DETERMINANTS OF NON-PERFORMING LOANS IN NIGERIA
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DETERMINANTS OF NON-PERFORMING LOANS IN NIGERIA
Israel Odion Ebosetale Idewele Cyprus International University, Turkey
The study examines the determinants of nonperforming loans in Nigeria. Secondary data were extracted from the Central Bank of Nigeria Statistical Bulletin and the Annual Reports of all commercial banks.
We used ordinary least square multiple regression analysis given that the data are cross – sectional and time series in nature. The cross – section random effect model was employed and the estimate parameter data were regressed and analyzed with the aid of EVIEWS 7.0 econometric software package. The findings of the study are that, the Gross Domestic Product is not a significant determinant of bad debt ratio, and poor credit risk management contributes significantly to non – performing loans in the Nigerian banking sector. We therefore insistently recommend that, Nigerian government should establish positive banking regulations that would contribute to oversee the administration of loans, and banks should adopt efficient loan appraisal techniques consisting of conventional investment analysis and risk measurements
Keywords: Financial institution, Non-performing loans, Poor credit management, Macroeconomics variables and commercial banks.
Introduction
The financial institutions generally serve as financial intermediaries. This form of asset intermediation is required to ensure that the funds are transferred from the surplus economic units to deficit economic units within the economy. The Nigerian banking sector encourages individuals and organizations to establish themselves by approving credit and loans to them and also ensuring that organizations which buy goods or services on credit pay on time. The incidence of non-performing loans (NPLs) could occur when due, resulting in over-bloated loan interest due for payments.
Poor credit management and non-Performing loans (NPLs) reduce the liquidity of banks, and credit expansion, this would relatively slow down the growth of the real sector with direct consequences on the performance of the banks, the firm and the economy as a whole. Lending involves the creation and management of credit assets. Banks need good lending policy. It help banks to do well. Lending policies and careful lending practices are essential in efficient credit system and in minimizing the risk in lending.
The banking sector seem to have an important role to play in the economic development of the country. However, the previous studies on the sector indicate that little success was recorded in this regard. Some banks find it difficult to deal with the obligation to their customers and owners due to faults or weakness in managing their lending portfolio and the short comings which could render them either illiquid or insolvent. Most banks in Nigeria in the past have been saddled with problems relating to loans and advances particularly credit management and non-performing loans (NPLs) which have gradually
413
eroded their profits and their performances have been greatly retarded. The ability of banks to recover loans and advances granted to customers brings bank’s growth.
Research Objectives
To examine the extent to which poor credit management by Nigerian banks have contributed to determinants of non-performing loans,
To determine the impact of macroeconomic performance of Nigerian economy on the prevalence of non- performing loans in Nigeria.
Literature Review
The reason for this part is to show other authors views about our subject of discussion.
Non-Performing Loans
Non-performing loans (NPLs) usually slow down with the loans that for a relatively long quantity of it slow do not generate gain. that is the principal and \or interest on loans has remained unpaid for a minimum of ninety days (Caprio and Ktingebiel 1999). value and Renault, (2004) submitted that non- performing loans (NPLs) has taken a replacement dimension in finance as charge per unit and liability management were, fifteen years past as a results of mounting pressure of non-performing loans (NPLs) on bank’s balance sheets and constant banks failure. Shocking incident might happen which will disrupt the nice plans already organized down. Once a loan is to default there unit sometimes warning signals, that if perceived early have to be compelled to stimulate the lenders curiosity to need necessary action to safeguard the bank’s interest.
Causes of Non-Performing Loans (NPLs) In the Banking Sector
Causes of non-performing loans (NPLs) can loosely be classified into the following: Adverse economic conditions or problems, Bank connected problems, Customers' connected problems and Political condition/problems. Employment and gain unit closely full of lack of payment which might place the borrowers in an exceedingly} very position of not having the flexibility to repay. Some consumed loans could cause problems due to poor budgeting by the recipient like their unforeseen contingencies that unit in excess of gain.
Some banks connected problems unit the causes of non-performing loans (NPLs) such as: Poor management, Lack of sound credit policy, inadequate credit analysis, Error in documentation, Undue stress on gain at the expense of loan quality. Dishonest practices, abnormal competition – Kassim (2002).
