




































American International Journal of Business and Management Studies  

Vol. 1, No. 2; 2019 

ISSN 2641-4937     E-ISSN 2641-4953 

Published by American Center of Science and Education, USA 

 

1 

 

Effect of Non-Performing Loans on the Financial Performance of 

Commercial Banks in Nigeria 

 

Okoh Gabriel 

Department of Banking and Finance 

Ahmadu Bello University, Nigeria 
E-mail: Okohgabriel39@gmail.com 

 

Inim Ekemini Victor 

International Organization for Migration, Lagos, Nigeria 

E-mail: ekeminiinim@yahoo.com 

 

Idachaba Odekina Innocent 

Department of Banking and Finance 

Ahmadu Bello University, Nigeria 

E-mail: Innocentdaniel4grace@gmail.com 

 

 

 

Abstract 

The study 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 from the Central Bank of Nigeria (CBN) statistical bulletin and Nigeria Deposit Insurance Corporation 

(NDIC) publications for various years. The result of the study shows that Non-Performing Loans to Total Loans 

ratio (NPL/TLR) and Cash Reserve Ratio (CRR) had statistically negative significant effect on Return on Asset 

(ROA). These result shows 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. 

 
Keywords: Non-Performing Loans, Return on Asset, Bank Financial Performance. 

JEL classification: G21, G29 

1. Introduction 

The efficiency of the bank’s performance is a function of how they are able to satisfy their customers at a minimum 
risk level and maximize profit as well. Commercial banks are the dominant financial institutions in most developing 

and emerging economies and well-functioning commercial banks accelerate the rate of economic growth while 

poorly functioning commercial banks are an impediment to economic progress (Richard, 2014). Loans are part of 

the assets of a commercial institution since they are meant to earn interest in the course of time (Waweru & Kalani, 

2016). This, however, is not always the case. Some loans do not perform as expected and are termed non-performing 

loans (NPLs). 

 

Obviously, credit creation is the main income generating activity of banks (Kargi, 2011). However, it exposes the 

banks to credit risk. The Basel Committee on Banking Supervision (2001) defined credit risk as the possibility of 

losing the outstanding loan partially or totally, due to credit risks (default risk). Credit risk is an external determinant 

of bank performance. The higher the exposure of a bank to credit risk, the higher the tendency of the bank to 
experience financial crisis and vice-versa. According to Ahmad & Ariff (2013), most banks in Nigeria and other 

economies such as Thailand, Indonesia, Malaysia, Japan and Mexico experienced high Non-Performing Loans 

(NPLs) and significant increase in credit risk during financial and banking crises, which resulted in the closing down 

of several banks in Indonesia and Thailand. The negative effect of credit risk and non-performing loans on banks 

performance and the economy in general has made the issue of NPLs a global one and of great importance in the last 



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decades. According to Hou & Dickinson (2007), many researches on the causes of bank failures found that asset 

quality is a statistically significant predictor of insolvency, and that failing bank institutions always have high level 

of Non-performing loans prior to failure. Hence, this study seeks to investigate the effect of Nonperforming loan on 

the financial performance of commercial banks in Nigeria. 

 

2. Problem Statement 
In Nigeria, due to the rising increase of non-performing loans, the CBN (2010) through its prudential guideline, 

required licensed banks to periodically review their credit portfolios continuously, at least once in a quarter with a 

view to recognizing any deterioration in credit quality and that a credit facility should be deemed to be non-

performing once any of the following conditions exists; where Interest or principal is due and unpaid for 90 days or 

more and interest payments equal to 90 days, interest or more have been capitalized rescheduled or rolled over into a 

new loan. Thus they classified non-performing credit facilities into three categories namely, substandard, doubtful or 

lost (CBN, 2010).  

