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Background of the study
A bank is a type of financial institution which acts as an intermediary or a bridge between surplus and deficit units. It gets funds from the depositor i.e. surplus unit and provides credit to the borrowers i.e. deficit unit. (Abel, 2018) It has an important role in developing the economy of the country as they make an investment in productive sectors (Richard, 2011). One of the major activities of the bank is to provide loan to the individuals or businesses. Loan is a major earning asset of the bank since it charges interest on loans at different rates. However, lending is a risky business. (Stewart, 2003) Loan is the riskiest asset because there is a risk that the customers might not pay back the loan amount and the principal on time which will affect the performance of the bank. This type of risk is known as the credit risk which the financial institutions including the commercial banks are most prone to. The problem of credit default which is also known as non-performing loans (NPL) has been growing nowadays due to which it is becoming an alarming issue in the banking industry.
Non-performing loans have become an important issue as it can affect the profitability of the bank. The non-performing loan to total loans ratio also known as NPL rate indicates how a bank is managing its credit. The high NPL ratio means the bank is not able to manage its credit risk and it also indicates that the bank does not have efficient and effective credit recovery system. This might affect the reputation of the bank due to which its customer base will be affected. Similarly, the high NPL ratio means the bank having ineffective credit management and recovery system and is more prone to credit
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risk. Thus, the bank maintains a certain percentage of its total loan and advances as a provision for possible loan losses to reduce the default risk. At the most general level, NPL is a loan where a borrower is not making repayments in accordance with contractual obligations. (Bholat, D., Lastra, R. and Markose, S., 2016) The Basel Committee on Banking Supervision (2012) has recommended 29 principles for effective banking supervision of which the principles regarding the management of credit risk, identification of problem assets and maintenance of adequate provisions and reserves, prudential limits to restrict bank exposures to single counterparties or groups of connected counterparties and checking for related parties lending directly related to assets quality and credit risk management. This indicates that assets quality including the loan quality is of general concern to financial supervisory authorities in countries throughout the world (Abata, 2014).
Nepal is also facing banking crisis and some of the bank and financial institutions have already failed during last few years and are in the process of liquidation (Sapkota, 2011). Studies show that the failure of banks in Nepal was also the result of the high non-performing assets, lending without differentiating markets, products and borrowers’ credit worthiness and excessive loan exposure to real estate (Sapkota, 2011). In the past before 2001, Nepal bank limited and RBBL nearly collapsed due to high non-performing loan of over fifty percent of their total assets. Because of which NRB with the support of IMF and World Bank adopted a reform program (Ahikary, 2007).
In Nepal, NPL is the loan which comes under watchlist, substandard, doubtful and bad loans according to the NRB directives, 2074. The non-performing loans of Nepalese commercial banks have increased in the 1st quarter of 2017/18 compared to the
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corresponding quarter of fiscal year 2016/17 from 1.64% to 1.77%. Nepal SBI Bank has the lowest rate of NPL at 0.13% followed by Sanima Bank Ltd (0.14%), Standard Chartered Bank Nepal Ltd (0.18), Everest Bank Ltd (0.26%) and NIC Asia Bank Ltd (0.29%). Civil Bank Ltd has the highest NPL among the commercial banks in Nepal. NRB has prescribed bank to keep its NPL below 5% of its total loans above which it will attract prompt corrective action from NRB. (My Republica, 2017)
From this data, it can be seen that the Civil Bank Ltd is incurring the problem of high Non-performing loan ratio which has a direct impact on the profitability of the bank.
1.2. About the Bank
Civil Bank Limited (CiBL) is a public company founded on November 26, 2010 in Nepal. It is an ?A? class financial institution licensed by Nepal Rastra Bank (NRB). Its head office is in Kamaladi, Kathmandu and has branches all across the country through which it provides entire banking services in Nepal.
The bank was established with a paid up capital of NPR 1.20 billion. It merged with (former) International Leasing and Finance Company Limited to reach its target of NPR 8 billion in paid-up capital. The bank has moved towards diversification through the acquisition of Civil Capital Market Limited and looks to the future to offer various services related to mutual fund activities, portfolio management, and other merchant banking services through this subsidiary. (Civil Bank)
1.3. Problem Statement
Profitability is considered as a benchmark for evaluating the performance of any business enterprise including the banking industry. However, in the process of making an
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investment and providing loans to the customer the bank is more prone to the default risk i.e. credit risk. This has a direct impact on the profitability of the bank. Moreover, the NRB has prescribed banks and financial institution to recognize interest income only when it realized in the cash form. Also, they have to create a provision for possible loan losses at the rate of 1%, 5%, 25%, 50% and 100% which will be shown in the income statement as an expense leading to the loss in profit of the bank. Also, creating and maintaining a loan loss provision incur the opportunity costs i.e. the amount which has been kept as a provision for loan losses could have been invested elsewhere and provide earnings.
Civil Bank Ltd has the highest NPL rate among the commercial banks which shows that it is more prone to credit risk and if this trend continues for the long run, it will create a problem for the bank even the bank run. So, this study is undertaken to examine the impact of NPL on the profitability of Civil Bank Ltd.
