Effect of Bank Characteristics on Loan Default in Selected Microfinance Banks in Southwest, Nigeria

Effect of Bank Characteristics on Loan Default in Selected Microfinance Banks in Southwest, Nigeria

Tunde Samson Babalola

Department Of Banking and Finance Olabisi Onabanjo University, Ago-Iwoye

DOI: https://dx.doi.org/10.47772/IJRISS.2025.907000360

Received: 03 July 2025; Accepted: 07 July 2025; Published: 18 August 2025

ABSTRACT

Loan default has become rampant in microfinance banks in Nigeria, the ratio of non-performing loan to total loans of 11% for the period 2014-2023 far exceeded the maximum 5% specified by the Central Bank of Nigeria. The huge volume of loan default has been affecting the outreach, profitability and sustainability of microfinance banks in Nigeria. This aspect of microfinance operations appears to have been sparsely investigated in Nigeria despite its negative consequences on microfinance banks. Therefore, this study investigated the of Bank Characteristics- Loan Appraisal, Loan Monitoring, Disbursement Lag and Bank Size on Loan Default in microfinance banks in Southwest, Nigeria. The study employed survey research design. Four hundred (400) structured questionnaires were administered through on-line survey as well as in-person distribution. Binary logistic regression model was used for analysis at 5% level of significance. The findings revealed that loan appraisal (β = -0.004, p = 0.032) and loan monitoring β = -0.036, p = 0.031) have significant and negative influence on loan default in microfinance banks in Southwest, Nigeria. The study concluded that bank-related factors are key micro-macro determinants of loan default in Nigerian microfinance banks. The study recommended strengthening borrower profiling, diversifying loan portfolio, enhancing loan monitoring, adopting digital credit assessment tools, leveraging credit guarantee services, and implementing the global standing instruction initiative to mitigate loan defaults.

Keywords: Loan appraisal, Loan Monitoring, Bank characteristics, Loan default, Microfinance banks.

INTRODUCTION

Background to the Study

The study of microfinance banks has been of keen interest to academic scholars, finance managers and regulatory authorities in recent years and the reasons for the this are not far-fetched. Microfinance banks constitute a major source of finance for the extremely poor members in the community who lack access to the deposit money banks because they are unable to meet the rigorous conditions of these financial institutions.

Microfinance banks play crucial roles in the lives of the poor people in urban, semi-urban and rural areas especially in developing countries. Some researchers have postulated that microfinance reduces unemployment (Manshor, et al, 2019; Muhammad & Al-Shaghdari, 2025).). When poor people are able to get credit from microfinance finance banks, they can start small businesses of their own or expand existing businesses.

Other researchers concluded that microfinance banks assist in reducing poverty (El- Nasharty, 2022; Parihar & Parihar, 2024). Yunus (2010) described microfinance as a potent anti-poverty tool. Other studies have linked microfinance with deepening of financial inclusion (Milana & Ashta, 2020; Sangeetha, 2023). The microfinance banks have deepened financial inclusion, especially in remote rural areas where deposit money banks are unable to open branches. In addition, microfinance bank credits have been positively and significantly associated with economic growth (Cole & Akintola, 2021; Sangeetha, 2023). Some researchers also found that microfinance bridges income inequality in developing countries, (Lacalle-Calderon, et al, 2018; Miled, Younsi. & Landolsi, 2022).

However, despite the foregoing laudable impact of microfinance banks on the society, the microfinance banks are currently facing some challenges which are affecting their outreach and sustainability. One of these challenges is loan default by their customers. Microfinance banks are particularly vulnerable to loan default because of information asymmetry between the banks and the borrowers. Most of the customers of microfinance banks do not have credit history that can be used to assess their credit worthiness and collateral securities are not sometimes not demanded as conditions for granting loans unlike in deposit making banks. There are growing concerns about the high incidence of loan default in microfinance banks by the operators, the regulators and other stakeholders in the finance sub-sector because of its potential adverse effects on the financial performance and sustainability of microfinance banks.