The Nigeria banking industry, according to NDIC (2013) annual statement and account show that the total loans and 
advances stood at N10.043 trillion in 2013, showing an increase of 23.22 percent over N8.150 trillion granted in 

2012, and that the non-performing loans to total loans ratio improved from 3.51 percent in 2012 to 3.23 percent in 

2013, this according to the report was within the regulatory threshold of 5 percent. However, in spite of this 

improvement, the volume of non-performing loans increased by 13.30 percent from 281.09 billion in 2012 to 324.14 

billion in 2013 (NDIC, 2013). As a proactive measure to avert the menace of resurgence of non-performing loan and 

to ensure safe and sound financial system the CBN in June 2014 directed that no financial institutions shall without 

the prior written approval of the CBN grant a credit facility to a potential borrower who is in default of the any 

existing credit facility to the tune of N500Million and above in the case of deposit banks and N250Million and 

above in the case of development banks and banks in liquidation. 

 

But in 2016, the NDIC report shows that, the commercial banks total loans to the domestic economy stood at 
N16.29 trillion as at 31st December, 2016, out of which the sum of N2.08 trillion was non-performing. The sharp 

rise in the quantum of non-performing loans (NPLs) by 220% from N0.65 trillion as at 31st December, 2015 to 

N2.08 trillion as at 31st December, 2016 and the NPL to Total loans ratio (NPL ratio) which increased from 4.88% 

as at 31st December 2015 to 12.80% as at 31st December 2016, compared unfavorably with the maximum prudential 

threshold of 5%.  

The NDIC report 2016 indicated on a negative note that the commercial banks profitability indices declined in 2016. 

The commercial banks unaudited profit fell by 30.16% from N 0.63 trillion as at 31st December, 2015 to N 0.44 

trillion as at 31st December, 2016. Also, Non-interest income decreased by 32.60% to N 0.17 trillion as at 31st 
December 2016 from N 0.25 as at 31st December, 2015. Net-interest income also decreased to N 0.28 trillion as at 

31st December, 2016 from N 1.44 trillion in 2015. The commercial banks Return on Assets (ROA) decreased from 

2.34% in 2015 to 1.48% in 2016 while Return on Equity (ROE) fell from 19.78% in 2015 to 12.65% in 2016. Yield 

on Earning Assets also depreciated from 13.40% in 2015 to 3.51% in 2016. The declining profit trend necessitated 

this study, to investigate the effect of non-performing loan on the financial performance of commercial banks in 

Nigeria.  

3. Research Questions 

The following research questions were raised: 
 Does Non-Performing Loan affect the financial performance of commercial banks in Nigeria? 

 Does Cash Reserve Ratio affect the financial performance of commercial banks in Nigeria? 

 Does inflation rate affect the financial performance of commercial banks in Nigeria?  

 

4. Objectives of the Study 

The main objective of this study is to investigate the effect of non-performing loans on the financial performance of 

commercial banks in Nigeria. Specifically, the following objectives were designed to: 

 Identify the effect of Non-Performing loan to total loans ratio on the financial performance of commercial 

banks in Nigeria. 

 Examine the effect of Cash Reserve ratio on the financial performance of commercial banks in Nigeria. 

 Identify the effect of Inflation rate on the financial performance of commercial banks in Nigeria. 
 



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5. Research Hypothesis 

The following hypotheses were considered for the study: 

HO1: Non-Performing loan to Total Loan ratio has no significant effect on the financial performance of 

commercial banks in Nigeria. 

HO2: Cash Reserve ratio has no significant effect on the financial performance of commercial banks in Nigeria. 

HO3: Inflation Rate has no significant effect on the financial performance of commercial banks in Nigeria. 
 

6. Literature Review 

6.1 Non-Performing Loans and Bank Performance 

In Nigeria, the rising trend in NPLs between 1981 and 2013 accounts for over 10% of the total loans granted and 
significantly resulted in bank distress. Bank defaulting debtors were in many cases found to abandon their debt 

obligations and went to other unsuspecting banks to contract new debts which again most likely to degenerate into 

nonperforming loans. The use of status reports on bilateral basis was not effectively utilized to detect such dubious 

multiple loan defaulters. Thus, the need for a central information data-base from which the required consolidated 

credit information on borrowers has become inevitable. This prompted the Central Bank of Nigeria to establishment 

of the Credit Risk Management System (Ojo and Somoye; 2013). 