The objective of this study is
? To examine the impact of non-performing loans on the profitability of Civil Bank Ltd.
? To provide solutions to reduce the incidence of increasing trend of non-performing loans of Civil Bank Ltd.
1.4. Research Question
The research question for this study is
? What is the impact of non-performing loans on the profitability of Civil Bank Ltd?
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1.5. Significance of the study
The main significance of this study is to address the basics of the stated problem. In addition, the researcher has attempted to provide solutions to the problem and help the bank to achieve its goals. Also, it is believed that the results of this study have the following contributions;
? Enrich the knowledge of the readers on the impact of the non-performing loan on bank profitability
? Enable the bank to take necessary measures to control occurrences of non-performing loans
? Provide more literature to support existing theoretical propositions on the effects of nonperforming loans on the profitability of commercial banks and provide a basis for further studies
1.6. Organization of the study
The research is organized is as follows.
Chapter 1 ?Introduction? analyzes the background of the study and the bank, the articulated research objectives, problem statement, research question and significance of the study.
Chapter 2 ?Literature Review? includes the review of various pieces of literature in the field of NPL and its impact on the profitability of the Civil Bank Ltd. This section also includes the conceptual framework and the research gap of the study.
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Chapter 3 ?Methodology? describes the methodology employed in this study by the researcher including the research design, data collection method and procedure and data analysis and empirical model.
Chapter 4 ?Findings? explores the results that the researcher got from the SPSS. It also includes the analysis of the findings.
Chapter 5 ?Recommendation? provides the proposed change programs and the implementation plan that the researcher has recommended to the Civil Bank Ltd including the strategies that are employed by the bank to minimize the incidence of NPL.
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CHAPTER 2: LITERATURE REVIEW
2.1. Introduction
In this chapter, it contains the review of various kinds of literature that are relevant for conducting the research on the impact of non-performing loans on the bank profitability.
2.2. Non-performing loan and Provisioning
There are various definitions of a non-performing loan. Its definitions differ according to the countries.
?A loan is nonperforming when payments of interest and/or principal are past due by 90 days or more, or interest payments equal to 90 days or more have been capitalized, refinanced, or delayed by agreement, or payments are less than 90 days overdue, but there are other good reasons5 —such as a debtor filing for bankruptcy—to doubt that payments will be made in full.? (IMF, 2005)
According to the Unified Directive issued by NRB, the total loans and advances extended by a bank have to be classified on different types based on the expiry of the deadline of repayment of the principal and interest.
a. Pass: Loans/advances which are not overdue or are overdue up to a period of three months are classified as pass loans on which 1% provision should be maintained.
b. Watchlist: Loans/advances which have met all the criteria for a good loan but have some signs of vulnerability are classified as watchlist loans on which 5% provision is to be maintained. For example, a loan provided to a firm by
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keeping receivable amount as a security but this loan will not be collected in the next three months.
c. Sub-standard: Loans/advances which are overdue by a period from three months to a maximum period of six months are classified as sub-standard loans on which 25% provision should be maintained.
d. Doubtful: Loans/advances which are overdue by a period from six months to a maximum period of one year are doubtful loans on which 50% provision is maintained.
e. Loss: Loans/advances which are overdue by a period of more than one year are loss loan on which the full amount should be maintained as a provision i.e. 100%.
The loans which are in pass class and watchlist class are called the performing loan, and the sub-standard, doubtful and loss categories are called non-performing loans. Note: Loans/advances also include bills purchased and discounted.
In this study, a non-performing loan ratio measured by non-performing loans over total loans and advances and loan loss provision over total loans and advances are used as an independent variable.
2.3. Profitability of banks
For surviving in the competitive banking industry, profit is essential. Also, it is the cheapest source of funds. The bank should see the profit not only as a measure of performance but also as a necessity to succeed in growing financial markets. (Ing) When a firm generates income that exceeds the business expenses incurred during the same
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period of time, this situation is known as profitability. (Sanni, 2006) Profit is a soul of business for a profit-oriented firm. There are various indicators to measure the profitability which includes return on assets (ROA), return on equity (ROE) and net interest margin (NIM). However, there are diverse views among the scholars regarding which one is the good measure of profitability. For instance, Goudreau and Whitehead (1989) and Uchendu (1995) believed that the three indicators namely ROA, ROE, and NIM are all good whereas Hancock (1989) used only ROE and Odufulu (1994) used only the gross profit margin to measure the profitability. For this study, ROA is taken as an indicator to measure the profitability of the bank as it indicates how well the total assets of the bank are used to generate profits. It is widely used as a measure of bank performance and profitability while establishing the regression model. (Wheelock, R. Alton Gilbert and David C., 2007).
2.4. Empirical Evidence
There are various works of literature which determine the relationship between non-performing loans and profitability. Michael et al. (2006) emphasized that non-performing loans in the loan portfolio affect operational efficiency which will ultimately affect the profitability, liquidity, and solvency position of banks. Berger et al. (1997) connected problematic loans with cost efficiency, which in turns affect the profitability of the commercial banks. Chang (1999) believed that non-performing loan can be treated as an undesirable cost to a bank decreasing its performance. According to Kroszner (2002), non-performing loans are closely associated with banking crises.
