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Australian Finance & Banking Review 

Vol. 1, No. 1; 2017 

Published by Centre for Research on Islamic Banking & Finance and Business 

 

14 

 

 

Comparative Study on Credit Monitoring Practices in Slected 

Banks of Nepal 
 

Fatta Bahadur K.C
1 

Indra Kumar Kattel
2 

 

1
Tribhuvan University, Nepal 

2
Mewar University, Rajasthan, India 

Correspondence: Indra Kumar Kattel, Rastriya Banijya Bank Limited, Central Office Singhdurbar Plaza, 

Kathmandu, 44600, Nepal, Email: indra.kattel2024@gmail.com  

 

Received: October 01, 2017     Accepted: October 05, 2017      Online Published: October 14, 2017 

 

Abstract 

Credit monitoring is performed by the banks as post approval activities for existing credit clients to indentify the 

early warning single of credit risk. So that, the study was accomplish to observe the credit monitoring practice in 

Nepalese commercial banks.  The study was based on a sample of 10 commercial banks, comprising 5 private 

sector banks and 5 joint venture banks.  This paper attempts to determine the awareness of Nepalese bankers 

about the significance of credit monitoring as risk identification tools. The result of the study indicates that the 

periodically review of the security documents, credit processing procedure, compliance of covenants setup 

during credit approval, technique to control default, risk reporting, review of loan account and regular follow-up  

were differently used as credit monitoring practice in  private sector and joint venture  banks in Nepal. These 

factors also found significant predictor for credit monitoring. Moreover, there was a positive relationship 

between credit monitoring practice and its factors instead of technique to control default. 

 

Keywords: Monitoring, Compliance, Default, Approval, Procedure. 

 

1. Introduction 

Credit monitoring management is a fundamental process of the every banks and financial institutions, which 

replicates in the quality of the credit portfolio. The banks need to constantly do an assessment and make updates 

where there is a need so as to be sure to handle any unexpected risks at the right time before it is happen. This is 

because any neglected or minimized risk can have very long term big and negative consequences since the 

banking activities are so interrelated with monitoring. Credit risk cannot be avoided or eliminated. So, the only 

alternative is to control it. For this rationale, Banks, establish the credit. Banks have challenges to mintined the 

the cfedit in pass categories. Diwan & Rodick (1992), suggested that high NPLs increase the uncertainty 

regarding the capital position of the banks and therefore tend to limit their access to additional financing in 

regular banking business. The shortfall of the lending fund contributes to lower credit growth. In certain banks, 

governments have large amounts of non-performing loans and some commercial banks tend to finance 

government fiscal deficits and sustain some unprofitable government projects with large borrowings from banks. 

These actions increase the prospects of generating NPLs in the banks. So, non-performing loans are one of the 

main reasons that cause insolvency of the financial institutions and ultimately destroy the whole economy (Hou, 



Comparative Study on Credit Monitoring Practices in Slected Banks of Nepal 

 

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2007). By considering these facts, it is necessary to control non-performing loans for the financial soundness of 

banks; otherwise the capital can be jammed in unprofitable projects and sectors which not only damage the 

financial health of banks but also the economic stability of the country.  

In order to control the non-performing loans, it is necessary to know their root causes in the particular financial 

sector (Rajaraman & Vasistha, 2002). Kassim (2002) suggests that some causes of non-performing loans (NPLs) 

include: Poor management, Lack of sound credit policy, Inadequate credit analysis, Errors in documentations, 

Undue emphasis on profitability at the expense of loan quality, Fraudulent practices (Diwan & Rodick, 1992; 

Diwan & Rodick, 1992), Political instability, Economic depression, Abnormal competition, Policy and 

regulatory inconsistencies, Weak real sector, Political and social influence on bank operators etc. 

Non-performing loans (NPLs) have gained world’s attention in the last three to four decades as these increasing 

non-performing loans are causing banking crisis which are turning into banking failures (Siems & Barr, 1994). 