Mohd Karim and Sallahundin (2010), maintain that the management of non-performing loans is often associated 

with high operational costs leading to dwindling capital growths in the affected banks. Non-Performing Loans 
(NPLs) reduces the liquidity of banks, distorts credit expansion, and slows down the growth of the real sector with 

direct consequences to the performance of banks.  

Somoye, (2010) said that NPLs also bring down investors’ confidence in the banking system, thereby discouraging 

them from making reasonable investments. As far as the Nigeria banking sector is concern, something has to be 

done seriously and urgently to bring back the confidence of bank customers in the sector. Confidence is one of the 

factors banks must offer in order to get the patronage of customers. 

The performance of commercial banks can be measured by return on assets (ROA) which reflects the ability of bank 

management to generate profits from the available assets. Athanasoglou, Brissimis and Delis (2008) argued that 

ROA is considered to be a core performance indicator used in the majority of empirical studies. Studies by Golin 

(2001) and Rose and Hudgins (2008) confirm the view that ROA is one of the most important measures of 

profitability in banking literature. Therefore, in this study ROA will be used to measure the financial performance of 

commercial banks in Nigeria. 

 

6.2 Empirical Review 

There are a number of studies that investigated the effect of non-performing loan on the financial performance of 

commercial banks. While the debate on the usefulness of these non-performing loan factors in explaining financial 

performance of commercial banks is still rampant and inconclusive, extant empirical evidence can be sifted to 

identify some of these non-performing loans factors that have been frequently established by studies as important 

factors determining banks performance. This section presents empirical review of previous studies on the non-

performing loans and financial performance in developed and emerging markets. 

Lydnon, Peter and Ebitare (2016) investigated the relationship between non-performing loans and bank performance 

in Nigeria for the period of 1994-2014. The multiple regression technique was used to analyze the data. The result of 

the study shows that Bad loans (BAL) and Doubtful Loans (DOL) had statistically negative significant influence on 

Return on Capital Employed (ROCE), while Substandard Loan (SUL) had statistically negative insignificant impact 

on ROCE. The result further shows that high level of non-performing loans would reduce the performance of banks 

in the long-run in Nigeria.  

Similarly, Joseph and Okike (2015) investigated the impact of Non-performing loans on firm profitability: A focus 

on the Nigerian Banking industry for a period of (7) year (2006-2012). Data were analyzed using the regression 

statistical tools and the result revealed that there is no relationship between the Non-performing Loans (NPL) and 

Return on Asset (ROA) of Nigeria Banks. This means that the assets values of the firms are not affected by the level 



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of NPL. The shareholders wealth maximization is affected as the second result showed that there is a relationship 

between the non-performing loan (NPL) and Return on Equity (ROE) of Nigerian -Bank. 

Ekanayake and Azeez (2015) investigated the determinants of non-performing loans in licensed commercial banks 

in Sri Lanka for the period 1999- 2012 and found that the level of non-performing loans can be attributed to both 

macro-economic conditions and banks specific factors. Their study results reveal that non-performing loans tends to 

increase with deteriorating banks efficiency and there was a positive correlation between loan to asset ratio and non-

performing loans. They also observed that banks with high level of credit growth is associated with a reduced level 

of non-performing loans, while larger banks incur lesser loan defaults compared to smaller banks. However the 

study found with regards to the macro economic variables, that non-performing loans vary negatively with growth 

rate of GDP, while inflation was positively related to the prime lending rate. 