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Also, the study conducted by Yuga Raj Bhattarai (2015) in the context of Nepal and Simion Kirui (2013) in the context of commercial banks of Kenya revealed that the non-performing loan ratio has a negative effect on bank performance (ROA). Mekasha (2001) has examined the relationship between ROA and loan effect of credit risk on the performance of Nepalese Commercial Banks 45 provision, non-performing loans, and total assets which resulted that there is a significant relationship between bank performance and credit risk management. Felix and Claudine (2008) have investigated the relationship between bank performance and credit risk management and found out that both ROE and ROA were inversely related to the non-performing loan ratio of financial institutions which led to a decline in profitability. Another study showed that the loan loss provision of the banks has a significant impact on profitability. (Mustafa, A.R., Ansar, R.H. and Younis, M.U., 2009). Also, Miller and Noulas (1997) stated the negative relationship between credit risk and profitability. It means if there is a negative relationship between credit risk and profitability, it signifies that there is a greater risk involved with loans which in turns create a problem in profit maximization. However, some empirical findings by Li and Zou (2014), Ali Sulieman Alshatti (2015) show that there is a positive effect of the credit risk indicators of Non-performing loans/Gross loans ratio on the financial performance of firms, as measured by ROA and ROE. Similarly, there are some pieces of literature conducted by Gizaw, Kebede, and Selvaraj (2013), Anandarajan et al., (2003) and Muhammad et al., (2012) which show that loan loss provisions ratio which is a forward-looking measure of credit risk have a significant positive effect on ROA.
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Besides non-performing loan ratio and loan loss provision ratio, there are other macro-factors too that affect the profitability of the bank. The macro-variables like exchange rate, real interest rate, inflation rate, GDP growth rate, unemployment rate, etc. also affect the ROA of the bank but these factors are beyond the control of the organization. Empirical results exhibit that there is a positive relationship between bank profitability and inflation in China. (Tan, 2012). Another empirical finding indicated an insignificant positive effect on ROA, but an insignificant negative impact on ROE and EM. The inflation rate, on the other hand, has a negative link with all 3 profitability measures. ( Kanwal,S. and Nadeem, M., 2013)
Also, in India, it was found that there is a significant relationship between GDP growth rate and ROA. (Ramchandani, K. and Jethwani, K., 2017). And while reviewing the study of Dashen Bank S.C, the study found out that NPLs rate, lending interest rate, and GDP growth rate had a statistically significant effect on the level of ROA, insignificant effect of inflation rate on the level of ROA. (Tarko, 2015). Another literature showed that in the context of Nepal macroeconomic variables namely, GDP and Inflation rate has a negative effect on commercial banks profitability. (Shrestha, 2015)
So, two macroeconomic factors i.e. inflation rate and GDP growth rate are incorporated as the control variables besides the NPL ratio and LLP rate which affects the ROA of the bank.
2.5. Conceptual Framework
The conceptual framework is developed from the review of literature discussed above and presented in the following diagram (Figure 2.1).
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Figure 2.1 Conceptual Framework
The hypotheses of this study are:
H1: There is a significant effect of the non-performing loans ratio on ROA.
H2: There is a significant effect of loan loss provision rate on ROA.
H3: There is a significant relationship between inflation rate and ROA.
H4: There is a significant relationship between GDP growth rate and ROA.
2.6. Research Gap
From the previous studies, it is found that there are differing results in the relationship between non-performing loans and the profitability and also, with the macroeconomic variables. Thus, this study has helped us to examine the direction and testing the significance of the relationship between these variables in the case of Civil Bank Ltd. Moreover, this study has addressed to solve the problem of non-performing loans of Civil Bank Ltd. which can help the bank to gain a competitive position in the banking industry of Nepal by taking measures to control the incidence of NPL.
Independent Variable Non-performing loan (NPL) ratio’ Loan Loss provision (LLP) rate Dependent Variable Profitability (ROA) Control Variable Inflation rate GDP growth rate
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CHAPTER 3: RESEARCH METHODOLOGY
3.1. Introduction
This chapter contains the methodology the researched has employed in investigating the effect of non-performing loans on the profitability of Civil Bank Ltd.
3.2. Research Design
The research is a causal hypothesis based since the study has been conducted to establish the impact of non-performing loans on the profitability of Civil Bank Ltd. The study setting is non-contrived as there is no manipulation in the environment. The unit of analysis is organization and it is a longitudinal study since different financial figures for different quarters of the bank are taken for the research. Profitability measured by ROA is taken as a dependent variable and non-performing loans measured by non-performing loan ratio and loan loss provision ratio are taken as independent variables. Macroeconomic factors namely GDP growth rate and Inflation rate affecting profitability are taken for consideration as controlling variables.
Deductive approach is used while conducting the research i.e. quantitative data is used to determine the impact of non-performing loan on the profitability of the bank.