According to K.K & Pillai (2012, p. 3), some of the important reasons for non performing asset, that should be 

closely monitored by the banks. These mentioned reasons are summarized below:  

 Willful defaults, exhaust off of funds, fraud, disputes, management disputes, mismanagement, 

misappropriation of funds etc.,  

 Lack of proper pre-appraisal of credit proposal and follow up.  

  Improper selection of borrowers/activities.  

 Inadequate working capital leading to operational issues. Under financing/untimely financing.  

 Delay in completing the project.  

 Non-compliance of sanction terms and conditions.  

 Poor debt management by the borrower, leading to financial crisis.  

 Excess capacities created on non-economic costs.  

 In-ability of the corporate to raise capital through the issue of equity or other debt instrument from capital 

markets.  

 Business failures. 

 Failures to make out problems in advance.  

 Diversion of funds for expansion\modernization\setting up new projects\ serving or endorsing sister 

concerns.  

 Lack on the part of the banks viz. in credit appraisal, monitoring and follow-ups, delay in settlement of 

payments / subsidiaries by government bodies etc., 

 Time involved in the legal process and realization of securities.  

 The management of non-performing loans is often associated with high operational costs leading to 

declining capital growths in the affected banks. Non-Performing Loans reduces the liquidity of banks, 

deform credit expansion, and slows down the growth of the real sector with direct consequences for the 

performance of banks. So, that credit monitoring is a useful tool to identify the earning warning signal of 

the borrowers. The regular monthly helps to diagnosis of the real cause of NPL and assist to improve the 

credit quality.    

 The risk is being assessed in terms of the sternness of the impact, likelihood of occurring and controllability 

(Gray & Larson, 2008, p. 215). So that credit monitoring and review renewal of the existing credit limit for 

the client are the post sanction activities of the banks.  Credit monitoring is performed by prioritizing the 

risk either by using off site or onsite for risk evaluation.  (Williams, et al., 2006, p. 70).  This monitoring 

is based on the likelihood and consequences. Likelihood depends on the probability that the risk will occur 



Comparative Study on Credit Monitoring Practices in Slected Banks of Nepal 

 

   Fatta Bahadur K.C and Indra Kumar Kattel 

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and how frequently it will take place. While, consequences on the other hand can be calculated by looking 

at the effects on results or on the enablers of results (Williams, et al., 2006, p. 70). For this purpose, banks 

adopt the various monitoring and follow up tools to know the actual position of the credit clients. Hence, 

credit monitoring is then carried out when an appropriate risk appraisal tools has been assumed. An 

assessment is done against an appropriate risk-acceptance criterion to give a risk level of the credit 

(Williams, et al., 2006, p. 70). Therefore, monitoring and control is equally important for credit risk 

management practice in banking sectors. During the post credit appraisal, banks try to find out risk level 

from the basic sources of credit risk. 

1.1 Objective of the Research 

The major objective of the study is to compare the credit monitoring practices between private sector banks and 

joint venture banks in Nepal. The key objective of this research is to establish relationship credit monitoring 

practices ant its explanatory variables.   

1.2 Hypothesis of the Research 

To fulfill the above define objectives of this study, the following hypotheses were developed and tested by using 

statistical tools. 

H1:  There are significant differences among private sector and joint venture banks in credit monitoring 

practice.   

H2:  There is positive relationship between credit monitoring practice and its explanatory variables.  

1.3 Model Specification  

To test the above hypothesis, following model has been developed by the researcher.     

------------------------------(I) 

Dependent variable, y= credit monitoring practice (CMP) 

Independent variables are explained as given.  

X1 = periodically review the security document  

X2= periodically review credit processing procedures  

X3= Review the compliance of covenants to find out the early warning signal of the loan account in time 

X4=Review is a technique to control the default of loan. 

X5 = Risk reporting system may support to revise the existing policy and procedures 

X6= Review of loan account find the utilization of limit. 

X7= Regular fallow up the loan account to know the business activities.  

2. Literature Review  

Das & Das (2007) evaluated the credit risk management practices in Bangladesh. The study identified the 

importance of credit risk management of  commercial banks and then tried to find out the existing procedures 

for credit risk management that were followed by the different commercial banks in Bangladesh. The 

researchers suggested that some prudential guidelines to be required for commercial banks to sustain in the 

volatile banking market. 

