement of dispersion in which the
drawbacks present in other measures of dispersion are removed. The high amount of
dispersion reflects high standard deviation. The small standard deviation means the high
degree of homogeneity of the observations. In simple term high SD means very less
similarity in the values and low SD means high similarity among the values. SD gives the
accurate result.
σ =√ ∑ ¿ ¿ ¿ ¿
Where,
X = number of observations in the sample
X = mean of number of observations in the sample
n = number of years
¿ = Sum of Total number of observations deviation from mean in the sample.

Coefficient of Variation (CV)

The coefficient of variation (CV) is a statistical measure of the dispersion of data points
in a data series around the mean. The coefficient of variation expresses the ratio of the
standard deviation to the mean and is a useful statistic for comparing the degree of
variation from one data set to another, even when the means differ significantly. . Less
CV is the more uniformity and consistency and vice versa. Only standard deviation is not
appropriate to compare two pairs of variables but also CV is capable to compare two
variables independently in terms of their variability. It is calculated as under:
σ
C.V = * 100
X

Correlation Coefficient (r)

Correlation coefficient is defined as the association between the independent Variable
and independent variable. Correlation coefficients are used to measure how strong a
relationship is between two variables. Two variables are said to have correlation when the
 38

value of one variable is accompanied by the change in the value of the other. Therefore, it
is measured by following formula using two variables. It is denoted by small ' r'

n ∑ XY −∑ X ∑ Y
Correlation Coefficient (r) =
√n ∑ X −¿ ¿ ¿
2

Multiple Regressions
A multiple regression analysis is performed to identify the relationship between liquidity
and profitability. Liquidity is the independent variable here. Profitability is the dependent
variable and can be expressed as:
ROA = β 0+ β 1 CDR+ β 2 NPLA + β 3 NPLTL+ β 4 IILA + e
ROA Return on Assets
CDR Total Credit to Deposit Ratio
NPLA Net Profit to Loan and Advance
NPLTL Non-Performing Loan to Total Liability
IILA Interest Income to Total Loan and Advance
e error
B0, B1, B2, B3, B4 Are the Parameter of the independents Variable

3.5 Research Framework and definition of Variable

The conceptual framework of the study describes systematic explanations of the
relationship between dependent and independent variables with the aim of clarifying
Impact of non-performing loan on profitability of development banks in Nepal. This
section provides a conceptual framework for the study and describes the variables
studied. In this study, the dependent variable is return on assets. Independent variable
Total credit to deposit ratio (CDR), Net profit to loan and advance (NPLA), Non-
performing loan to total liability (NPLTL), Interest income to total loan and advance
(IILA).Therefore, the following conceptual model is designed to summarize the main aim
and scope of this study.
 39

Independent Variable Dependent Variable

Total credit to deposit

ratio (CDR)

Net profit to loan and

advance (NPLA)

Return on Assets (ROA)

Non-performing loan to
total liability
(NPLTL)

Interest income to total

loan and advance
(IILA)

Soures: (Gautam, 2018)

Return on Assets
Return on assets is the relationship between profit and total assets of a firm on a given
date. It measures the profitability of a firm’s assets or the amount of net income it earns
in relation to the assets available for use. The return on total assets ratio indicates how
well a company’s investments generate value, making it an important measure of
productivity for the business. It is calculated by dividing the company’s earnings after
taxes (EAT) by its total assets, and multiplying the result by 100%.
Return on assets (ROA) =
Total credit to deposit ratio (CDR)
The CD ratio refers to the credit-deposit ratio in banking parlance. It tells us how much of
the money banks have raised in the form of deposits has been deployed as loans. The
loan-to-deposit ratio (LTD) is a commonly used statistical tool for assessing a bank's
liquidity by dividing the bank's total loans by its total deposits. This number is expressed
as a percentage.
 40

Total credit to deposit ratio (CDR) =Total Deposits/Total Credit

Net profit to loan and advance (NPLA)