3.3. Data Collection Method and Procedures
For this study, the data is collected from the secondary sources. The macroeconomic variables i.e. GDP rate and Inflation rate are collected from the Central Bureau of Statistics (CBS) and the Nepal Rastra Bank (NRB). And the independent and dependent variables i.e. ROA, NPLR, and LLPR are obtained from the unaudited
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quarterly report of the bank published by them in the website of Sharesansar. All the required data relating to non-performing loans to total loans, provision for loan losses to total loans and net profit to total assets relating to the bank and the inflation rate and GDP rate of Nepal are collected and studied from the second quarter of the fiscal year (FY) 2069/70 to the third quarter of FY 2074/75 since there are outliers i.e. zero non-performing loans till the first quarter of FY 2069/70.
3.4. Summary of variables
Table 3.1 Summary of variables
Abbreviation
Variable
Type
Formula
ROA
Return on Assets
Dependent
Net Profit/Total Assets
NPLR
Non-Performing Loan Ratio
Independent
Non-Performing Loans/Total Loans and Advances
LLPR
Loan Loss Reserve Ratio
Independent
Loan-Loss Provision/Total Loans and Advances
INFR
Inflation Rate
Control
Consumer Price Inflation (CPI)
GDPR
GDP Growth Rate
Control
(GDPt-GDPt-1)/GDPt-1
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3.5. Definition of variables
3.5.1. Dependent variable
3.5.1.1. ROA
Return on assets (ROA) is an indicator of how profitable a company is relative to its total assets. ROA gives information on how efficiently a company is managing its assets to generate income. Higher the value, more productive the assets are. It is calculated as ROA = Net Income / Total Assets. (Investopedia)
3.5.2. Independent variables
3.5.2.1. NPLR
The amount of non-performing loans over the total loans and advances expressed as a percentage is non-performing loan ratio. (Financial Times). The higher value indicates a credit risk.
3.5.2.2. LLPR
A loan loss provision is an amount maintained as an allowance to cover the number of factors associated with future possible loan losses including bad loans, customer defaults, etc. The loan loss provision ratio shows what percentage of total loans and advances are maintained as a provision. (Investopedia) Higher value means the bank is having enough funds to control the bad loans. It is calculated as LLPR= Provision for possible loan losses/ total loans and advances.
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3.5.3. Control variables
3.5.3.1. INFR
Inflation refers to an overall increase in the Consumer Price Index (CPI), which is a weighted average of prices for different goods. The set of goods that make up the index depends on which are considered representative of a common consumption basket which can be different according to the country and the consumption habits of the majority of the population. Some goods might record a drop in prices, whereas others may increase, thus the overall value of the CPI will depend on the weight of each of the goods with respect to the whole basket. Annual inflation refers to the percent change of the CPI compared to the same month of the previous year. (Economic Forecasts from the World’s Leading Economists)
3.5.3.2. GDPR
The GDP growth rate measures how fast the economy is growing. It does this by comparing one year of the country’s gross domestic product to the previous year. GDP measures the economic output of a nation. (The Balance)
3.6. Data Analysis and Econometric Model
In order to analyze the data, the researcher has used several data analysis techniques to achieve the objectives and answer the basic research questions. The researcher has sorted and organized the data in Excel before capturing the same in Statistical packages for social sciences (SPSS) for analysis purpose.
A time series dataset covering 22 observations from the second quarter of FY 2069/70 to the third quarter of FY 2074/75 are used to examine the impact of non-
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performing loan on the profitability of the Civil Bank Ltd. Since there are zero non-performing loans on the quarters preceding the second quarter of FY 2069/70, the data set of these quarters is ignored while conducting the research. For data analysis, the researcher has used the descriptive statistics and multiple linear regression model to find whether there is a significant impact of NPL on ROA. According to Nor Mazlina, Abu Bakar and Izah Mohd Tahir (2009) multiple linear regression analysis is one of the most widely used statistical techniques for establishing the linear relationship between two or more variables. It is a common method to find the determinants of bank performance in the banking and finance literature.
The regression model for the impact of NPL on ROA is ROA= ?0+ ?1NPLR + ? 2LLPR+ E Where, ROA (Return on Assets) = Net income/ Total Assets (Dependent Variable) ?0= constant term; E= error term; ?1- ?2= coefficient of independent variables NPLR= non-performing loan rate (Independent Variable) LLPR= loan loss provision rate (Independent Variable) The analysis of non-performing loan may not give a viable explanation regarding the profitability of the bank because there are other internal factors like bank size, loan to assets ratio and macroeconomic factors such as GDP rate and inflation rate. So, the following linear regression function is used to examine the impact of NPL on the profitability of Civil bank Ltd with the presence of macroeconomic variables as control variables.
The linear function of regression model is ROA= ?0+ ?1NPLR+ ?2LLPR+ ?3INFR+ ?4GDPR+E
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Where, ROA (Return on Assets) = Net income/ Total Assets (Dependent variable) ?0= constant term; E= error term; ?1- ?4= coefficient of independent and control variables NPLR= non-performing loan rate (Independent variable) LLPR= loan loss provision rate (Independent Variable) INFR= inflation rate of Nepal (Control Variable) GDPR= gross domestic product growth rate of Nepal (Control Variable)
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CHAPTER 4: FINDINGS
4.1. Introduction
This chapter presents research findings and interpretation of findings made from the study on the impact of non-performing loans on the profitability of Civil Bank Ltd.