Mwangi, (2014) carried out a study on the effect of nonperforming loans on the financial performance of 

commercial banks in Kenya. The study aimed at establishing how nonperforming loans portfolio impacted on the 

financial profitability of commercial banks in Kenya. The study focused on all the 46 commercial banks in Kenya 

for the period 2005 – 2011. Secondary data was obtained from the banks relating to two variables; Return on assets 

(ROA) which were the dependent variable and NPL which was the independent variable. The study adopted simple 

linear regression model of the form Y = a+bx to establish the effect of nonperforming loans on commercial banks 

financial performance. The results obtained from the study confirm that during the earlier years of the study, there 

was a high amount of NPLs resulting to a very low ROA. Later years however showed a different trend where ROA 

was higher and NPLs were low. 

 

Nir Klein (2013) in An International Monetary Fund (IMF) Working Paper investigates the non-performing loans 
(NPLs) in Central, Eastern and South-Eastern Europe (CESEE) covering 1998–2011. The study reveals that the 

NPLs level can be ascribed to both macroeconomic conditions and banks’ specific factors, even though the banks’ 

specific factors was found to have a relatively low explanatory effect on NPLs. It further reveal that NPLs were 

found to respond to macroeconomic conditions, such as GDP growth, unemployment, and inflation which means it 

affects the economic recovery of the region. 

 

Mohammad, Ammara, Abrar and Fareeha (2012) examined economic determinants of non-performing loans using 

correlation and regression analysis to analyze the impact of selected independent variables and the result reveals that 

interest rate, energy crisis, unemployment, inflation and exchange rate has a significant positive relationship with the 

non-performing loans of Pakistan banking sector, while GDP growth rate has a significant negative relationship with 

the non-performing loans of Pakistan banking sector. 

 

6.3 Theoretical Framework  

This section explains the related theories on which the study is based. There are a number of theoretical perspectives 

which are used in explaining the relationship between non-performing loan and profitability Such as Moral Hazard 

theory is used to underpin the study 

6.3.1 The Moral Hazard Theory 

Moral hazards refers to a condition leading to risk that results when a banks customer provides information that is 

misleading about its financial statements or his or her credit capacity, or has a hidden incentive to take risks that are 

unusual in an attempt to earn a profit before the contract settles. The bank customer who is the borrower may not 

enter into the contract with the bank in good faith, hence gives misleading information about his or financial status 

or credit capacity. The theory postulates that, the problem of moral hazard may result from information asymmetric 

between banks customer and the bank which makes it almost impossible to distinguish bad from good prospective 

borrowers (Richard (2011). Researchers have noted that moral hazard problem has led to overtime pilling up of 

NPLs (Bofondi & Gobbi, 2003). This theory underpins this study because efficient financial systems and financial 

intermediation requires accurate information about borrowers and the venture the credit are used for. More so, the 

moral hazard theory stated that the higher the nonperforming loan's the lower the financial performance and the 
higher the assets quality the higher the financial performance of banks and vice versa. 

 

 



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7. Methodology 

The study examined the effect of non-performing loans on the financial performance of commercial banks in 
Nigeria. The study adopted ex-post facto research design as there was the existence of variables and secondary time 

series data at the time of the study. Secondary data for 32 years period covering 1985 to 2016 was collated for the 

commercial banks in Nigeria. Data was collated from the Central Bank of Nigeria (CBN) statistical bulletin and the 

Nigerian Deposit Insurance Corporation (NDIC) annual reports for various years. 

7.1 Variables Measurement  

Table 1 Variable Measurement and Description 

S/N Variable 

Name 

Description/Measure Variable  

Type 

Source Apriori 

Expectation 

1 ROA Measured as net profit before 

interest and tax divided by 

Total assets of commercial 

banks. 

 

Dependent 

 

Kakanda et al, (2016) 

  

Positive sign 

2 NPL To measure the non-

performing loans, the study 

used the NPL ratio computed 
as a percentage of non-

performing loans to total 

loans 

 

 

Independent 

 

Achou and Tenguh (2008) 

  

 Negative sign 

3 CRR CRR is the specified 

minimum fraction of the total 

deposits of customers, which 

commercial banks have to 

hold as reserves either in cash 

or as deposits with the central 

bank. 