Loan default has been found to have adverse influence on the liquidity and solvency of microfinance banks and consequently on their capacity to lend money (Adamu, 2020). Furthermore, it has been observed that the financial performance of microfinance banks can be adversely affected by loan defaults (Afolabi, et al, 2020).

In the long run, loan default has grave implications on the sustainability and survival of microfinance banks. It has also been observed that loan default is a major cause of microfinance banks’ failure (Arhin, et al, 2019). Loan defaults can result in technical insolvency, a situation where the microfinance banks are unable to meet their financial obligations as and at when due.

The borrowers of microfinance banks who are unable to repay loans also have unpleasant experiences. The poor borrowers may enter into debt trap- borrowing from another bank to repay earlier loan and thereby enter into a cycle of debt trap. The defaulting borrowers may also be captured by credit bureau companies and subsequently blacklisted by microfinance banks and other institutions in the finance industry and this action forecloses the chances of such people getting loans in future. In addition, some microfinance banks often result to unethical and dehumanising methods of recovering debts.

The Central bank of Nigeria has taken various measures stem the ugly trend of loan default in the microfinance subsector of the economy including issuing of guidelines on credit policy and other matters to microfinance banks mandating microfinance banks to have a comprehensive credit policy approved by their respective Boards.

Another effort made to curb the high rate of loan default in microfinance banks in Nigeria is the approval and licensing of credit bureau agencies to gather relevant information on the credit records of individuals and companies to ascertain their status, banking habits, total unpaid debt, repayment attitude and other contractual commitments. Global Standing Instruction (GSI) was also introduced by the Central Bank of Nigeria in 2020 to ensure practical debt recovery machinery whereby unpaid loans can be recovered in a legal way from loan defaulters by debiting their accounts crediting the lending banks.

Furthermore, the Central Bank of Nigeria introduced Credit Guarantee Companies (CGCs) as part of its efforts to mitigate the impact of loan default by Micro, Small and Medium Enterprises (MSMEs) obtained from banks (including microfinance banks) and other financial institutions.

The Chartered Institute of Bankers of Nigeria, also introduced Microfinance Bank Certification Programme to equip key microfinance bank staff with critical skills to aid their performance. It is believed that equipping the staff of microfinance banks with adequate credit management skills which can assist in reducing the rate of loan default.

Despite the afore-mentioned efforts, loan default in microfinance banks remains hydra headed problem with its grave consequences This study, therefore, investigated the effect of Bank characteristics on loan default in microfinance banks, Southwest, Nigeria.

This study is centred on microfinance banks licensed by the Central Banks of Nigeria operating in Southwest, Nigeria. Out of the existing 772 licensed microfinance banks in the country as at 2023, 283 (36.66%) are located in the Southwest.

Statement of Problem

The volume of loan default among the customers of microfinance banks in Nigeria is very high and this has been impacting negatively on their operations. Loan default has been constraining the ability of microfinance banks in granting loans to people. Besides, the profitability of microfinance banks is being affected by loan defaults.

Furthermore, according to the Central Bank of Nigeria, out of 1,306 licensed microfinance banks in the country as at December 2023, 534 of them representing 40.9% have either closed down or have their licenses revoked (NDIC, 2014, 2020, 2023). One of the major causes of this mass failure of microfinance banks is poor asset quality caused by loan default (Kwanbo, 2022). The average non-performing loan in the microfinance sub-sector from 2014 to 2023 averages of 10.97%% of total loans and advances (CBN Annual Reports, 2014-2023). This portfolio at risk ratio is on the high side when compared with the Central Bank of Nigeria’s recommended maximum ratio of 5% of non-performing loans to total loans for Banks in Nigeria.

The table shows the total loans and advances, total non-performing loans and percentage of non-performing loans to total loans of microfinance banks in Nigeria for the period 2014-2023. The percentage of Non-performing Loans to Total Loans for the period averages 10.97%.

Table 1. Total Loans, Non-performing loans in Microfinance Banks from 2014-2023

Source: CBN Annual Reports

Some studies have linked bank characteristics including loan supervision, loan appraisal, disbursement lag and bank size on loan default in microfinance banks (Ogunsanwo, et al, 2020; Wafula, Muli & Bulla 2023). This study investigated the effects of bank characteristics on loan default in microfinance banks, Southwest, Nigeria.