Bodla & Verma (2009) examined the credit risk management framework of Indian commercial banks. The 

results show that there is the right for approval of Credit Risk with ‘Board of Directors’ in case of 94.4% and 

62.5% of the public sector and private sector banks, respectively. The study has brought out that credit risk 

management framework in India is on the right track and it is fully based on the RBI’s guidelines issued in this 

regard. 



Comparative Study on Credit Monitoring Practices in Slected Banks of Nepal 

 

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17 

 

Jordon (2009) conducted the study on risk management lessons from the credit crisis. The paper shows that the 

perfect carrying out of risk management does not assure the huge losses. Probability of loss always exists even if 

all the precautionary measures are taken. There are certain factors involved in huge losses usually, business 

decisions and weak monitoring mechanism. The credit crisis emphasized the importance of risk management. 

Pu & Zhao (2010) examined the correlation in credit risk using credit default swap (CDS) data. Secondary data 

for the period of January 2001 to December 2006 was taken for analysis. The finding of the research suggested 

that infectivity is not only statistically but also economically significant in causing correlation in credit risk.  

Norden & Weber (2010) investigated the link between account activity and information production on borrower 

risk. For this purpose, they examined whether credit line usage and cash flows in a borrower’s checking account 

were helpful for monitoring, and how banks used this information. Measures of account activity substantially 

improved default predictions and were especially helpful for monitoring small businesses and individuals. 

Furthermore, early warning indications resulted in higher loan spreads, and in a higher likelihood of limit 

reductions and complete write-offs. The result of the study shows that account activity provides a real-time 

window into the borrower’s cash flows. It may be helpful to take a credit decision for certain types of debt 

financing. The finding of the research suggests that lenders can benefit most from regular monitoring and source 

of information. 

Alam & Masukujjaman (2011) examined the risk management practices of commercial banks in Bangladesh 

based on five commercial banks operating in Bangladesh. The research reveals that credit, market and 

operational risk are the major risks in commercial banks which are managed through three layers of 

management structure. The Board of Directors performs the responsibility of the main risk oversight; the 

Executive Committee observes risk and the Audit Committee supervises all the activities of banking operations. 

In the circumstance of views regarding the use of risk management techniques, it is found that internal rating 

system and risk adjusted rate of return on capital are comparatively significant techniques used by commercial 

banks in Bangladesh. 

Aman & Zaman (2011) examined credit risk performances of the state-owned, private and foreign banks over 

the period from 1990 -2005 by using the simple Error Correction Model (ECM). Credit feature is statistically 

significant for PBs with expected sign. In the light of empirical analysis of data, the research finds that private 

sector banks concentrate more on credit to attract credit customers' findings because it is imperative for private 

sector banks to concentrate more on credit to attract customers. In the same manners private sector banks 

maintain credit risk efficiently and effectively during the analysis period.   

Ariffin & Kassim (2011), analyzed the relationship between risk management practices and financial performance 

in the Islamic banks in Malaysia. Overall, the findings on risk management practices shows that the importance of 

board of directors to endorse the overall policies and to guarantee that the management requires actions to manage 

the risks.  

Hassan (2011) examined the degree to which Islamic and conventional banks used risk management practices 

and techniques in dealing with different types of risks in the Middle East region. There was no significant 

difference between Islamic Banks and Conventional Banks concerning risk identification. However, there were 

significant differences between Islamic Banks and Conventional Banks regarding the understanding risk, risk 

assessment and analysis, risk monitoring, and credit risk analysis of the entire sample banks.   

Thiagarajan, Ayyappan, & Ramachandran (2011) empirically carried out a study to predict the determinants of 

the credit risk of the commercial banking sector in India by using an econometric model. The results showed 

that the insulated non-performing assets had a strong and statistically significant positive influence on the 



Comparative Study on Credit Monitoring Practices in Slected Banks of Nepal 

 

   Fatta Bahadur K.C and Indra Kumar Kattel 

18 

 

current non-performing assets. It is a significant inverse relationship between the GDP and the credit risk for 

both public and private sector banks. The study reveals that both macroeconomic and bank specific factors play 

crucial role in determining the credit risk of the banking sector. 