Adverse Economic Condition
According to Alo (1995) a significant reason for non-performing loans (NPLs) is “the nice impact of a contributive economic setting on the flexibility of the recipient to fulfill its obligation” as an example, in amount of recession, the flexibility and temperament to pay ar greatly reduced. The degree of impact on each people and businesses depends on the seriousness of the recession and its period. because the recession deepens customers purchases decline that reduces the sales and level of financial gain of business companies.
Employment and financial gain ar closely suffering from lack of payment which can place the borrowers during a position of not having the ability to repay. Some consumed loans might also gift
issues attributable to poor budgeting by the recipient like their unforeseen contingencies that ar in more than financial gain.
Banks Related Problems
Some banks related problems are the causes of non-performing loans (NPLs) such as:
x Poor management
x Lack of sound credit policy x Inadequate credit analysis x Error in documentation
x Undue emphasis on profitability at the expense of loan quality.
x Fraudulent practices
x Abnormal competition – Kassim (2002)
Muller (2001) is of the opinion that tho' banks earn profit by taking risk, they'll minimize this risk to associate extent by adopting sensible loaning, policy, distinguishing the chance concerned, which means and improvement, scenario of the venture to forestall unhealthy loaning. He went any to state that banks ar loaning space during which business risk ar identified and also the spirit of simply making new business mustn't plunge the bank into serious debts management drawback. To him, most causes of non- performing loans ar typically the consequence of violation of loaning policies and market speculation.
Olashore (1985), believes that an outsized incidence of non-performing loans (NPLs) develop as a results of the shortcoming of banks to develop conservative live before granting loan facility. this implies that banks ought to have a mixture of administration of loans and definite loan policy. Another issue with reference to most Nigerian banks is that they're too slow in process loan applications. In associate economy wherever high rates of inflation exist delay in obtaining authorization could jeopardize the complete success of the project. in keeping with Osayameh (1986), the longer it takes for the project to take-off, the more cash is required to finance its operational expenses. Nkhuleigbe (1992) known late disbursement of loans by banks as a significant issue for diversion of funds by the beneficiaries at the investment level and thus affects their ability to repay the loan back. Another major issue to think about is that the space of security analysis, non-perfection of securities so isn't given enough thought.
Alegbe (2004) is of the opinion that security perfection is that the solely prudent follow since customers ar over willing to co-operate before disbursement, however becomes extraordinarily troublesome once disbursement has been allowed. He thus warned bank managers to confirm that security demand is absolutely formed before a client is allowed to draw down approved facility. He believes that with the collusion of the workers or through inefficient book keeping, the bank won't press for compensation.
Nwankwo (1970), whereas discussing way forward for industrial banks in African nation attributed non-performing loans to (among other) issues, high degree of workers irregularities starting from forgeries to sophisticated frauds.
Adverse selection
The idea underlying this version is that borrowers don't invariably offer all the data needed. Despite the actual fact that they are doing, now not all facts are correct (Chang eta, A 2007). Borrowers usually have personal (internal) facts or so their initiatives this can be further correct than the statistics possessed by mistreatment lenders. Consequently, a investor might want to nevertheless be unsure regarding the default threat of a loan contract and have issues in assessing and dominant the character and behavior of the receiver. The negative choice problem happens if lenders decide to defend themselves con to default threat with the help of setting their written agreement phrases in a very method applicable for the anticipated average fine in their mortgage candidates.
Moral Hazard
It shows that borrowers who have internal information take hidden actions that increase their default probability. Therefore, moral hazard arises as a result of changes in the two parties incentives after entering into a contract such that the riskiness of the contract is altered (Chengdu, A).
Patronizing effect
This is a tendency that lenders are unwilling to collect. Unwillingness may arise from several factors such as poor policies, procedures, structure, rewards, physical setting, etc. Such internal problems weaken management and motivate borrowers not to repay the loan, because they are confident that no serious action will be taken against them (Islam, Shirl, Man nan, A).
Credit Risk
Credit risk is defined as the potential that a bank borrower will fail to meet its obligations in accordance with agreed terms. It is a probability of loss from a debtor's default. In Banking Credit risk is an important factor in determination of interest rate on a loan.
Loans and Advances
Loan is Credit granted when money is disbursed and its recovery is made on a later date. Advance is a credit faculty granted by the bank. Bank grant advances largely for short-term purposes. Loan and Advances are to be repaid. Advanced can be paid in one while loan over a period.