Statement of Hypothesis

H₀1: Bank characteristics (loan supervision, loan appraisal, disbursement lag and bank size) have no significant effect loan default in microfinance banks in Southwest, Nigeria.

Figure 1. Research Model

Source: Author’s drawing, 2025.

Conceptual Framework

Addae-Korankye (2014) defines a default as the inability or failure to repay a loan, which can include various forms of loan obligations such as mortgages, bonds, loans, and notes. Central Bank of Nigeria defined lost facilities as loans on which accrued principal and/or interest are unpaid for over 180 days, and loans that are regarded as unrecoverable and are of such small amount that their continued treatment as a bankable asset is not realistic for example loans that have been abandoned, loans secured with securities that cannot be sold and loans given to judgment debtors with no collateral to foreclose in order to offset the loan. In the context of this research, loan default is defined as the situation where a borrower from a microfinance institution is unable or intentionally fails to meet their loan repayment obligations in accordance with the terms specified in the loan agreement, and the microfinance bank has made every reasonable and ethical effort to recover the outstanding loan without success.

Microfinance institutions are financial entities that gather funds through deposits and interest, which are subsequently utilized to provide credit to the very poor people who are unable to meet the rigorous requirements of the mainstream deposit money banks. Microfinance banks are financial institutions with licenses issued by Central Bank of Nigeria to pecuniary services to the less privileged people who are unable to meet the rather rigorous conditions of conventional commercial banks.

Bank characteristics are bank related attributes about its policies, procedures relationship management and size such as loan appraisal, loan monitoring, capital adequacy, branch network, disbursement lag and age of the microfinance banks.

Loan appraisal is the process of evaluation of request or proposal for loan by a financial institution to assist in deciding approval or decline of the loan. It involves character assessment of the borrower and capacity or ability of the borrower to repay the loan. If thoroughly done, loan appraisal can reduce cases of loan default.

Loan monitoring involves keeping an eye on the borrower to track the utilisation of the loan, borrower behaviour and repayment progress. This is usually done through regular visits and data gathering Sometimes some restrictions may be imposed on the borrower, for instance that all sales proceeds must be banked with only lending bank. The objectives of loan monitoring are to ensure that the utilisation of the loan is in line with the terms of the loan agreement and detect early signs of distress.

Bank size describes attributes of bank such as the capital adequacy, loan portfolio and geographical spread. Bigger banks have more resources which they can leverage on to invest in staff training, technology and information gathering for more efficient screening and monitoring of loan applicants.

Disbursement lag is the promptness with which the bank disburses the loan after processing and approval. If there is delay in disbursing loan after approval it might affect project execution and subsequently loan repayment performance.

THEORETICAL FRAMEWORK

Theory of Delegated Monitoring of Borrowers

The theory of delegated monitoring of borrowers was propounded by Diamond (1984), he maintained that investors can choose between three options: delegated monitoring (keeping money in a bank and letting the bank determine who to lend to), not monitoring at all (investing directly and trusting the borrowers), or monitoring as individual investors, with each option having its associated costs. The theory of delegated monitoring specifically pertains to the idea of entrusting the task of monitoring or oversight to a bank instead of having individual investors independently monitor the borrower.

The initial phase of delegated monitoring involves the evaluation of loan proposals. The bank collects previous information on the borrower from multiple sources, including the applicant’s past repayment history and banks from where the customer had earlier obtained loan. The second step involves assessing the applicant’s creditworthiness. This involves determining the credit score, which is used to prudently price the loan and manage the bank’s internal total lending risk.

Once a loan is approved, banks continually monitor the borrower’s transactions through their bank accounts. Delegating monitoring responsibilities to banks is a cheaper and mor effective approach than having individuals monitor a borrower independently. The objective of this theory at lowering the expenses involved in monitoring of borrowers by using available information which is very crucial in addressing challenges which may come up between the bank and its customers. One major reason for loan defaults is when borrowers use the funds for unintended purposes or divert them to other projects. To prevent this, banks also conduct post-loan processing monitoring of borrowers to ensure that the money is used as intended and not used for other purposes.