Nazir, Daniel, & Nawaz (2012) examined and compared the risk management practices of Conventional and 

Islamic banks in Pakistan. The result found that those Pakistani banks were efficient in credit risk analysis, risk 

monitoring and understanding the risk in the most significant factors of risk management. Furthermore, there 

was a significant difference in risk management practices of the Islamic and conventional banks of Pakistan.  

Abdullah, Khan, & Nazir ( 2012)  evaluated the Credit risk management of domestic and foreign banks in 

Pakistan. Based on the result of the research, researchers recommended that credit risk might be reduced if (i) 

the size of the banks keeps with specifies limits and (ii) liquidity of the banks is increased. 

Rani (2012) evaluated the risk management practices in scheduled commercial banks of India. The finding reveals 

that the difference between the various levels of staff positions have been statistically significant, but no 

significant difference in the awareness level of officers of public sector, private sector and foreign sector banks 

regarding credit, market and operational risk. The result indicated that awareness about risk management was the 

optimum level of the officials of the private sector and foreign sector banks as compared to public sector banks. 

Wood & Kellman (2013) examined the risk management practices by Barbadian Banks with the primary 

objective to evaluate the various types of risk faced by banks operating in Barbados. The main findings of the 

study are: risk managers perceive risk management as critical factors to banks’ performance; the types of risks 

causing the extreme exposures are credit risk, operational risk, country or sovereign risk, interest rate risk and 

market risk; there is a high level of success with current risk management practices and these practices have 

evolved over time in line with the changing economic environment and regulatory updates.  

Bilal, Talib, & Khan (2013) examined the risk management in the banking sector with the evidence from the sub- 

continent and gulf country. Based on statistical analysis and personal surveys, research findings concluded that 

banking sector of the study countries had deep concerns with potential risk challenges and they were in a 

continuous process to improve the risk measurement framework in accordance with the latest regulatory 

obligations. All three types of banks had a clear understanding of RM practices and strong relationship was 

observed between predictors and endogenous variables.  

Arora & Kumar (2014), evaluated the credit risk management framework of public and private sector banks in 

India. The findings revealed that the strength of the overall CRM framework did not vary significantly between 

public and private sector banks as on the whole there was very little difference in the scores of the public and 

private sector banks. 

Imbierowicz & Rauch (2014) investigated the relationship between the two major sources of bank default risk: 

liquidity risk and credit risk. The result of the research showed that both risk categories did not have an 

economically meaningful reciprocal contemporary or time-lagged relationship. These results provided new 

insights into the understanding of bank risk, as developed by the body of literature on bank stability risk in general 

and credit and liquidity risk in particular.  

Luqman (2014) studied the effect of credit risk on commercial bank performance in Nigeria. Secondary data 

were explored in presenting the facts of the situation. The result showed that the ratio of loan and advances to 

total deposit negatively related to profitability, though insignificant, and that the ratio of non-performing loan to 

loan & advances negatively related to profitability. This study showed a significant relationship between bank 

performance and credit risk management. Overall credit and NPLs were major variables in determining asset 

quality of commercial bank. 



Comparative Study on Credit Monitoring Practices in Slected Banks of Nepal 

 

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3. Research Method and Materials 

In order to fulfill the research objective, questionnaires were design to collect the primary data. The researcher 

has chosen the survey as the appropriate research design for the study, and as such, questionnaires were used as 

research instruments. The study was based on a sample of 10 commercial banks, comprising 5 private sector 

banks and 5 joint venture banks, which were randomly chosen.  Descriptive statistics, ANOVA and regression 

used to analyze the data. 

To ensure accuracy, internal consistency and completeness, reliability of the instrument was established using 

Cronbach’s alpha coefficient test (Cronbach, 1946). The choice of this indicator was influenced by the 

simplicity and its prominence in banking risk literature. The higher generated score is more reliable. Nunnaly 

(1978) has indicated 0.7 to be an acceptable reliability coefficient to measure the reliability but lower thresholds 

are sometimes used in the literature. In this case, the alpha (α) coefficients were 0.84, which is acceptable level. 