Bank Capital Base
Capital Structure of a bank or company (Shareholders' capital plus loans retained profits) used as a way of assessing the company worth or bank worth. It measure a bank financial health. In financially, it is the buffer storage of cash and safe Asset that banks hold and to which they need access in order to protect creditors in case the bank assets liquidated. 2.2.9. Gross home Product (GDP)
of a country's overall output of goods and services at market prices, including net The value income from abroad there's a intensive empirical proof of negative association among boom in gross home product and non-acting loans (Louzis, Vouldis and Metaxas 2011, Khemraj and authority (2009), Salas and Suarina, 2002; Rajan & catjang pea, 2003; Fofack, 2005; and poet and Saurian, 2005). If we have a tendency to explore the explanation of this poor relationship provided by mistreatment the literature we discover that increase within the gross home product ordinarily can increase the earnings that within the long haul enhances the loan fee capability of the receiver that successively contributes to lower unhealthy loan and the other way around (Khemraj and authority, 2009).
Inflation Rates
There is also associate empirical proof of nice qualitative analysis among the inflation inside the economy and non-appearing loans (Khemraj and authority, 2009, Fofack 2005). whereas Nkusu, (2011) has outlined that this relationship is also positive or unhealthy in keeping with the author inflation influences mortgage worth potential of debtors absolutely or negatively, higher inflation will beautify the loan payment capability of receiver via lowering the important price of extraordinarily smart debt; what is more increased inflation may weaken the loan fee potential of the debtors by mistreatment decreasing the particular profits whereas salaries/wages square measure sticky, what is more by means that of highlight the operate of inflation inside the presence of variable hobby charge Nkusu additionally explains that during this situation inflation reduces the debt conjugation capability of the mortgage holders as lenders regulate the disposition interest prices to change their actual come. therefore in keeping with literature
relationship between inflation and non-performing loans is also top quality or terrible wishing on the economic system of operations.
Macroeconomic Variables
GDP and inflation are the some microeconomic variables used in this study. The total market value of all final goods services produced in a country in a given year, equal to total consumer, investment and government spending, plus the value of exports, minus the value of imports. In economics, inflation is a rise in the general level of price of goods and services in an economy over a period of time. When the general price level rises, each unit of currency buys fewer goods services. Negative effects of inflation include a decrease in the real value of money and other monetary items over time. Examining the macroeconomic factors that contribute to banking crises in Latin America during the 1990s, Gavin finds that interest rates, inflation, terms of trade, domestic income, credit growth and exchange rate regime are important constraints on loan servicing capacity. Typically, these studies finds that loan loss provisions are negatively related to GDP growth and positively related to interest rate.
The Impact of Non-Performing Loans (NPLS) Within The Banking Business
The result of non-payment of due debts on bank loaning is known with a doable failure, barrier to any loaning reduction in profit level and negative economic process within the society. failure is currently seen to be a standard development within the Nigerian banking system.Nwankwo (1990) didn't mince words once he aforementioned, once some portion of its expected capital or funds is given as loans and losses still mount and persist for many years the bank’s capital eventually becomes worn and unless extra fund is injected, the bank is also forced to liquidate.
Nwankwo (1990) any analyzed that the failure of a bank prices a spell over the complete community that function the suggests that of funding the already stricken business with the community. A run on one bank usually generate uncertainty and panic among depositors of alternative banks within the society, and therefore the effect of failure might successively be transmitted to additional remote components of the country.
Male horse (2004) emphasised the result of non-performing loans as a significant explanation for bank’s failure and absolutely explicit that, though poorly managed commerce risk will quickly sink, a failure continues to be loans that flip bitter. The on top of statement conforms with the views of Nwankwo (1990) World Health Organization control that a high level of non-performing loans mostly represent to failure that might place a stop to any loaning business relations by the affected banks, and adversely have an effect on economic development. The result of non-performing loans is devastating to Associate in nursing economy if not checked as a multiple of tailing banks will erode the boldness of the banking public and this may have a negative implication on the complete banking system.