The relevance of this theory to the study lies in its emphasis on the monitoring of borrowers and their compliance with the loan agreement’s terms and conditions. To achieve this, banks usually mandate borrowers to establish and maintain accounts with them. Through this, banks can monitor the borrower’s financial transactions, including cash inflows and outflows and loan repayments.

The theory posits that banks have a comparative cost advantage in monitoring loan covenants compared with the cost of individual monitoring. Fama (1985) opines that banks, as insiders, have access to inside information in contrast with individual investors who depend information that is made available to public. Banks are therefore able to offer efficient monitoring which reduces the cost of monitoring borrowers. Diamond (1984) also argues that banks have economy of scale in monitoring borrowers. In addition, financial intermediaries are in a better position to monitor loans and screen borrowers because they have the expertise and the facilities. Delegated monitoring of borrowers to microfinance banks can therefore reduce loan default rate.

Robust loan appraisal reduces the probability of adverse selection- a situation in which borrowers who are likely to default are granted loan. Effective loan monitoring reduces the probability of moral hazards where borrowers, after obtaining loans engage in actions that may be detrimental to the interest of the bank such as engaging in risky business or diverting loan obtained for business purpose to consumption.

However, monitoring customers involves huge expenses such as staff salaries, investment in technology and other overheads which the banks usually pass on to the borrowers in form of higher interest.

The figure below illustrates delegation of monitoring of borrowers by investors or lenders to a bank which acts as intermediary. The three investors delegated monitoring of four borrowers to the bank, instead of each investor monitoring the borrowers independently.

Figure 2: Delegation of monitoring of borrowers to banks by investors

Source: Author’s drawing, 2025.

Empirical Review

Siaw, Ntiamoah, Oteng, and Opoku (2014) investigated the causes of loan delinquency in Ghana and found that loan default is significantly and positively associated with high interest rates, unfavorable repayment terms, loan disbursement delays, and the absence of monitoring.

Addae-Korankye (2014) conducted research on the factors contributing to loan delinquency in microfinance institutions in Ghana. The study used a survey design and utilized both questionnaire and an interview guide to obtain primary data. Descriptive statistics was employed for analysis. The results indicated a significant and positive correlation between loan default and loan disbursement lag, business failure, unrealistic payment schedules, high interest rates, insufficient loan sizes, unexpected events, and the absence of training.

Mphaka (2017) conducted a study on strategies to reduce loan default in microfinance institutions operating in low-income markets. Data were gathered through semi-structured interviews and descriptive statistics was used for analysis. The study found that offering favorable repayment schedules, training of borrowers and loan monitoring had significant and positive impact on loan repayment.

Abara, et al, (2017) examined the factors determining credit default risk in microfinance institutions in Assosa Zone in Ethiopia. Both primary data and secondary data were utilized while descriptive and inferential analysis logistic probit model were employed for data analysis. The study results showed that income, loan supervision, and repayment terms were negatively correlated with loan default while a significant and negative correlation was found between loan diversion and loan repayment.

Lumpur and Rahman (2018) examined strategies for reducing loan defaults in microfinance in Bangladesh. They employed structured interviews and used content analysis to analyse the data. The authors concluded that loan default has significant and positive relationship with lack of loan supervision, inadequate business advisory support, absence of experienced officers, weekly repayment requirements and absence of a reliable database.

Erena and Yadeta (2018) examined the causes of loan default in the Sabata Town Branch Office of Wasasa Microfinance S.C. in Ethiopia. Primary data was collected through questionnaires and descriptive statistics were employed for data analysis. The study identified inadequate loan assessment, high interest, operational inefficiencies, and poor customer service as positively and significantly influencing loan default. Additionally, political instability, poor business proposals, and price instability have a strong positive impact on loan delinquency.