4.2. Descriptive Statistics
Table 4.1 Summary of descriptive statistics Descriptive Statistics N Minimum Maximum Mean Std. Deviation ROA 22 -.035 .968 .47347 .286734 NPLR 22 .50 4.67 2.6532 1.31418 LLPR 22 .153 2.301 1.05172 .533234 GDPR 22 .20 7.39 4.2759 2.47867 INFR 22 4.3 9.9 7.518 2.3668 Valid N (listwise) 22
Source: Researcher computation on SPSS software
Table 4.1 shows the descriptive statistics of the explanatory and explained variables in this study including the control variables. It reports ROA as a measure of profitability of Civil Bank Ltd, two independent variables NPLR, LLPR and two macroeconomic variables GDPR and INFR as the control variables. The ?N? indicates that the researcher has used 22 observations for each respective variable. ROA ranges from -0.035% to 0.968% and its average is 0.473% i.e. the total assets of Civil Bank Ltd is earning 0.473% return on an average during the second quarter of FY 2069/70 to the
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third quarter of FY 2074/75. The mean value of NPLR is 2.6352% which is well within the current regulatory requirement of Nepal Rastra Bank (NRB) of 5%. Similarly, the mean value of LLPR shows that on average the bank has maintained 1.052% loan loss provision of its total loans and advances. The standard deviation of ROA (0.2867) and LLPR (0.53) is very low which shows that there is very low variability in the variables. The macroeconomic variables incorporated in this study have the mean value of 4.2759 and 7.518% with the standard deviation of 2.478 and 2.3668% for GDP and the general rate of inflation, respectively.
4.3. Analysis of Regression results
4.3.1. Findings before control variables are incorporated
Table 4.2 Model Summary before control variables are incorporated
Model Summary
Model
R
R Square
Adjusted R Square
Std. Error of the Estimate
Durbin-Watson
1
.681a
.464
.4107
.220792
2.055
a. Predictors: (Constant), LLPR, NPLR
b. Dependent Variable: ROA
Source: Researcher computation on SPSS software
Table 4.2 shows the model summary of ROA, NPLR, and LLPR before control variables are incorporated. The R square i.e. coefficient of determination is a measure of goodness of fit to show what proportion of the variation in dependent variables is explained by the independent variable Based on the study, the R i.e. correlation
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coefficient is 0.681 indicating a positive correlation between the dependent variable and the predictors and R square is 0.464 indicating 46.4% of the profitability of the Civil Bank Ltd is predicted by non-performing loans. Also, the Durbin-Watson test indicates that there is no autocorrelation in the model since the value is near to 2.
Table 4.3 ANOVA table before control variables are incorporated
ANOVA
Model
Sum of Squares
Df
Mean Square
F
Sig.
1
Regression
.800
2
.400
8.208
.003b
Residual
.926
19
.049
Total
1.727
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a. Dependent Variable: ROA
b. Predictors: (Constant), LLPR, NPLR
Source: Researcher computation on SPSS software
Table 4.3 shows the ANOVA table of dependent and independent variables. The model is statistically significant at a 95% confidence interval or 5% significance level since the sigma value is 0.003 which is less than the p-value of 0.05.
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Table 4.4 Coefficients table before control variables are incorporated
Coefficients
Model
Unstandardized Coefficients
t
Sig.
95.0% Confidence Interval for B
Collinearity Statistics
B
Std. Error
Lower Bound
Upper Bound
Tolerance
VIF
1
(Constant)
.314
.117
2.697
.014
.070
.558
NPLR
-.126
.047
-2.682
.015
-.225
-.028
.605
1.653
LLPR
.470
.116
4.048
.001
.227
.713
.605
1.653
Source: Researcher computation on SPSS software
Table 4.4 presents the coefficients table incorporating the independent variables. The unstandardized coefficient of intercept (?0) is 0.314 indicating the constant value of ROA is 0.314 ceteris paribus and the unstandardized coefficients of independent variables are NPLR (?1=-0.126) and LLPR (?2=0.470) which indicates a negative relationship between NPLR and ROA and a positive relationship between LLPR and ROA. It also indicates that if there is 1% increase in NPLR, there will be 0.126% decrease in ROA ceteris paribus. Similarly, if there is 1% increase in LLPR, there will be 0.470% increase in ROA ceteris paribus. Hence the regression model is ROA= 0.314- 0.126NPLR+0.470LLPR +E
For testing the presence of multicollinearity among the independent variables, the tolerance level (TV) and the variance inflation factor (VIF) are computed. The VIF is less than 2 for each of the independent variables. The higher value of VIF indicates that the variables are collinear and as a rule of thumb a VIF greater than 10 is not acceptable.
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(Gujarati, 2004) Thus, in this study the VIF of less than 2 indicates that NPLR and LLPR are not collinear.