Alo (1995) additionally submitted that a bank continued existence depends on viable loaning, keeping non-performing loan to the barest minimum. As she puts it “a high quantitative relation of non- performing loans poses a threat to the continued existence of the banks.’ She went any to stress that loan issues adversely have an effect on bank’s liquidity whereas loan losses scale back its ability to tend to alternative customers and this negatively affects the economic process. However, humans haven't been mean enough to fully forestall loan losses. The result is summarized as follows:
There is high chance of the banks affected to liquidate. Slow business turnover as new loaning cannot be created while not reimbursement of recent loans and advance. Reduction in revenue earnings by approach of interest and commission on turnover.
A bank inability to serve her varied customers expeditiously is predicated on restricted fund. Prior to the rise within the capital base of the banking system, immense invalid loans and advances has been known as a significant issue liable for the two NDIC (2002) before 2003, an oversized variety of commissioned bank will hardly pass any criteria of viability check, NPIC and alternative oversight
authority were aware that the majority banks were creating gain issue that amount it the account of banks that was placed on correct accounting basis notably with relevancy increase of interest on non-performing loans, several of the banks may be looking forward to deposited funds. Obadan (1992) additionally discovered Associate in nursing uncontrolled growth of non-performing loans and therefore the capability to jeopardize individual banks survival and threaten the state is economic stability and growth
Credit Risk Managements
the number of debt that is absolutely acquainted to be lost ought to be written off as dangerous debts.
Provision for debts might be associate financial plan account jointly named as dangerous debt expenses or uncollectable account expenses.
Hypotheses
There are two formulated Hypothesis for this studies. And they are as follows;
Hypothesis 1 Poor Credit management does not contribute significantly to non-performing loan in Nigeria banking sector
Hypothesis 2 Macroeconomic variables do not contribute significantly to non-performing loans in Nigeria banking sector.
Methodology
The aim of this study is to examine the determinants of non-performing loan in Nigeria. The analysis and interpretation of the data of an investigation are the means by which research problem is answered and the stated hypotheses are tested. The analysis would provide the basis for an examination of the effectiveness of how banks can reduce the effect of loans loss to total loans and advances given to customers. Study covers commercial banks in Nigeria, Secondary data collection method was adopted in this study. Data were collected on the dependent and independent variables for the period under review (1981-2014). The research is both analytical and descriptive. It is analytical in the sense that data supplied by the sample banks were analyzed to determine their individual debt capacities and descriptive in the existing attitudes and practices concerning non-performing loan and comparisons were measured. Population of this study consists of all Nigeria commercial banks that operate in the sector from 1981 – 2014.
Secondary data are used in this study. It was used to agree with their methodology which uses historical records and survey studies because there is no way research into the past events would be carried out without relying on secondary sources. Similarly, it serves as a source of reference for further research.
As indicated from above, secondary data were sourced from existing records and published reports.
The data for this study were extracted from the audited statement of accounts and annual reports (1981 – 2014) of all commercial banks to generate the data to be used for the analysis. Also various reports and brochure of Nigerian Deposit insurance Corporation (NDU) were sourced, CBN statistical bulletin were used in this study. Some selected corporate reports of bank were helpful.
Augmented Dickey Fuller (ADF) tests will be used for the analysis. This study examines credit risk management in Nigeria commercial banks. It explore the long run and short term relationship between the dependent variable, bad debt ratio (BDR), (our proxy for credit risk) and some independent variable – total deposits (TO), bank capital base (BCAP), total loans (TL), board independence (BIR), provision for bad debt (PBD), interest rate (INTR), gross domestic product (GDP) and total non-performing loans (TNL). The study covers existing commercial/merchant banks in Nigeria during the period under review.
The study period was thirty-one years (1981 – 2014).The pooled data were analyzed using multiple regression analysis.
The functional form of our regression model is:
TNPL = F (TD, BCAP, TL, INTR, INFL, GDP, TNL Econometric form of our regression model is:
TNPL = Į0 + Į1 TD + Į2 LNBCAP + Į3 LNTL +Į4 INTR + Į5 INFL + Į6 GDP + Į7 TNL + ɟ
Where: Į0 – Į7 = Coefficients
TNPL =Total Nonperforming Loans (our proxy for credit risk) TD = Total deposits
LNBCAP =Natural Logarithm of Bank capital base LNTL = Natural Logarithm of Total Loans
INTR = Interest rate INFL = Inflation
GDP = Gross domestic product TNL = Total non-performing loans e = Error terms
Data Analyses and Result Interpretation Data Analyses
This chapter presents the analysis and interpretation of data for this study. This study examines credit risk management in Nigerian deposit money banks. It explores the long run and short term relationships between the dependent variable, total non-performing loans (TNPL), (our proxy for credit risk) and some independent variables – total deposits (TD), total loans and advances (TLA), bank capital base (BCAP), interest rate (INTR), gross domestic product (GDP) and inflation rate (INFL). The study covers existing deposit money banks (and merchant banks during the era of universal banking) in Nigeria within the period under review. The study period is thirty four years (1981 – 2014).