 

Independent 

 

Montoro and Moreno 

(2011) 

  

Negative sign 

4 IFR Inflation is the persistent 

increase in the general price 

level of goods and services in 
the economy. Measured as 

inflation rate in Nigeria for 

the period under study.  

 

Independent 

 

Farhan (2012) 

 

Negative sign 

Source: Researchers’ Compilation, 2019 

7.2 Model Specification 

 A multiple regression model in the order below was formulated to capture the relationship between NPLR, CRR 

and IFR. 

ROA = f (NPLR, CRR, IFR.) 

Translating the above into it explicit form we have: 

ROA = α + β1 NPLR + β2 CRR + β3 IFR + μ 

Where; 

ROA = Return on Asset 

NPLR = Non-performing Loans to Total loans ratio  

CRR = Cash Reserve Ratio 



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 IFR = Inflation rate 

α = the intercept or constant term  

β1, β2 = Coefficients of the independent variables to be estimated  

μ = the error term of the regression equation. 

8. Result and Discussions 

Table 2: Diagnostics test results (Pre-regression Test) 

 PROBABILITY CENTERED VIF CHI-SQUARE 

VIF  1.162,1.496,1.66  

JARQUE 0.67  775.97 

Breusch-Pagan Godfrey Test 0.67   

Source: Author’s Computation Using E-View 10.0 Version. 

 

The multicollinearity tests was carried out using the Variance Inflation Factor (VIF) which quantifies the severity of 

multicollinearity. From the result above in (Table 2) it can be concluded that there is no multicollinearity because 

the VIF value of 1.162, 1.496, 1.66 lies between the range of 1-10. As a VIF greater than 10 would be a cause of 
concern Eston (2016). 

8.1 Unit Root Test 

The test of stationarity of the variables was conducted using the Augmented Dickey-Fuller (ADF) and the Phillip-

Perron (PP) tests. The results of the ADF and PP tests with trend and intercept are presented in Table 3 below: 

Table 3: Unit Root Test of ADF and PP 

Variables ADF Individual Intercept PP Individual Intercept 

 T-Statistic 
Critical 

Value 5% 

P-

Value 

Orde

r of 

Integ

ratio

n 

Remark T-Statistic 
Critical 

Value 5% 

P-

Value 

Order 

of 

Integr

ation 

Remark 

ROA (6.512642) (2.967767) 0.0000 1(1) Stationary (31.78560) (2.963972) 0.0001 1(1) Stationary 

NPL/TL (4.299634) (2.967767) 0.0022 1(1) Stationary (3.810861) (2.963972) 0.0071 1(1) Stationary 

CRR (4.916469) (2.963972) 0.0004 1(1) Stationary (5.002036) (2.963972) 0.0003 1(1) Stationary 

IFR (3.641647) 2.981038 0.0118 1(1) Stationary (6.094187) (2.963972) 0.0000 1(1) Stationary 

Source: Author’s Computation Using E-View 10.0 Version. 

 
The results of the unit root tests indicate that all the variables are integrated of order one, that is 1(1), which implies 

they are non-stationary at level but become stationary after first differencing. Both the ADF and PP test statistic 

result values were greater than the critical values 5%. Moving on to the co-integration as presented below, since all 

the variable are stationary at the same level. 

 

 



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Table 4: Co-integration Test 

Hypothesized 

No: 

Trace 

Statistics 

0.05 Critical 

Value 
Probability 

Max-Eigen 

Statistics 

0.05 Critical 

Value 
Probability 

None 24.67132 29.79707 0.1735 17.82000 21.13162 0.1367 

At most 1 6.851323 15.49471 0.5950 6.770532 14.26460 0.5166 

At most 2 0.080791 3.841466 0.7762 0.080791 3.841466 0.7762 

Source: Author’s Computation Using E-View 10.0 Version. 

 

The result presented above (in table 4) shows that no co-integration exist among the variables, that is no long run 

relationship exist among the variables. Hence, the alternate hypothesis that there is no Co-integrating vector is 

rejected as a result of the fact that both the Trace statistics and the Max-Eigen statistics is less than the critical value 

at 5% significance level respectively. 