The ultimate goal here is to ensure that the bank is being adequately compensated for the
risks it is taking in its lending business. It is used mainly for computing a risk-adjusted
return.
Non-performing loan to total liability (NPLTL)
The net NPA to loans (advances) ratio is used as a measure of the overall quality of the
bank's loan book. A nonperforming loan (NPL) is a loan that is in default due to the fact
that the borrower has not made the scheduled payments for a specified period. Although
the exact elements of nonperforming status can vary depending on the specific loan's
terms, "no payment" is usually defined as zero payments of either principal or interest.
Interest income to total loan and advance (IILA)
This ratio shows how much a bank has earned by the way of net interest income after
deducting all the costs incurred on earning the interest income. Higher the spread higher
will be the efficiency of the banks and affects positively the profitability of the banks
(Sharma, 2016)

CHAPTER IV
RESULT AND DISCUSSION
This chapter has been organized to present the result, analysis and interpret them
accordingly. Its main objective is to present data and facts and interpret them. Data
collected from various sources were classified and tabulated as requirement of the study
and in accordance to the nature of collected data. Different types of financial and
statistical tools are used in this chapter.
4.1 Data Presentation and Analysis
Data presentation and analysis refers to the process of organizing, summarizing, and
interpreting data to derive meaningful insights and make informed decisions. It involves
 41

using various techniques and tools to explore patterns, relationships, and trends in the
data.
4.1.1 Average of mean, Standard deviation and Coefficient of variance
Table 4.1
Average of mean Stander deviation and CV
Mean Std. Deviation CV
ROA 1.87 0.47 25.098
CDR 84.37 5.57 6.6
NPLA 2.94 1.32 45.006
NPLTL 2.85 1.013 35.54
IILA 11.63 1.2 10.372
Sources: SPSS output
Table 1 indicates the position of average of mean Stander deviation and CV over the 10
Years 3 Development Bank mean, Standard deviation, and Coefficient of Variation. The
ROA is mean, Std. Deviation and CV is 1.87, 0.47 and 25.098%. . The CDR is mean,
Std. Deviation and CV is 84.37, 5.57and 6.6%. . The NPLA is mean, Std. Deviation and
CV is 2.94, 1.32, and 45.006%. . The NPLTL is mean, Std. Deviation and CV 2.85, 1.013
and 35.54%. . The IILA is mean, Std. Deviation and CV is 11.63, 1.2 and 10.372. The
mean CDR of is 84.37 greeter than mean CDR of ROA, NPLA, NPLTL and IILA
Showing CDR has greater performance than other Variable. The SD of ROA is 0.47
lesser than other CDR, NPLA, NPLTL and IILA lesser risk. Similarly CV of NPLA is
45.006% lesser then CDR ROA, CDR, NPLTL and IILA showing grater Consistency.

4.1.2 Descriptive Table

Descriptive statistics are brief descriptive coefficients that summarize a given data set,
which can be either a representation of the entire or a sample of a population. Descriptive
statistics are broken down into measures of central tendency and measures of variability
(spread). Measures of central tendency include the mean, median, and mode, while
measures of variability include the standard deviation, variance, and the minimum and
maximum variables.
Table 2
Descriptive Statistics
 42

Std.
N Minimum Maximum Mean
Deviation
ROA 30 0.55 3.21 1.87 0.71
CDR 30 59.45 107.01 84.37 10.68
NPLA 30 0.91 4.83 2.94 1.02
NPLTL 30 0.48 5.46 2.85 1.42
IILA 30 7.71 13.93 11.04 1.63
Sources: SPSS output
Table 2 the descriptive statistics for the selected variables considered in this study. Their
Return on asset has a minimum value of 55 percent and a maximum of 321 percent with
average of 187 percent. Stander deviation is 71 percent. Their CDR has a minimum value
of 55.45 percent and a maximum of 107.01 percent with average of 84.37 percent.
Stander deviation is 10.68 percent. NPLA, NPLTL and IILA minimum value of 0.91,
0.48, 7.71 percent respectively. NPLA, NPLTL and IILA maximum value of 4.83, 5.46,
13.93 percent respectively. NPLA, NPLTL and IILA mean value of 2.94, 2.85, and 11.04
respectively. NPLA, NPLTL and IILA stander deviation value 1.02, 1.42, and 1.63
respectively.
4.1.3 Pearson’s Correlation Analysis
Correlation is a statistical technique that can show whether and how strongly pairs of
variables are related. A correlation between variables indicates that as one variable
changes in value, the other variable tends to change in a specific direction. Understanding
that relationship is useful because we can use the value of one variable to predict the
value of the other variable.
Table 3
Correlations