First, to reduce the effect of large numbers and make the slope coefficients to be measures of elasticity of the dependent variable with respect to the independent variables, we take the natural logarithms of some of the variables - total deposits (LNTD), total loans and advances (LNTLA), bank capital (LNBCAP), and gross domestic product (LNGDP) - with large number in their series. To determine the order of integration and to avoid spurious regression, the unit roots tests are conducted at levels (with both intercept and trend) to test the null hypothesis that the series have unit roots against the alternate hypothesis that the series do not have unit roots. Using the Augmented Dickey-Fuller (ADF) tests at 95% level of significance, the results show that all the variables are not stationary at levels (because the absolute values of the ADF test statistic are lower, in many instances, than the ADF critical values (absolute) at 95% level of significance). Details of the tests are contained on table
Table 1. Unit roots test for variables at levels
Variable ADF Test Statistic ADF Critical Value @ 95% Remark
TNPL 6.0901 -3.5950 STATIONARY
TD 0.8434 -3.5950 NON-STATIONARY
TLA -1.5591 -3.5875 NON-STATIONARY
BCAP -1.5232 -3.5530 NON-STATIONARY
INTR -4.5228 -3.5806 STATIONARY
GDP 0.0120 -3.5530 NON-STATIONARY
INFR -2.3692 -3.5806 NON-STATIONARY
As shown above, all the variables are not stationary at levels. Thus, to ensure the analysis is conducted at the same order of integration, the series are transformed to their first differences and thereafter the unit root tests are repeated on the first-differenced values.
Table 2. Unit roots test for variables at first difference Variable ADF Test
Statistic ADF Critical
Value @ 95% Status Order of
Integration
DTNPL -5.0718 -3.5875 STATIONARY I(1)
DTD 3.9006 -3.6220 STATIONARY I(1)
DTLA -3.9234 -3.6220 STATIONARY I(1)
DBCAP -5.7923 -3.5806 STATIONARY I(1)
DINTR -6.0477 -3.5742 STATIONARY I(1)
DGDP -5.8117 -3.5629 STATIONARY I(1)
DINFR -5.1468 -3.5875 STATIONARY I(1)
From table 2 above, it can be seen that in each of the variable in the data series, the ADF test statistic is greater than the 95% ADF critical value (absolute values only). This is an indication that the series are stationary at first difference and thus are integrated of order one, I(1). Hence, we reject the hypothesis of the existence of unit roots (non-stationarity) for the data series. Thus, the variables are stationary at first difference and are integrated of order one [I(1)]. Therefore, the regression analysis on the transformed data will produce non-spurious results.
The next stage of the analyses involves the co-integration test.
Determination of Longrun or Equilibrium Relationship
To test for co-integration, the Engle and Granger two-stage technique is employed. Co-integration is necessary in order to determine the long run or equilibrium relationships between the dependent and independent variables. Towards this end, first, we conducted an ordinary least square (OLS) regression analysis (where we regressed, the dependent variable, total non-performing loans [LNTNPL] on the independent variables of the model) and thereafter, extract the regression residuals. The test is concluded when the unit roots test is performed on the residuals.
Table 3 shows the OLS regression results while the full regression output is contained in the appendix:
Table 3. Ordinary Least Squares Multivariate Regression Analysis
Dependent Variable TNPL
Variables Coefficient t-statistic Probability
C 4.6350 0.8298 0.4145
LNTD -0.3755 -0.7029 0.4886 LNTLA 1.5953 3.5286 0.0016*
LNBCAP 0.1214 0.4695 0.6428 INTR 0.0354 1.8964 0.0695**
LNGDP -1.5887 -1.3754 0.1812
INFR 0.0014 0.3340 0.7412
AR(1) 0.3476 1.6900 0.1035
R2 0.986
Adj. R2 0.982
F-statistic 246.68
Pro (F-statistic) 0.000000 DW= 1.81 Source: Data analysis by Researcher, November, 2015
KEY: * and ** indicate statistical significance at 1% and 10% levels respectively.