 

Table 5: Multiple Regression Analysis 

Variable Co-efficient Std-Error T-Statistics Probability 

C 7.566539 6.374114 1.187073 0.2452 

NPL/TL (0.293620) 0.186558 (1.573880) 0.1267 

CRR (0.396248) 0.424607 (0.933212) 0.3587 

IFR (0.067998) 0.145315 (0.467938) 0.6435 

R-Square                 0.571284 

Adjusted R-Square  0.535614 

F-Statistics              4.32146 

Prob(F-Statistics)   0.00004 

Source: Author’s Computation Using E-View 10.0 Version. 
 

 

The result presented above shows that the coefficient for all the variables, NPL/TL, CRR and IFR had negative 

signs, meaning that to every one percent decrease in NPL/TL, CRR and IFR will on average, lead to 0.29, 0.39 and 

0.06 percent reduction in ROA. 

 

The result further indicates that NPL/TL & CRR had negative relationship with ROA at 5 percent significant level 

suggesting that an increase in NPL/TL & CRR will result to a reduction in ROA which means a reduction in Return 

on Asset (ROA) used as proxy for the commercial Banks Financial performance. This result is in line with previous 

studies conducted by Joseph & Okike (2015) and Lydon, Peter & Ebitare (2016) using ROA and Return on Capital 

Employed (ROCE) respectively. As proxy for bank performance, meaning that there is a negative effect of non-

performing loan on the financial performance of commercial banks in Nigeria. 
 

Moreso, the R2 value reveals that the explanatory variable in the model i.e NPL/TL, CRR and IFR accounted for 

about 57 percent of the variation in the dependent variable ROA, while the 43 percent that is unaccounted for is due 

to other factors. The result shows that the independent variables are good predictors of ROA. For the F-statistic, 

which apart from the adjusted R2 also tells about the overall significance of the model, the value obtained through 

estimation 4.32146 shows how the model is highly fit for the analysis. 

 



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9. Conclusion and Recommendation 

The study examined the effect of Non-performing loans on the financial performance of commercial banks in 

Nigeria for the period 1985-2016. Secondary aggregate data (figures) were collated from the annual reports and 

publications of the Nigerian Deposit Insurance Corporation (NDIC) and the Central Bank of Nigeria (CBN) 

statistical bulletin for various years. ROA was employed as proxy for the financial performance of commercial 

banks which is the dependent variable, and on the other hand NPL/TL, CRR and IFR were used as proxy for Non-
Performing Loans (the independent variables). A multiple regression model was formulated to examine the effect of 

the variables; the diagnostic test was carried out to check the severity of the multicollinearity, followed by the ADF 

and the PP unit root test, the co-integration test which shows that there is no co-integration among the variables and 

the multiple regression analysis. 

 

The unit root tests (i.e both the ADF & PP) shows that all the variables of interest were integrated of order 1(1) and 

were stationary at first differencing. The multiple regression results show that NPL/TL, & CRR had statistically 

significant negative influence on ROA, while IFR had statistically insignificant negative influence on ROA. It 

proved that non-performing loan had a negative effect on the financial performance of commercial banks in Nigeria. 

The effect of the above is that any increase in the volume of non-performing loan would reduce the financial 

performance of commercial banks in Nigeria. 

 
Consequently, upon the findings of the study, the following recommendations were made: that the regulatory 

authorities in Nigeria should ( through the Asset Management Corporation of Nigeria AMCON) create and support 

an environment where commercial banks in Nigeria can have a strong risk management practices, by strengthening 

the bank’s internal risk management process of identification, measurement and monitoring of risk. Considering the 

negative correlation that CRR had on performance, the study therefore, recommends that commercial banks should 

come up with innovative ways of boosting their internal financial capacity to be able to handle any possible policy 

movement (changes) in CRR and inflation rate. 

 

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