Yeboah and Oduro (2018) studied the factors contributing to loan defaults in various cooperative societies in the Kumasi Metropolis of Ghana. The research utilised questionnaires for data gathering while binary logistic estimation and probit regression were used to analyse the data. The results indicated that education and income significantly and negatively correlated with loan default. Furthermore, loan diversion was significantly and positively correlated with loan delinquency while loan monitoring had strong and negative correlation with loan diversion.

Aidoo and Mensah (2018) investigated factors influencing loan default in microfinance banks in Ghana. The study used on six microfinance institutions located in Kumasi and Accra as case study. Using questionnaire for collecting data and descriptive statistics for analysis, the study identified high-interest rates, poor monitoring, and high utility prices as major factors with a strong positive impact on loan defaults in the country.

Karanja (2019) conducted a study in Kenya to explore the factors contributing to loan defaults in microfinance banks. Using a descriptive research method, primary data was collected through questionnaires, and the data was analysed using descriptive statistics. The study identified disbursement delays, inadequate training, poor loan appraisal, and the absence of loan monitoring as strong positive factors influencing loan delinquency. Borrower characteristics were also found to be significantly associated with loan default, and loan diversion positively related to default.

Agasha, et al, (2020) conducted research on the loan portfolio quality of microfinance institutions in Uganda. The study used exploratory research design and employed structured interviews to elicit data. The result of the content analysis showed that poor loan supervision and loan diversion had positive and significant influence on loan default.

Wafula, et al (2023) studied the effect of loan monitoring on loan default among microfinance institutions in Nairobi County. Correlation research design was used for the study and questionnaires designed on a 5-point Likert scale were employed for data collection while descriptive and inferential statistics were used for data analysis. The study concluded that effective loan monitoring significantly correlates with loan repayment performance.

Kiran and Sureshramana (2024) reviewed the literature on factors that influence loan repayment performance in microfinance institutions. Income, education level, financial literacy, and family size, repayment schedule, loan size, loan monitoring and loan appraisal were found to have significant effect on loan default.

Asongo and Adamu (2014) conducted an examination of the determinants of loan delinquency in microfinance banks, focusing on Standard Microfinance Bank in Yola, Adamawa State, Nigeria. They gathered primary data through questionnaire while descriptive and inferential statistics were used for analysis. The study revealed positive and significant relationship between loan default and high staff turnover, client dropouts, lack of loan monitoring, multiple borrowings, inexperienced staff, and failure to adhere to credit management policies.

Enimu, et al, (2017) conducted research to identify the determinants of loan repayment among agricultural microcredit finance associations in Delta State, Nigeria. Data was collected through questionnaires, and the analysis encompassed descriptive statistics and multiple regression. The study observed that age, family size, income, education, loan size, proximity to the microfinance bank office, loan monitoring, and the promptness of disbursement significantly influence loan default.

Agada, et al, (2018) conducted a study examining the determinants of loan default among Agricultural Cooperatives in Benue State, Nigeria. They collected data through structured questionnaires and employed descriptive statistics for data analysis. The findings showed that loan default loan is being significantly influenced by disbursement lag, lack of supervision, dishonesty, economic recession and non-strategic market locations.

Afolabi (2021) explored the association between credit risk practices and repayment performance in microfinance banks. Data were collected through questionnaires and ordinal logistic regression method was used for analysis. The study concluded that loan appraisal had a positive and significant influence on loan performance, whereas credit terms showed a positive but statistically insignificant relationship with loan performance. Collection procedures revealed a negative but insignificantly correlated pattern with loan performance.

Kinyua, et al (2022) examined the effect of client appraisal and loan monitoring strategies on the repayment of revolving funds in Kenya that were disbursed from 2010 to 2019. The authors employed a correlational research design, and a purposive sampling approach. Structured questionnaires were used to gather data and analysis was done using SPSS version 23. The results of analysis revealed that business assessment visits, frequency and type of training for borrowers, and the number of monitoring visits had positive and significant effect on repayment performance.

RESEARCH METHODOLOGY

This study used survey research design to collect data from staff and customers of microfinance banks are being targeted. Specifically, descriptive type of survey research was used. A cross-sectional research design was utilized, where data were collected at a single point in time from representative samples of microfinance banks and their customers in Southwest, Nigeria.