To conclude the co-integration test, the unit roots test is conducted at levels on the residuals extracted from the above regression model to test the null hypothesis that ECM has a unit root against the alternate hypothesis that ECM has no unit root. The test produced the following results on Table 4 below.
Table 4. Augmented dickey-fuller unit roots test on ECM
ADF Test Statistic Test Critical Values AT 95% Remarks
-5.3322 -3.5530 STATIONARY
From the above table, it can be observed that the absolute value of the ADF test statistic, -5.3322, is greater than the 5% critical value of -3.5530 (absolute value). This indicates that the regression residuals are stationary and that the relationships between the dependent and independent variables of the model are co-integrated and have long or equilibrium relationships. Thus, a long run or stable relationship exists between the dependent variable, total non-performing loans (LNTNPL) (our proxy for credit risk), and the independent variables – total deposits (LNTD), total loans and advances (LNTLA), bank capital (LNBCAP), interest rate (INTR), gross domestic product (LNGDP) and inflation rate (INFL).
Indeed, the long run relationship between credit risk and total deposits (LNTDA) is negative but not statistically significant. That is in the long-run, deposits availability has a moderating influence on loan creation and ultimately on credit risk. On the one hand, the relationship betwee credit risk and total loans and advances (LNTLA) are positive and statistically significant. This suggests that high rate of credit creation increases credit risk in the long-run. Similarly, banks’ capital base increases credit risk in the long run although the impact is not statistically significant. The same is true of interest. High interest rate also increases the rate of loan default and thus increases banks’ credit risk. On the other hand, inflation rate has a positive but non-statistically significant influence on credit risk in the long-run.
Short Run Dynamic Relationships
The error correction mechanism (ECM) initiated by Sargon (1984) and popularized by Engle and Granger (1987) corrects the long run or equilibrium relationship for disequilibrium. In accordance with the Granger representation theorem, two variables are co-integrated where the relationship between them can be expressed as ECM. Thus, the ECM framework shows the temporary behavior of the dependent variable given short run changes in the independent variables. In this analysis, the autoregressive distributed lags (ARDL) approach is used in estimating the ECM. The results are contained on Table 4.4 below. The adjusted R-squared criterion and information criteria (Akaike info criterion, Schwarz criterion and the Hannan-Quinn criteria) are used in selecting the parsimonious model from the over-parameterized models that is reported on the table. The Durbin Watson statistic is used to check for autocorrelation; and in conjunction with other criteria in selecting the best model from many over parameterized ECM models.
The absolute value of the ECM(-1) parameter determines how quickly the equilibrium is restored given temporary shocks in long run relationships.
As shown on Table 5 below, the results of the factors that influence credit risk (proxied in this study by total non-performing loans, DTNPL) in the Nigerian banking industry show that the goodness of fit statistic of the model is very high. The R-squared value is 0.99 while the adjusted R-squared value is 0.98, an indication that about 98% of the systematic variation in credit risk (DTNPL) is accounted for by variations in the explanatory variables including changes in the error correction term. Given that F- statistic, 132.15, passes the significant test at 1% [Prob (F-stat) =0.0000] level, this is a strong indication that the ECM model has a strong predictive power. Thus, the null hypothesis of no significant linear relationship between total non-performing loans (our proxy for credit risk) and all the independent variables of the model is rejected. Therefore, we conclude that a significant linear relationship exists between credit risk (proxied by total non-performing loans) and the independent variables. The complete parsimonious short run model is contained in the appendix.