The P-values of NPLR and LLPR i.e. 0.015 and 0.001 indicate that both the independent variables have a significant impact on ROA at a 95% confidence interval or 5% level of significance. The 95% confidence interval indicates that there is 95% chance that the actual value of unstandardized coefficient of NPLR ranges from -0.225 to -0.028 and the actual value of unstandardized coefficient of LLPR ranges from 0.227 to 0.713.
4.3.2. Findings when control variables are incorporated along with dependent and independent variables
Table 4.5 Model Summary after control variables are incorporated
Model Summary
Model
R
R Square
Adjusted R Square
Std. Error of the Estimate
Durbin-Watson
1
.766a
.585
.489
.204931
2.868
a. Predictors: (Constant), Inflation rate, LLPR, GDP growth rate, NPLR
b. Dependent Variable: ROA
Source: Researcher computation on SPSS software
Table 4.5 shows the model summary of ROA, NPLR, and LLPR after the control variables are incorporated. Based on the study, The R i.e. 0.766 indicates a positive correlation between the dependent variable and the predictors. R square is 0.586 indicating 58.6% of the profitability of the Civil Bank Ltd can be predicted by NPLR, LLPR, GDPR, and INFR and the rest is explained by other factors which are not within the scope of the researcher. This value of R square has increased indicating the model has
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become better after incorporating the control variables. The value of Durbin-Watson test indicates that the error terms are negatively autocorrelated.
Table 4.6 ANOVA table after control variables are incorporated
ANOVA
Model
Sum of Squares
Df
Mean Square
F
Sig.
1
Regression
1.013
4
.253
6.028
.003b
Residual
.714
17
.042
Total
1.727
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a. Dependent Variable: ROA
b. Predictors: (Constant), Inflation rate, LLPR, GDP growth rate, NPLR
Source: Researcher computation on SPSS software
Table 4.6 shows the ANOVA table of dependent and independent variables along with the control variables. The regression model is statistically significant at 95% confidence interval as the sigma value is less than 0.05.
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Table 4.7 Coefficients table after control variables are incorporated
Coefficients
Model
Unstandardized Coefficients
T
Sig.
95.0% Confidence Interval for B
Collinearity Statistics
B
Std. Error
Lower Bound
Upper Bound
Tolerance
VIF
1
(Constant)
1.664
.720
2.311
.034
.145
3.183
NPLR
-.258
.095
-2.715
.015
-.459
-.058
.128
7.804
LLPR
.540
.113
4.781
.000
.302
.778
.552
1.813
GDPR
-.064
.029
-2.222
.040
-.125
-.003
.388
2.577
INFR
-.106
.0568
-1.829
.085
-.229
.016
.106
9.448
a. Dependent Variable: ROA
Source: Researcher computation on SPSS software
Table 4.7 presents the coefficients table incorporating both the independent and the control variables. The unstandardized coefficient of intercept (?0) is 1.664 indicating the constant value of dependent variable ceteris paribus; the unstandardized coefficients of independent variables are NPLR (?1=-0.258) and LLPR (?2=0.540) and that of control variables are INFR (?3=-0.106) and GDPR (?4=-0.064) which indicates a negative relationship between NPLR and ROA, INFR and ROA, GDPR and ROA and a positive relationship between LLPR and ROA. It means that if there is 1% increase in NPLR, there will be 0.258% decrease in ROA ceteris paribus. Similarly, if there is 1% increase in LLPR, there will be 0.540% increase in ROA ceteris paribus and so is the case of
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control variables. Hence the regression model is ROA= 1.664- 0.258NPLR+0.540LLPR-0.106INFR-0.064GDPR +E
The tolerance level (TV) and the variance inflation factor (VIF) indicates there are some issues of multicollinearity among NPLR, INFR, and GDPR. Also, the t-ratio of NPLR and LLPR indicates that these variables have the highest impact on ROA of the Civil Bank Ltd.
The P-values of NPLR, LLPR, and GDPR i.e. 0.015, 0 and 0.04 indicates that these variables have a significant impact on ROA at a 95% confidence interval or 5% level of significance. However, the inflation rate does not have a significant impact on ROA. The 95% confidence interval indicates that there is 95% chance that the actual value of unstandardized coefficient of NPLR ranges from -0.459 to -0.058 and the actual value of unstandardized coefficient of LLPR ranges from 0.302 to 0.778 and so on.
4.4. Conclusion
From the findings, it can be explained that the regression model both before and after the control variables have been incorporated is statistically significant at a 95% confidence interval or 5% level of significance. Also, the coefficient of determination i.e. R square has increased in the second model which indicates that the second model better explains the variation in ROA. However, there are issues of multicollinearity and autocorrelation in the second model.
As expected, there is a significant negative relationship between non-performing loan ratio and ROA of Civil Bank Ltd. Since the increasing NPL causes delinquencies, this affects the reliability and credit quality of the bank. Delinquency in loan repayment and interest payment causes a loss in the earnings of the bank. Moreover, if NPL is
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increased, it signals the increasing credit risk which distorts the public confidence in the bank. This result is consistent with the findings of Felix and Claudine (2008); Yuga Raj Bhattarai (2015) in the context of Nepal and Simion Kirui (2013) in the context of commercial banks of Kenya. However, it is contrary to the findings of Li and Zou (2014) and Alshatti (2015)) who found the positive effect of non-performing loans ratio on the financial performance of banks.