Population of the Study

The population for this study consists of the entire 283 licensed microfinance banks in Southwest Nigeria as shown in table 5.1 below. Southwest Nigeria comprises six states, Ekiti, Lagos, Ogun, Ondo, Osun, and Oyo as shown in Figure 5.1. The region is predominantly inhabited by the Yoruba ethnic group, with Yoruba being the primary language spoken; however, there are variations in dialects across the different states. There are millions of petty traders, artisans, farmers and other low-income earners who need the services of microfinance banks in the region. The estimated adult population of this region is 41,220,000 out of which 1,409,724 (6% of the adult population) estimated to be customers of microfinance banks (EFInA Survey, 2020).

Table 5.1  Number of Licensed MFBs in Southwest Nigeria

Source: Central Bank of Nigeria annual report, 2023.

Sample and Sampling Techniques

The study employed both stratified and random sampling techniques. The entire Southwest was first divided into subgroups, in this case states after which customers of microfinance banks were randomly selected in each state. The distribution of MFBs across the six states in Southwest Nigeria is highly uneven. Lagos alone accounts for 150 MFBs, while Ekiti has only 8, making it critical to ensure that each state is adequately represented. A simple random sampling (SRS) approach without stratification could result in an overrepresentation of banks from states with a larger MFB population and an under-representation from states with fewer banks. Stratification addresses this issue by dividing the banks based on their state-level distribution, ensuring that the sample is drawn proportionally to reflect the actual spread of MFBs across the region.

Model Specifications

The primary data collected was analysed using binary logistic regression. Binary logistic regression models the relationship between a set of independent variables and a binary dependent variable. The dependent variable is the status observed after the loan is disbursed, which will be 1 if it is a defaulter, and 0 if not. In this study, the logistic regression model was utilized to estimate the likelihood of loan default, considering various independent variables encompassing bank characteristics- Loan appraisal, Loan monitoring, Disbursement lag and Bank size.

The regression model is formulated as follows:

Hypothesis 1: Bank characteristics (loan monitoring, loan appraisal, disbursement lag and bank size) has no significant effect loan default in microfinance banks in Southwest, Nigeria.

The Model explored the relationship between Loan default and Bank characteristics. The independent variables in this model include loan monitoring (LM), loan appraisal (LA), disbursement lag (DT), and bank size (BS).

Log (LD/1-LD)  =    + LS + LA + DT + BS + ε

Where

LM= Loan Monitoring, LA= Loan Appraisal, DT= Disbursement lag BS= Bank size

Table 5.2  Units of measurement for Bank Characteristics

Source: Author’s Compilation, 2025.

Method of Data Collection

Primary data were gathered through structured questionnaires administered to customers of the selected microfinance banks and staff. The questionnaires addressed bank characteristics

Data Analysis and Interpretation

The study employed both online survey and structured questionnaires designed separately for two target groups: bank customers and bank staff.  A total of 400 questionnaires were distributed using stratified and random sampling techniques across 166 microfinance banks (MFBs). Of these, 372 were successfully retrieved and found suitable for analysis, resulting in a high response rate of 93%. Insights from both customers and bank officials are crucial for understanding borrower behaviour, institutional factors, risk management practices, and the macroeconomic factors contributing to loan defaults in microfinance banks in Nigeria.

Estimates for Objective: Determine the effects of bank characteristics (loan appraisal, disbursement lag and loan monitoring, bank size) on loan default in microfinance banks in Southwest, Nigeria.

Table 6.1: Logistic Regression Analysis for Bank characteristics and loan default in microfinance banks in Southwest, Nigeria

Note:  The values under the beta ( ) are the coefficients; (**) is significant at 5%.

Source: Author’s Computation (2025)

Table 6.1 presents the logistic regression analysis evaluating the effect of bank characteristics, including loan appraisal, loan monitoring, disbursement lag, and bank size, on loan default in microfinance banks in Southwest Nigeria.