CDR CDR NPLA NPLTL IILA

Pearson
CDR 1
Correlation

Pearson
CDR .432* 1
Correlation

Pearson
NPLA .488** 0.122 1
Correlation
 43

Pearson -
NPLTL 0.25 0.053 1
Correlation 0.119
Pearson
IILA .565** 0.323 0.337 .527** 1
Correlation
*. Correlation is significant at the 0.05 level (2-tailed).
**. Correlation is significant at the 0.01 level (2-tailed).
Sources: SPSS output
Table 3 shows the Pearson correlation coefficient between dependent and independent
variables taken in the study. The result shows a positive relationship of return on assets
with total credit to deposit ratio (CDR), net profit to loan and advance (NPLA), non-
performing loan to total liability (NPLTL) and interest income to total loan and advance
(IILA). It indicates that larger the total credit to deposit ratio (CDR), net profit to loan
and advance (NPLA), non-performing loan to total liability (NPLTL) and interest income
to total loan and advance (IILA), higher the return on assets.
4.1.4 Multiple Regressions
To investigate the connection Impact of Non-Performing Loan on Profitability of
Development banks in Nepal businesses, a multiple regression analysis is carried out.
Finding the influence of predictors (independent variables) on the dependent variables is
the goal of regression analysis. The linear equation with one or more independent
variables and the coefficients that best predicted the value of the dependent variable can
be estimated using regression.

4.4.1 Model SUMMARY

Table 4
Impact of CDR, NPLA, NPLTL, IILA on CDR

Model Summary

Model R R Square Adjusted R Square Std. Error of the Estimate

1 0.903a 0.695 0.514 0.55
a. Predictors: (Constant), CDR, NPLA, NPLTL, IILA
Sources: SPSS output
 44

Table 4 show the model summary of data. The multiple Correlation Coefficients are 0.903
and the coefficient of coefficient of determination is 0.695 which Show that only 69.5%
variation in CDR is explained by independent variable and CDR, NPLA, NPLTL, IILA.
4.4.2 ANOVA TABLE
Table 5
Impact of CDR, NPLA, NPLTL, IILA on CDR

ANOVAa

Sum of
Model Squares Df Mean Square F Sig.
1 Regression 7.320 4 1.830 6.123 0.001b

Residual 7.471 25 0.299

Total 14.791 29
a. Dependent Variable: Return on Assets CDR

b. Predictors: (Constant), CDR, NPLA,NPLTL, IILA

Sources: SPSS output

Table 5 show the ANOVA. The ANOVA test shows that the significant value is 0.01
greater than level of significance 0.05 showing that the overall regression model is
significant.

4.4.3 Coefficients Impact of CDR, NPLA, NPLTL, IILA on CDR

Table 6
Coefficients
Impact of CDR, NPLA, NPLTL, IILA on CDR
Coefficientsa
Unstandardiz Standardi
ed zed
Coeffici Coefficie
ents nts
Std.
Model B Error Beta t Sig.
1 (Const -2.155 0.9 - 0.0
 45