Surprisingly in the case of Civil Bank Ltd, the study shows a significant positive relationship between LLPR and ROA. This result can be interpreted as the managers presuming the lending business of the bank to be risky even though loans are the major earning assets of the bank. Even having such expectations they are implementing effective credit risk management policies by maintaining high loan loss provision ratio so that they can absorb future possible loan losses. This helps the bank protect itself from the volatility in the earnings that might arise in the future. Also, higher LLPR signals bank having enough funds to control the bad loans which helps the bank to gain public confidence and trust due to which it attracts more customers. This finding of a significant positive relationship between LLPR and ROA is consistent with the findings of Gizaw, Kebede, and Selvaraj (2013), Anandarajan et al., (2003) and Muhammad et al., (2012). However, this result contradicts with the theory that the level of loan loss provisions is an indication of a bank’s asset quality and signals changes in the future performance Fadzlan and Royfaizal (2008) and Thakor (1987).
With regard to macroeconomic variables, there is a significant negative effect of GDP on ROA as consistent with the finding of Shrestha (2015). It can be interpreted as
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the bank not being able to grasp the opportunity of economic growth. Also, there is an insignificant effect of inflation rate on ROA.
Thus, the findings of the study of Civil Bank Ltd answer the research question and has met the research objective of determining a significant impact of NPL on the profitability of the bank.
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CHAPTER 5: RECOMMENDATION
5.1. Introduction
This chapter presents the existing strategies applied by the bank, proposed change programs/activities and the implementation plan that the researcher has recommended to Civil Bank Ltd as a control measures to reduce the incidence of increasing non-performing loans.
5.2. Existing Strategies of the bank
To manage the risk arising from the high non-performing loan ratio, Civil Bank Ltd has developed its own strategy. It has formulated credit risk management framework, credit policy, valuation guidelines and specific product papers so that the risk would be filtered from the credit approving channels. Also, they have created their own Credit Risk Management Division (CRMD) which is responsible for identifying the risk associated while extending credit. It reviews the files having a group limit of NPR 50 to 100 million on a sample basis whereas the one exceeding NPR 100 million are reviewed wholly. Also, this department has to analyze the portfolios on quarterly basis regarding the concentration risk i.e. whether the bank has crossed the single obligor limit or not, whether the bank has invested in different sectors including productive and deprived sector or not, business –segment wise (corporate, SME, consumer and micro), product wise (home loan, auto loan, education loan, etc.), and tenure wise (up to 1 year , above 1 year, up to 5 years and above 5 years); industrial risk profile review of particular client, product and business segment; quality check in terms of performance under each product, sector and business segment; analyzing the overall risk assets portfolio vis-à-vis
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prudential banking norms and practices, etc. Also, there is a separate Credit Control Department which controls the day to day activities related to credit and ensures the creditworthiness of the customer from different faucets be it character, ability, collateral offered, etc. (Civil Bank). Similarly, the bank performs various activities like customer details analysis to confirm his/her ability to repay the principal and the interest amount, his/her financial status, credibility in surroundings, blacklist checking, his/her banking relations with other banks and financial institutions and his/her net disposable income from a single household. The bank has also been offering the best products as per the clients’ profile, income source, and needs. Also, there is a proper analysis of collateral i.e. both primary (land, real estate) and secondary (stocks) along with the legal documentation including personal guarantee (PG) holders consent to be obtained while issuing the credit to minimize risk and put the bank on the safe side at the time of recovery. In case of revolving loans PG is reviewed every year. After the credit is approved, regular follow-up is done by the bank to confirm whether the loan is used for the right purpose or not and stock level is evaluated in case of the business loan. And if some creditors default, then the bank resort to selling of collateral by auction or transfer it into non-banking assets of the Civil Bank Ltd.
Also, the bank has strengthened its credit recovery department and is striving to improve the quality of loan in the loan portfolio by critically analyzing and regulating the credit appraisal process to reduce the NPL ratio.
5.3. Proposed Change Program/Actions
Since the study has resulted in a significant negative relationship of NPL ratio with ROA and a significant positive relationship with LLPR, the bank has to focus on reducing the
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non-performing loan ratio and increasing loan loss provision by increasing the number of good loans. Though the bank is able to minimize its NPL ratio from the second quarter of 2074/75 it is still high i.e. 3.73% after Prabhu Bank (3.90%) and Nepal Credit and Commerce Bank (3.97%).
The researcher has proposed the following change programs to the bank to reduce the incidence of high NPL ratio which will help the bank to gain a secured position in the competitive financial market.