Table 5. ARDL representation of the error correction mechanism based on the adjusted r-squared criterion
Dependent Variable:
DTNPL
Variables Coefficient t-statistic Probability
C 44.8621 1.8227 0.0883
DTNPL(-1) -0.5160 -3.9650 0.0012*
DTNPL(-2) -0.3601 -3.8458 0.0016*
DTLA 0.2097 4.0992 0.0009*
DTLA(-1) 0.2467 1.7617 0.0985 DTLA(-2) 0.2953 2.2431 0.0404**
DTD -0.4172 -9.4728 0.0000*
DTD(-1) 0.2011 1.8576 0.0830 DBCAP -4.8434 -27413 0.0151**
DCAP(-1) 5.4498 2.6157 0.0195**
DINTR 0.5127 0.1386 0.8916
DGDP -3.4634 -2.2498 0.0399**
DGDP(-1) -1.1500 -0.8649 0.4007 DINFR -0.2017 -0.2605 0.7980 DINFR(-1) -0.1322 -0.1540 0.8796 ECM(-1) -0.7941 -4.2715 0.0007*
R2 0.99
Adj. R2 0.98
F-statistic 132.15
Pro (F-statistic) 0.000000 DW=1.60
Source: Data analysis by Researcher, November, 2015
KEY: * statistically significant at 1% level; ** statistically significant at 5% level
From the above table, it is observed that the first and second year lag values of non-performing loans [DTNPL(-1) and DTNPL(-2)] have significant negative influence on credit risk. This implies that non- performing loans have some ripple effect on credit risk beyond the first year. Similarly, the current year and second year lag values of total loans and advances [DTLA and DTLA(-2)] have positive and significant impact at the 1% and 5% levels respectively on credit risk, while the impact of the one-year lag [DTLA(-1)] is also positive but not significant. These imply that the higher the volume of bank loans and advances given out by deposit money banks, the higher the associated credit risk in the short run. This seems to suggest that a bank policy that favours high rate of credit creation increases credit risk in the short-run. However, total deposits (DTD) have negative and significant impact on credit risk. That is, deposit liabilities have a moderating influence on banks’ high appetite for loan creation; and thus limit banks credit risk at least in the short run. However, the impact of banks’ capital base is significant on credit risk but the impact varies from negative to positive in the first and second year respectively.
Meanwhile interest rate (DINTR) has a positive but not significant impact on credit risk. That is, high lending rate increases the risk of default (i.e. credit risk). Nevertheless, the performance of the economy has a significant negative impact on credit risk in the first year while in the second year, the impact is not significant. This implies that economic performance limits banks’ credit risk. That is, for example a boom in the national economy promotes economic activities which enhances the ability of lenders to repay loans and thus reduces the risk of loan default and vice versa. Similarly, inflation also has a negative impact on credit risk but such impact is not significant in the short-run.
Long and Short Run Relationships and Test of Hypotheses
In both the short and long runs, total loans and advances have positive and significant impact on credit risk. That is, banks’ policies favouring high credit creation increase credit risk in the both long and short runs. Thus, we reject hypothesis one (1) which states that: poor credit management does not contribute significantly to non-performing loans in Nigeria, and conclude that poor credit management is a major determinant of credit risk amongst deposit money banks in Nigeria.
Also, previous years’ levels of non-performing loans have strong negative influence on credit risk in the short run. However, banks’ capital base has unstable influence on credit risk although the influence in the short run is significant. Also, interest rate increases credit risk in both long and short runs but the influence of lending rate on credit risk is not a strong one. Similarly, in both the long and short runs, bank deposits have negative influence on credit risk although the impact is only significant in the short-run.
This implies that bank deposits have a moderating influence on banks’ high appetite for loan creation; and thus limit banks credit risk particularly in the short run. This is not surprising because of the overriding need to protect depositors’ funds. Meanwhile, the economy exerts a negative influence on credit risk in both the long and short runs but the impact is very strong in the short run. Finally, inflation has negative impact on credit risk in the short run but the impact is positive in the long-run. However, the impact of inflation on credit risk in both short and long runs is not statistically significant.
Again, since interest and inflation rates have no significant influence on credit risk in both the long and short runs while GDP only has strong impact in the short run, we accept hypothesis two (2) that states that: macroeconomic variables do not contribute significant to non-performing loans in Nigeria; and conclude that macroeconomic variables do not exert significant impact on the credit risk of deposit money banks in Nigeria.
In the short run, any shock or deviation in the long run equilibrium values of these variables is speedily restored to equilibrium level at the rate of 79% given that the ECM coefficient is -0.79.