ant 29 2 2
) . 9
3
2
0
CDR 4.0 0.0 0.312 36. 0.0
5 0
4 6
3 4
NPLA 3.2 0.1 0.348 30. 0.0
0 0
7 3
7 2
NPLT 3.0 0.0 0.120 33. 0.0
L 2 0
6 5
2
IILA 8.1 0.8 0.284 10. 0.0
0 0
1 6
5 9
a. Dependent Variable: Return on Assets(ROA)%
Sources: SPSS output
Table 6 shows the coefficient analysis of CDR and independent Variable. The P value of
NPLA 0.0064 lesser than Significance level 0.05. It is shows the relation between NPLA
and CDR is significant. The beta coefficient of NPLA is 0.245 which shows that for
increment in the value NPLA, the value of dependent variable CDR increases by 0.2319
units. The P value of CDR, NPLIT and IILA is 0.0032, 0.005, and 0.0069 receptively
lesser than significant level 0.05.
4.2 Major Finding
 The position of average of mean Stander deviation and CV over the 10 Years 3
Development Bank mean, Standard deviation, and Coefficient of Variation. The
ROA is mean, Std. Deviation and CV is 1.87, 0.47 and 25.098%. . The CDR is
mean, Std. Deviation and CV is 84.37, 5.57and 6.6%. . The NPLA is mean, Std.
Deviation and CV is 2.94, 1.32, and 45.006%. . The NPLTL is mean, Std.
Deviation and CV 2.85, 1.013 and 35.54%. . The IILA is mean, Std. Deviation
and CV is 11.63, 1.2 and 10.372. The mean CDR of is 84.37 greeter than mean
CDR of ROA, NPLA, NPLTL and IILA Showing CDR has greater performance
 46

than other Variable. The SD of ROA is 0.47 lesser than other CDR, NPLA,
NPLTL and IILA lesser risk. Similarly CV of NPLA is 45.006% lesser then CDR
ROA, CDR, NPLTL and IILA showing grater Consistency.
 The descriptive statistics for the selected variables considered in this study. Their
Return on asset has a minimum value of 55 percent and a maximum of 321
percent with average of 187 percent. Stander deviation is 71 percent. Their CDR
has a minimum value of 55.45 percent and a maximum of 107.01 percent with
average of 84.37 percent. Stander deviation is 10.68 percent. NPLA, NPLTL and
IILA minimum value of 0.91, 0.48, 7.71 percent respectively. NPLA, NPLTL and
IILA maximum value of 4.83, 5.46, 13.93 percent respectively. NPLA, NPLTL
and IILA mean value of 2.94, 2.85, and 11.04 respectively. NPLA, NPLTL and
IILA stander deviation value 1.02, 1.42, and 1.63 respectively.
 The Pearson correlation coefficient between dependent and independent variables
taken in the study. The result shows a positive relationship of return on assets
with total credit to deposit ratio (CDR), net profit to loan and advance (NPLA),
non-performing loan to total liability (NPLTL) and interest income to total loan
and advance (IILA). It indicates that larger the total credit to deposit ratio (CDR),
net profit to loan and advance (NPLA), non-performing loan to total liability
(NPLTL) and interest income to total loan and advance (IILA), higher the return
on assets.
 The model summary of data. The multiple Correlation Coefficients are 0.903 and
the coefficient of coefficient of determination is 0.695 which Show that only
69.5% variation in CDR is explained by independent variable and CDR, NPLA,
NPLTL, IILA.
 The ANOVA. The ANOVA test shows that the significant value is 0.01 greater
than level of significance 0.05 showing that the overall regression model is
significant.
 The coefficient analysis of CDR and independent Variable. The P value of NPLA
0.0064 lesser than Significance level 0.05. It is shows the relation between NPLA
and CDR is significant. The beta coefficient of NPLA is 0.245 which shows that
for increment in the value NPLA, the value of dependent variable CDR increases
 47