Loan appraisal has a negative and statistically significant relationship with loan default ( This suggests that a more rigorous loan appraisal process reduces the likelihood of loan default. Effective appraisal ensures that only creditworthy borrowers receive loans, thereby improving repayment rates.

Loan monitoring also has a negative and significant effect on loan default  indicating that closer supervision of borrowers reduces default rates. This implies that when banks actively track loan utilization and repayment behaviours, borrowers are more likely to fulfill their obligations.

Disbursement lag does not have a significant impact on loan default  suggesting that delays in loan disbursement do not directly influence whether a borrower will default. Similarly, bank size shows no significant relationship with loan default  implying that the scale or operational size of the microfinance bank does not determine the likelihood of default.

In summary, the analysis shows that loan appraisal and loan monitoring help reduce loan default by ensuring that only creditworthy borrowers receive loans and by actively tracking loan utilisation and repayment behaviours. In contrast, disbursement lag and bank size do not have a significant impact on loan default, suggesting that delays in loan disbursement and the operational scale of microfinance banks do not directly influence borrowers’ repayment behaviour.

DISCUSSION OF FINDINGS.

The findings of the study reveal the influence of bank characteristics (loan appraisal, disbursement lag, loan monitoring, and bank size) on loan default in microfinance banks in Southwest Nigeria. Loan appraisal with p value of 0.032 which is less than 0.05 was found to have a significant and negative relationship with loan default, underscoring its importance in reducing default risks. For loans intended for business purposes, effective appraisals involve assessing the viability of business proposals and evaluating borrowers’ creditworthiness through background checks. A lack of thorough loan appraisal increases the probability of adverse selection, which in turn raises the likelihood of default, as banks may approve loans for borrowers or projects with a higher risk of non-repayment.

Loan monitoring with p value of 0.031 which is less than 0.05 was also found to exert a significant and negative influence on loan default. This aligns with the theory of delegated monitoring, which assumes that investors and depositors delegate the responsibility of overseeing borrowers to microfinance banks. Proper loan monitoring ensures that disbursed funds are used for their intended purposes and enables banks to identify and address challenges faced by borrowers at an early stage. By offering guidance and maintaining oversight, banks can reduce the risk of loan diversion and repayment challenges. Regular monitoring instills a sense of accountability in borrowers and discourages misuse of funds, which ultimately reduces default rates. Conversely, poor monitoring can lead to moral hazards such as loan mismanagement, which increases the probability of default.

Other bank characteristics such as collateral, disbursement lag, and bank size were not found to significantly influence loan default in this study. The lack of significance for these variables in this study may reflect unique circumstances in Southwest Nigeria, such as borrower characteristics, bank practices, or regional economic conditions. For example, collateral may be undervalued or weakly enforced, reducing its effectiveness as a deterrent to default, while disbursement lag might not significantly affect default if borrowers account for delays in their financial planning. The findings affirm the theoretical relevance of the theory of delegated monitoring in understanding how microfinance banks can address loan default through effective loan appraisal and monitoring practices.

CONCLUSION AND RECOMMENDATIONS

Conclusion

This study examined bank related factors that contribute to loan default in microfinance banks, in Southwest, Nigeria. The results demonstrate that loan appraisal (with p value of 0.032) and loan monitoring (with p value of 0.031) significantly influence and reduce the likelihood of loan default in microfinance banks in Southwest Nigeria. However, disbursement lag and bank size did not show significant association with loan default in microfinance bank in Southwest, Nigeria. The study therefore concludes that loan appraisal and loan monitoring have significant and negative effect on loan default in microfinance banks in Southwest, Nigeria.

Recommendations

Microfinance Banks should ensure robust loan appraisal procedures that gather comprehensive information about borrowers. Regular loan monitoring should be institutionalized to confirm the proper use of funds and identify early signs of repayment difficulties. Staff training on appraisal   techniques and monitoring best practices are also essential. To enhance their operations, microfinance institutions should invest in capacity-building for their staff; adopt technology to streamline loan appraisal and monitoring processes, and design strategies to encourage borrower accountability.

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