The parsimonious ECM model’s adjusted R-squared value of -0.99 clearly shows that the model has strong predictive power. The Durbin Watson statistic of 1.60 indicates the absence of autocorrelation in the time series data. Therefore, we conclude that the results of the regression analyses and the coefficients of the models are reliable and could be useful in prediction and for policy direction.
In conclusion, arising from this study, the major determinants of credit risk among the deposit money banks in Nigeria in both the short and long-runs are total loans and advances while previous years’ levels of non-performing loans, bank deposits, bank capital base and national economic performance are strong determinants of credit risk in the short run. Secondly, it is further concluded that while poor credit management is a major source of credit risk amongst deposit money banks in Nigeria, macroeconomic variable have no appreciable impact on credit risk.
The study recommends, among others, that deposit money banks should enact policies that ensure proper credit analysis and credit risk management. In particular, policies that encourage credit creation without due regard to credit quality should be reviewed.
Findings
This study examined credit management and the determinants of non-performing loans in Nigeria banking industry. It ascertained the impact of credit management on bank lending performance in Nigeria by examining the long run stable and short-term dynamic relationships between the dependent variable – bad debt ratio (BDR) (our proxy for credit risk) and the independent variables – total deposit (TD), bank capital base (BCAP), total loans (TL) , interest rate (INTR), inflation (INFL), gross domestic product (GDP) and total non-performing loans (TNL). The study covered a period of thirty four years (1981–
2014).
The major findings of the study are as follows:
x Gross Domestic Product is not a significant determinant of credit risk.
x Total loans and advances significantly impact credit risk.
x Total non-performing loans have significant impact on credit risk.
x Poor credit management contributed significantly to non-performing loans in the Nigerian banking sector.
x Other macro-economic variables (inflation and interest rate) do not contribute significantly to non-performing loans in the Nigerian banking sector.
x Board independence does not significantly have any impact on the level of credit risk.
However, on the short run dynamic relationships, the following findings were revealed:
x The current year value of total loans (DLNTL) has a negative but significant impact at the 1%
level on credit risk (DBDR) while the impact of the one-year lag is not significant.
x Similarly, previous year provision for bad debt (DPBD(-1) significantly impact on credit risk, also at the 1% level of significance. Meanwhile although the impact of current year non- performing loans (DTNL) on credit risk is not significant,
x The previous year level of total non-performing loans (DTNL(-1)) has negative but statistically significant impact on credit risk.
Other variables in the model including board independence (BIR), interest rate (DINTR), and inflation rate (INFL), gross domestic product (GDP) and bank capital base have no statistically significant impact on credit risk. Thus, this study indicated that board independence (BIR), interest rate (DINTR) inflation rate (INFL), gross domestic product (DGDP) and bank capital base (BCAP) are not significant determinant of credit risk in Nigeria.
Conclusion
In conclusion, bank management should pay greater attention to bank lending activities so as to minimize the incidence of bank debts in the industry. Since the relationship indicators and bad debt ratio are not statistical significant, the Nigerian banks should do all within their power to ascertain that the credit
worthy customers and other corporate bodies are given loans instead of out rightly depriving them access to loans in order to enhance the economic development of the country in no time. The level of credit management by Nigerian banks should be significantly improved upon to avoid or reduce the incidence of non-performing loans. This study will serve as a guide to banks and financial expert who are involved daily in loan analysis, disbursement and administration. It will enable banks and supervisory authorities to re-evaluate existing polies needed for non-performing loans so as to determine whether the policies need to be changed, modified or retained.
Recommendations
In relation to our findings, the following recommendations are suggested:
x The Nigerian government should put in place some banking regulations that would help oversee effective administration of loans.
x The managers of the Nigerian banks from time to time should carry out seminars with their employees on the subject of “credit management” in order to thoroughly educate the workers.
x Banks should endeavor to establish an enduring loan recovery mechanism and the various loan recovery strategies be well employed to recoup all non-performing loans.
x Banks should adopt an Efficient Loan Appraisal Techniques (ELAT) consisting of conventional investment analysis and risk measurement
x Adequate provisions for non-performing loans so as not to distort the true presentation of the bank position in their balance sheets as well as sound credit analysis.
x The banks should endeavor to diversify their investment credit portfolio, such investment should cut across three categories of loan, viz: short term, medium and long term.
x The institution of bank credit strategy that will account the cyclical aspect of economy and shifts in the composition and quantity of credit portfolio.
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