by 0.2319 units. The P value of CDR, NPLIT and IILA is 0.0032, 0.005, and
0.0069 receptively lesser than significant level 0.05.
2.3 Discussion
The management of the organization always takes Non-Performing loan and profitability
into consideration when assessing the company's financial standing. This study aimed to
look into impact of Non-Performing loan on Profitability of development banks in Nepal.
Using both a descriptive and research approach, the study was conducted. In order to
provide an answer to a research issue, study data was methodically gathered over a ten-
year period. This study used a sample of three Nepali development banks in Nepal.
Secondary sources, such the annual reports of the life insurance firms, were used to
collect the data. The following precise objectives have been developed to support the
proposal: In order to assess the financial health and Non-Performing loan and
profitability f Nepalese Development Bank. (Gautam, 2018) the result showed that beta
coefficient for credit to deposit ratio, net profit to loan and advances, non- 23 performing
loan to total loan, interest income to loan and advance are positive on return on assets.
(Gabriel, Victor and Innocent, 2019) the study showed that NonPerforming loans to total
loans ratio and cash reserve ratio had statistically negative significant effect on Return on
Asset. These result showed that a high level of non-performing loans would reduce the
financial performance of commercial banks in Nigeria
 48

CHAPTER – V
SUMMARY AND CONCLUSION
5.1 Summary
Impact of non-performing loan on profitability of development Banks in Nepal the basic
objective of the study is to analyze the NPL management of Development banks as well
as to compare it. To examine the impact of non-performing assets on profitability of
development banks in Nepal. To analyze the impact of non-performing assets of
development banks in Nepal. The study is impact of non-performing loan on profitability
of development banks in Nepal. Profitability is measured by Return on Assets (ROA) and
Capital Adequacy Ratio, Inflation Rate, Leverage Ratio (LR), Liquid Assets to Total
Assets (LAR), Loan to Deposit Ratio (LDR), Cash reserve ratio (CRR). Other CAMEL
factors affecting profitability were considered as control variables. The control variables
considered are; Capital Adequacy Ratio, Inflation Rate, Leverage Ratio(LR), Liquid
Assets to Total Assets (LAR), Loan to Deposit Ratio (LDR), Cash reserve ratio (CRR).
This study was conducted through the use of a descriptive design. The Population of
study comprised of the entire 3 Development Banks that have been licensed by Central
Bank of Nepal. The secondary data in this analysis covered a period of 10 years from
2012 to 2022.SPSS 25 was used to analyze the data. Lending is the most profitable
investment for commercial banks but non-performing loan has effect on profitability of
the commercial banks. The major objective of this study is to examine the effect of loan
specific factors that affect the profitability of Nepalese commercial banks. The factors
such as non-performing loans to total loans (NPLTL) and credit to deposit ratio (CDR),
net profit to loan and advance (NPLA) and interest income to loan and advance (IILA)
affect the profitability of Nepalese commercial bank. Therefore, the R-square results for
both models show that the mentioned independent variables are important variables to
influence the profitability of the commercial banks of Nepal.
5.2 Conclusion
To analysis the data different tool has been used such as statistical tool like coefficient of
correlation, regression, financial tools. Financial tools included profitability ratio under it
included Capital Adequacy Ratio, Inflation Rate, Leverage Ratio(LR), Liquid Assets to
Total Assets (LAR), Loan to Deposit Ratio (LDR), Cash reserve ratio (CRR). The data
 49

that have been analyzed by financial and statistical tool include from 2012 year to 2022
year. This study is mainly conducted on the basis of secondary data. Therefore, the study
has inherent limitation of the secondary data.
5.3 Implication
The study has also several implications pointing to interesting avenues for future
research. Some implication and suggestion for future research are discussed here.

 The provisions made by Nepal Rastra Bank determine the provisioning to be

made for the non-performing loan i.e. these provisions decrease the profit. So, not
only amount of non-performing loan but these provisioning also rule also
determines the profitability.
 The study helps to fulfill the gap of proper research about the relationship
between NPL and profitability. It may provide the knowledge about NPL
management in Nepalese Development banks and their profitability position.
 While lending the loan to borrowers, banks have to take all the necessary steps
honestly without skipping any of the steps in the procedure. If bankers skip any of
the important procedures that may lead to default of the loan.
 The bankers has to take corrective measures to avoid default i.e., data analysis on
regular interval for the prediction of defaulter and take necessary action on
predicted defaulter in advance.
 50

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