4. Result and Discussion  

This section presents the findings obtained from the data analysis. This result is presented in two sub sections: 

descriptive statistical analysis and regression analysis.  

4.1 Descriptive Statistical Analysis 

As shown in the given table, there was found difference of mean value of the credit monitoring practice such as 

periodically review of the security documents, credit processing procedure, compliance of covenants setup 

during credit approval, technique to control default, risk reporting, review of loan account and regular follow-up 

in  private sector and joint venture  banks in Nepal. The result indicates that credit monitoring practices were 

different in the Nepalese commercial banks. 

Table 1 Descriptive statistics of factors of monitoring practice  

 

      Source: Survey data 2015,                PSB = Public Sector Banks,  JVB= joint Venture Banks 



Comparative Study on Credit Monitoring Practices in Slected Banks of Nepal 

 

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20 

 

The one way ANOVA has been used to see the any differences between private sector and joint venture banks in 

the analysis of the periodically review of the security documents taken by the bank. It demonstrated the model 

was significant (p<0.05) with F value 26.127 at one degree of freedom.  Similarly, there was significant 

differences (p<0.05) in the analysis of the review of credit processing procedure between  private sector and 

joint venture banks with F value 112.464 at one degree of freedom.  

The analysis of variance (ANOVA) of review the compliance of covenants for borrower shows that F value is 

150.113 at significant level (p<0.05) suggesting that there was a significant differences between two group of 

banks.  Similarly, ANOVA of review the technique to control the default demonstrated that there was 

significant (p<0.05) differences with F value 147.179 at one degree of freedom.  

Table 2 Analysis of variance 

  Sum of 

Squares 

df Mean 

Square 

F Sig. 

X1 Between Groups 5.142 1 5.142 26.127 0 

Within Groups 24.997 127 0.197     

Total 30.14 128       

X2 Between Groups 14.483 1 14.483 112.464 0 

Within Groups 16.355 127 0.129     

Total 30.837 128       

X3 Between Groups 16.327 1 16.327 150.113 0 

Within Groups 13.813 127 0.109     

Total 30.14 128       

X4. Between Groups 16.662 1 16.662 147.179 0 

Within Groups 14.377 127 0.113     

Total 31.039 128       

X5 Between Groups 30.707 1 30.707 396.488 0 

Within Groups 0.982 127 0.008     

Total 31.69 128       

X6 Between Groups 15.407 1 15.407 122.383 0 

Within Groups 15.988 127 0.126     

Total 31.395 128       

 X7 Between Groups 17.136 1 17.136 164.23 0 

Within Groups 13.251 127 0.104     

Total 30.388 128       

 

The analysis of variance (ANOVA) of risk reporting of borrower shows that F value is 396.488 at significant 

level (p<0.05) symptomatic of significant differences between two group of banks.  Similarly, ANOVA of 

review of loan account demonstrated that there was significant (p<0.05) differences with F value 122.383 at one 

degree of freedom. The analysis of variance (ANOVA) of the regular follow-up of the client demonstrated that 

the model was significant (p<0.05) with F value 164.23 at one degree of freedom respectively.  

From the above statistical explanation, we conclude that there are significant differences between private sector 

and joint venture banks in the credit monitoring.  Hence H1 is accepted.  



Comparative Study on Credit Monitoring Practices in Slected Banks of Nepal 

 

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4.2 Regression Analysis 

The dependent variable considered for this model is cumulative score of different indicators of the credit risk 

monitoring and control. There are more than 7 variables, all measured in Likert Scale converting them to a 

numeric score. 

It shows that dependent variable is explained by joint correlation coefficient of 0.913 that according to Dancey 

and Reidy (2004) categorization is a high correlation. Similarly around 83.3% of the variability explained by the 

independent factors has been included in the model.  

