Abstract

Given the fact that interest on loans is the major source of income of commercial banks, this makes lending the backbone of commercial banks, and despite the increasing growth of commercial banks, difficulties in recovering loans the loans pose the utmost danger to the steadiness of commercial banks. The main objective of this study was to determine s the effects of bank customer demographic on loan recovery efficiency of commercial banks in Cameroon, specifically Fako region. Specifically, the research’s objective was to determine the effect of income level, education level, age and gender on loan recovery efficiency.

The research utilized the descriptive research design and the target population was 100 bank employees of commercial banks in Fako and a sample of 80 employees derived using the Yomanne formula. The probability proportional-to-size sampling technique was used to make sure all groups of interest are represented. A questionnaire containing closed ended and Likert questions was employed gathering primary data. The data was subsequently analyzed using quantitative techniques of descriptive and inferential statistics. The descriptive statistics was done using frequency tables, means and percentages. While inferential statistics was done through regression. The data was also analyzed using the SPSS tool (statistical package for social science).

Four variables; income level, education level, age and gender were regressed against loan recovery efficiency. From the regression analysis, the P values of income level and education level were found to be <0.05 (P< 0.05) therefore the alternative hypothesis was accepted, while the P values of age and gender were >0.05 (P>0.05) thus the alternative hypothesis was rejected. The conclusion is that the is a statistical significant relationship between income level, education level and loan recovery efficiency while there is no statistical significance between age, gender and loan recovery efficiency.

This study found out that there is a relationship between bank customer demographics and loan recovery efficiency of commercial banks.

CHAPTER ONE

INTRODUCTION

1.1 Background of the study

Over the last decade, many financial institutions in the banking industry as a whole were never so serious in their efforts to ensure timely loan recovery and consequent reduction of non-performing assets (NPAs) as they are today. Loan recovery is defined as a process of pursuing loans which have not been repaid and managing to recover them by convincing the debtors to make attempts to repay their outstanding loans (Early, 2006).

The role of recovering loans is not an easy task as clients will go out of their way to prove inaccessible to the lender/bank (Garber, 1997). It is important to note that credit management process needs to start at the loan initiating stage itself. According to swanson et al (2008), effective management of loan recovery comprise of two  prolonged strategies, first relates to arresting the defaults and creation of NPA thereof and the second is to handling loan delinquencies. The tenets of financial sector reforms are revolutionary which have created a sense of urgency in the minds of staff of bank and has given them an opportunity to perform or incur losses. Commercial banks have intensified loan recovery strategies in order to reduce bad debts and improve their loan books.

According to Essendi (2013), provision of loans to borrowers is the fundamental business of any bank. in order for this lending business to contribute towards the performance of the bank, loans recovery efficiency should be in place (Essendi, 2013; Wachira, 2017; Offiong and Egbuka, 2017). Unfortunately, researchers reveal that attaining the loans recovery efficiency has remained a problem in most banks. For instance, in Vietnam, Nguyen (2016) addressed that loans recovery efficiency was very low. Factors such as local classification of assets, difficulties in checking credit profile due to absence of a transparent information system and poor monitoring and supervision of loans covenants among banks were responsible for very low loans recovery (Nguyen, 2016).

Theoretically, PRSIM model is a contemporary model used in the credit risk management in modern world. It is called PRISM, an acronym for perspective, repayment, intention, safeguards and management. Management, a PRISM component, centers on what the borrower is all about, including history and prospects. Intention or loan purposes serves as the basis for repayment. Repayment focuses on internal and external sources of cash. Internal operations and asset sales produce internal cash, whereas new debt or equity injections provide external cash sources. internal safeguards originate from the quality and soundness of financial statements, while collateral guarantees and covenants provide external safeguards. The final component, perspective pulls other sections together; the deal’s risks and rewards and the operating and financing strategies that are broad enough to have a positive on shareholder value while enabling the borrower to repay the loan (Morton Glantz 2004). This model ensures a sound credit risk management. Credit risk management should be proactive and start with the origination process. Transactions should fit the profile and expertise of the organization and make business sense on a risk adjusted basis. This helps businesses like commercial banks set safe measures to manage the credit risk of default and also efficiently recover their loans late on payment.

In Spain, Jimenez and Saurina (2002) reported that there were poor loan recovery particularly among short-term loans (3 months to 5 years) and small loans. This was because during short term lending, the Spanish banks payed very little analysis on potential risk of loans. In small loans, which were offered among individuals and small business borrowers. Loan recovery was frustrated by lack of details on the financial base and assets of the borrowers (Jimenez and Saurina, 2002).

The similar problem has been reported among African banks in different countries. For instance, in Nigeria Oke et al. (2007) found that performance of Nigerian commercial banks was affected by repayment decisions of borrowers. In addition, Offiong and Agbuka (2017) found that loan recovery rate affected negatively performance of Nigerian banks. Researchers argued that in order for the banks to attain high loan recovery they required sound credit policy.