? Early warning signals (EWS)
The bank should set up an early warning signal (EWS) unit to identify the potential payment difficulties of a borrower as early as possible including automatic triggers such as overdrafts since it will be easier to remedy. In this way, the bank can develop a corrective action plan at a very early stage. The early warning signals can be effective only if clear deadlines and actions are enforced as early as possible to resolve the problem at an early stage. Larger loans should be monitored more closely and there should be the participation of senior staff and management. However, for smaller loans, there can be involvement of less senior staff but the results should be reported to the management. The EWS system should be independent of the credit department of the bank including the sufficient staffing to complete all tasks and it should operate on the IT platform that is integrated into bank’s risk management system. Once the EWS is received, the credit officer can contact the borrower and identify reasons and provide analysis for the same. Then such loan which has potential problem can be listed as watchlist on a temporary basis by monitoring such borrower’s performance. After certain months, a final decision should be taken by the risk manager and EWS manager whether
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such loan is removed from watchlist if the problem is resolved or it is transferred to workout unit for further recovery process. This is also one of the solutions recommended by the World Bank to Bank of Slovenia for effective management and workout of NPLs.
? Forbearance
There are both short term and long term measures of forbearance or restructuring options the bank can choose to minimize the credit risk.
The short-term measures are:
I. Reduced payments – if the borrower’s cash flow is sufficient to service interest and make partial principal payment.
II. Interest only – if the borrower’s cash flow is sufficient to service only the interest payment.
III. Moratorium – an agreement allowing the borrower to suspend payments of principal and/or interest for a clearly defined period, usually not to exceed 90 days.
The long-term measures are:
I. Interest rate reduction – involves the permanent or temporary reduction in interest rate. However, the bank has a high base rate of 11.84% which is calculated on the basis of the expenses incurred by the banks and financial institutions to collect deposits, plus 80% of the bank’s overhead expenses plus up to 0.5% profit. So, the bank should try to reduce its base rate firstly in order to reduce the interest rate for the loan products.
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II. Restructuring- allows the loan repayment period to be restructured or adjusted either by extending the maturity by spreading the repayment amount over a longer period or by adjusting the repayment program to a new sustainable one.
III. Debt-to-asset swap – a portion of debt or a whole amount is transferred into assets by selling the assets. For this, the management of the bank has to make sure that they maximize its returns from the sale of assets.
? Reduced centralization
The credit appraisal of the bank should be more quantitative in nature which can be achieved through the training process. For this, the bank can introduce the lending committee at different ranks and all of these committees will be required to appraise a credit together so that reckless lending will be minimized. This strategy will empower the staff and will reduce the level of centralization in decision making that is previously rested in the hand of the credit manager. This process can require change among the staff for which training should be provided so that the bank can manage the resistance to change
.
? Setting annual targets for every branch
The bank can set annual targets for branches to encourage every branch to focus more on NPL collection. Each of the branch targets will be linked to individual targets. If the target is not met, then the branch ought to provide an explanation for such deviation. The senior manager should be hired on a contractual basis whose main role is to collect the NPLs and the renewal of the contract is to be linked with the performance of set targets.
? Increasing the number of good loans by introducing new loan products
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Nepal is a country where there is a bright prospect in the sectors of small and medium scale enterprises. There are people who have an entrepreneurial ability and are undertaking some small profitable projects. Thus, to encourage these groups Civil Bank can introduce new loan products as follows which are already introduced in the Indian market.
i) Supply chain finance which helps the firms like manufacturing firms, distributors, and B2B firms to get the funds when they are in short of funds. Since these type of businesses might have a delay in payments which might seize the potential growth opportunity for them. So, with this finance, the problem of shortage of funds due to delayed payment can be solved through accounts receivable financing which will liquidate about 75-80% of the amount of outstanding invoices of the firms to cash. The bank can provide this finance for short term i.e. 30-60 days without any collateral.
ii) Online seller finance: In Nepal e-commerce is a booming industry. So, targeting these clients the bank can provide short-term nature of online seller finance without any collateral to them who are expanding to other marketplaces, looking to purchase or increase inventory and diversify the products by providing a customized credit based on monthly sales and projected revenue. For this, the bank can partner with major e-commerce sites of Nepal to help the newcomer access fast and flexible working capital loan to operate optimally. Furthermore, the bank can make the repayment terms flexible i.e. twice a month so that the burden of interest payment will be less.
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For both of these new short-term loan products, the bank should check the authenticity of the borrower and his/her business by verifying the necessary documents like VAT returns, audited financials, KYC document, etc. By attracting new clients the bank can increase their loan portfolio. Also, the bank can increase the amount of loan loss provision in the good/performing loans which will have a positive impact on the performance of the bank since the high amount of LLP indicates the bank having sufficient funds to control the bad loans.
5.4. Implementation Plan
The above change programs that the researcher has proposed to Civil Bank can be shown in the table below.
Table 5.1 Implementation Plan
Objective: To minimize the occurrence of increasing NPL in Civil Bank Ltd.
Initiation of strategy
Details of plan
Who will perform the task?
Target to be achieved
Potential barriers
Short term (3 years)
Long-term forbearance measures such as reducing the interest rate, restructuring of repayment program and debt to assets can be used by the bank
Credit Department, Risk department
Reduce NPLR to 2.8% at the end of year 5
High base rate of Civil Bank Ltd, the value of assets might reduce
Consultation: Evaluation can be done to see whether the target is met or not according to which change program can be adopted and feedback can be collected from the related parties.

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