Table 3 Model Summary 

Model R R 

Square 

Adjusted R 

Square 

Std. Error of the 

Estimate 

Durbin-Watson 

1 .913
a
 0.833 0.823 5.94 0.672 

a. Predictors: (Constant), X1-X7 

Similarly from the ANOVA table, it is shown that the model is highly significant (p<.05) reflecting that the 

improvement in the model is found than in the initial model. The F value is 86.079 at 7 degree of freedom.  

Hence, H2 is accepted. 

Table 4  ANOVA 

Model Sum of 

Squares 

df Mean 

Square 

F Sig. 

1 Regression 21262.191 7 3037.456 86.079 .000
b
 

Residual 4269.685 121 35.287     

Total 25531.876 128       

 

a. Dependent Variable: credit monitoring practice    

b. Predictors: (Constant), X1-X7 

After finding the model significance, we have gone through each and every independent variable. The prime 

motive is to identify the insignificant ones and remove them from the analysis. Then after, the significant 

contributions to the dependent variables have been explained in detail as given in table no. 5. 

Periodically review of the security documents, credit processing procedure, and compliance of covenants setup 

during credit approval, risk reporting, review of loan account and regular follow-up were found significant 

variables during the analysis. 

Risk reporting is variable that makes the significant contribution to explaining the monitoring practice when 

other remaining variables are controlled for with Beta coefficient of 0.0.511. Risk reporting plays the important 

roles to collect the information.  Similarly, significant contribution also found to make by regular follow-up 

with the beta coefficient of 0.461, and periodically review the security documents with the beta value of 0.298, 

while keeping all other variables constant. 

Table 5 Coefficients
a 

Model Unstandardized 

Coefficients 

Standardized 

Coefficients 

    t  Sig. 

     B Std. Error     Beta 

1 (Constant) -22.768 1.957   -11.634 0 



Comparative Study on Credit Monitoring Practices in Slected Banks of Nepal 

 

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X1 8.669 1.356 0.298 6.392 0 

X2 8.284 4.008 0.288 2.067 0.041 

X3 -21.762 7.546 -0.748 -2.884 0.005 

X4 -0.431 2.137 -0.015 -0.202 0.84 

X5 14.506 1.74 0.511 8.335 0 

X6 8.113 2.94 0.284 2.759 0.007 

X7 13.359 6.098 0.461 2.191 0.03 

a. Dependent Variable: monitoring practice    

More important, compliance of covenants was the variable with beta coefficient (0.-0.748), and the review of 

loan account with beta coefficient (0.284) was found significant predictor for monitoring practice credit risk 

measurement. 

5. Conclusion 

Lending is a key business activity in the bank. The loan portfolio is one of the largest assets and a chief source 

of revenue for bank, but is also a great source of risk to a bank’s safety and soundness. In the view of emerging 

concern from the deceleration in credit growth to different portfolio, there is need for strong and effective 

structured mechanism to put in the place in every level.  Since credit monitoring is a basic preventive tool to 

disclose the regulatory and functional weakness during the credit management. Monitoring is an integral part of 

our credit risk management practices.  It is the responsibility of each credit officer to undertake ongoing credit 

monitoring for their allocated portfolio of the clients. Bank has specific procedures in place intended to identify 

at an early stage credit exposures for which there may be an increased risk of loss. The objective this early 

warning system is to address potential problems while adequate options for action. This early risk detection is an 

ideology of the credit culture and is intended to ensure that greater attention is paid to such exposures. So that 

monitoring parameters should be established to diagnosis the weakness.  

Monitoring is an ongoing process in the banking business. Hence, most common procedures should be 

implimentation in regular basis.  The periodically review of the security documents, credit processing 

procedure, compliance of covenants setup during credit approval, technique to control default, risk reporting, 

review of loan account and regular follow-up are the common practices for credit monitoring, that support to 

reduce the credit risk.    

In this research, the limited source of the credit risk is considered as a primary data.  The statistical result 

obtained through primary data analysis is not correlated using the secondary data. This may be the prospective 

area for future researcher in banking sector.  

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Comparative Study on Credit Monitoring Practices in Slected Banks of Nepal 

 

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