Debeb (2015) study on the performance of Ethiopian Rural saving and credit co-operatives observed that the co-operatives’ performance was adversely affected by low loans recovery. Most borrowers did not fully repay the loans they took from the co-operatives. The researcher argued that in order to improve performance of the co-operatives in loan recovery, ensuring timely loan recovery was very essential (Debeb,2015). Reta (2011) study on loan recovery performance among bank beneficiaries in Ethiopia found that banks were not able to ensure high loans recovery among borrowers due to different abilities of the banks to engage in the recoverable loans.

Mraba (2011) study at NMB bank was reported that there was low loan recovery rate especially among borrowers who did not perform better in the business where the money was invested. Also, Luasha (2009) study at NMB bank reported that speed of loan repayment was low. This was because borrowers failed to meet conditions stipulated in loan contract forms by delaying to pay back their loans due to poor credit history of borrowers, multi-borrowing behaviors of some borrowers, high interest rate and poor bank-borrower relationship.

Cameroon in particular, despite the fact that loans remain the principal business for the performance and success of banking sector (Mafani,2013), almost all banks are struggling to attain high loan recovery efficiency. For instance, Ojong (2013) research on the factors affecting non-performing loans (NPL) at BICEC bank in Limbe observed that performance of BICEC bank was affected by high NPL which was created by diversification of funds for unnecessary expansion of business, speculations which led to investing high risk assets and unavailability of foreclosure laws and ownership rights among local and foreign investors. Commercial banks in Cameroon, Fako region specifically offers different types of loans to individuals, groups and companies and if the bank is to continue with this business, Sinkey and Mary,(2013) argued that it should ensure maximum loan recovery. Smooth loans recovery is associated with benefits both for the commercial banks and the borrowers (Godquin, 2004). Bond and Rai (2009) argued that high recovery rate helps to obtain the next higher amount of loan and other financial services. In contrast, if there is low recovery rate, both the borrowers and the bank will be affected. As the commercial banks in Fako continue into the lending business, ensuring efficiency in loans recovery is very important.

Effective loan recovery begins with oversight of the risk in individual loans. Prudent risk selection is vital to maintaining favorable loan recovery. Credit managers can now easily obtain early indicators of increasing risk by taking a more comprehensive view of the individual’s demographic characteristics (Bexley and Nemninger, 2012). In other for banks to ensure efficiency in loan recovery, loan officers must understand the vital impact individual’s demographics has on loan performance and subsequent recovery efficiency.

This motivated the researcher to analyze the effect of bank customer demographics on loan recovery efficiency of commercial banks using as case study commercial banks in Fako division.

1.2 Statement of the Problem

While lending has remained to be the principal business among customers of commercial banks, there is a critical problem of low loan recovery efficiency among banks. This poses as a problem because efficiency in loan recovery is required for the smooth running of the bank (Offiong and Egbuka, 2017). for instance, it was  observed that there was low loan recovery at Ecobank because borrowers failed to  meet loan repayment conditions by delaying payment of loans due to failures of the bank to consider poor credit history of borrowers, multi-borrowing behaviors of some borrowers, high interest rate and poor bank borrower relationship (Mafani, 2009). Also Cameroon’s debt recovery company SRC announced it was implementing a strategy to recover 33.9 billion in bad debts from the union bank of Cameroon in 2022. This amount, we learnt was the cumulative debt of 480 debtors whose identities were still not disclosed.

In order to address the problem of loan recovery, the banks have been implementing different recovery measures. These measures include careful assessment of credit standards for borrowers, portfolio risk management and attention to circumstances that may lead to deterioration in the credit standing. Other measures include providing adequate information of the penalties for loan defaults to clients and sound credit policy and strict measures such as monitoring and follow-up the borrowers.

Despite the established recovery measures among banks, concerns for what causes the loan recovery problem that commercial banks face is of importance.  Kathure (2016) observed that some of the banks hardly attain 60 percent loan recovery rate from bank borrowers. This problem did not only endanger the achievement of banks’ objectives, but also it threatened bank’s long term survival (Altman, Resti and Siron, 2012).

To some extent, the problem of low loan recovery efficiency arises from the failure of some banks to carefully profile the demographic characteristics of their clients so as to determine whether he/she is eligible for a loan or not, that is, whether the lending institution is willing to take on the risk of default.

Indeed banks do not take into consideration the changing demographics circumstances that can lead to deterioration in the credit standing and the subsequent inability to service their loans, leading to poor recovery. In a bid to survive and maintain adequate profit level in the highly competitive environment, some banks in Cameroon have tended to take excessive risks in lending loans which has led to low loan recovery. Greenidge and Grosvenor (2010) argue that the demographic characteristics of bank clients are a key element in the initiation and progression of non-performing loans which means failure to recover the loan. This study therefore seeks to analyze the effect of bank customer demographics on loan recovery efficiency of commercial banks.

1.3 Main research question

What is the effect of bank customer demographics on the loan recovery efficiency of commercial banks in Fako?

1.3.1    Specific Research Questions

1. What is the effect of income level on the loan recovery efficiency of commercial banks in Fako?
2. What is the effect of the level of education on the loan recovery efficiency of commercial banks in Fako?
3. What is the effect of age on loan recovery efficiency of commercial banks in Fako?
4. What is the effect of gender on the loan recovery efficiency of commercial banks in Fako?

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