Multiple borrowing and loan default…some empirical evidence


Financial institutions approve and disburse loans to individuals and firms to generate profit for their sustainability. However, one major challenge financial institutions face is loan default. Multiple borrowing is widely acknowledged as a major factor that contributes to loan default; but there is virtually no empirical evidence in support of this claim especially in the case of sub-Saharan African countries and Ghana in particular.

This study therefore examines the impact of multiple borrowing on loan default with evidence from small and medium enterprises (SMEs) in Ghana. The study relies on primary data and employs the binary probit regression for the analysis. The results reveal that SMEs that have multiple borrowing are more likely to default on repayment. The study therefore recommends that loan and credit officers of financial institutions should be more diligent and circumspect in their quality control checks and credit appraisal of prospective borrowers. Again, the study suggests the establishment of more Credit Reference Bureaus under the Credit Reporting Act, 2007 (Act 726) which facilitates information sharing among financial institutions about credit activities of borrowers. These measures are likely to reduce the incidence of loan default as potential defaulters will be exposed and their loan applications declined.

[The full paper can be accessed from the Ghanaian Journal of Economics, 2019, Vol. 7, No. 1]

Introduction and motivation for the research

Borrowing from financial institutions (FIs) constitutes a predominant source of financing for small and medium scale enterprises (SMEs) in developing countries (Abu et al., 2017; Nzomo, 2017; Munene et al., 2013; Cole and Wolken, 1995). SMEs’ over dependence on FIs for financial support is due to their inability to generate adequate retained earnings and also access other alternative financing sources to finance their operations (Boadi et al., 2017). According to Riding and Short (1987), the plight of SMEs are worsened especially when they have to depend on the often short-term financing sources such as bank lines of credit to finance long term projects due to lack of long term loans. The reliance on the limited short term credit (such as short-term bank loans, title loans and overdraft) leads to under financing of SMEs (Robson and Rhodes, 1984) which constrains expansion and realisation of their potentials (Egger and Kesina, 2014). In spite of the high concentration of bank finance in the SME funding structure, access to credit is widely reported to be limited (Quartey et al., 2017; Ardic et al., 2012; Abor and Biekpe, 2007). This outcome is confirmed in the case of Ghana by Aryeetey (1998) who reports that only 50 percent of all loan applications are likely to receive approval. The limited access to credit by SMEs is attributed to non-credit worthiness of entrepreneurs in the sector (Kutsuna and Crowling, 2013; Ojala and Tyrväinen, 2007; Smith, 2007).

The financing constraints notwithstanding, the role of FIs in SMEs financing cannot be overemphasised (Boadi et al., 2017; Samer et al., 2015; Mokhtar et al., 2012) considering the substantial contribution SMEs make towards the overall wellbeing of economies through poverty reduction, job creation and economic growth (Abdullah et al., 2016; Egger and Kesina, 2014; Dalberg, 2011). Financial institutions have been described as being actively involved in SMEs financing through the provision of loans to enable them realise their full potentials (Boadi et al., 2017; Boateng, 2015). In fact, Kipyego and Wandera (2013) assert that, provision of loans is one of the leading banking services offered by financial institutions. The authors further add that, FIs perform this vital role by mobilising funds from surplus units and making them available to deficit units. However, funds mobilisation is often made arduous due to the low saving culture in developing countries (Baidoo and Akoto, 2019; Baidoo et al., 2018; Mumin et al., 2013; Amu and Amu, 2012). This affects availability of loanable funds which makes FIs resort to market borrowing in order to meet the credit needs of prospective borrowers. Financial institutions therefore apply strict assessment tests to loan applications in order to determine borrowers who are likely to repay should the loan be approved and disbursed. Nonetheless, these assessments to prevent multiple borrowing and loan default sometimes proof futile due to information asymmetry (Kipyego and Wandera, 2013).

Loan default has been noted as one of the challenges increasingly affecting the operations of FIs and hinders their contribution to the success and development of SMEs in Ghana and the developing world at large (Bank of Ghana, 2017, 2016; Addae-Korankye, 2014; Munene and Guyo, 2013; Mokhtar et al., 2012). For instance, the financial stability report of Bank of Ghana covering operation of financial institutions for the first seven months of 2016 indicates that non-performing loans (NPLs) (which is defined as loans on which a borrower is neither paying the interest nor the principal amount for at least 90 days) is increasing as the figure reached GHS6.1 billion with NPL ratio of 19.1 percent (Bank of Ghana, 2016).

The report further indicates that this figure (GHS6.1billion) actually shows an increase of about 70 percent from GHS3.6 billion in 2015 (with NPL ratio of 13.1 percent). Credit to private sector contributed 85.8 percent of the total banking sector NPLs as at July 2016, whilst the public sector accounted for 14.2 percent. Subsequently, the NPLs further increased to GHS7.96 billion in 2017 from GHS6.1 billion in 2016 with NPL ratio of 21.2 percent compared with 13.1 percent and 19.1 percent in 2015 and 2016 respectively (Bank of Ghana, 2017). The rising trend in NPLs gives cause to worry as loans eventually become bad debts which tend to affects profitability and sustainability of the FIs negatively (Tilakaratna and Hulme, 2015; Wangai et al., 2014). For instance, Wangai et al. (2014) report that NPLs cause distress and sometimes the collapse of FIs which is also reported to have spiral effect on economies (Kipyego and Wandera, 2013; Munene and Guyo, 2013); it retards economic growth and increases unemployment since workers are laid off and entrepreneurs with viable investment plans may not have access to funds for such investments. Given this disquieting situation, it is imperative for researchers to examine factors that cause non-performing loans in order to address the problem of loan default.

In an attempt to curb non-performing loans and loan default phenomena, financial institutions have resorted to credit rationing. This results in prospective borrowers receiving only fractions of loans applied for which may be inadequate to meet their credit needs (Faruqee et al., 2011). To bridge this financing gap, SMEs resort to borrowing from multiple sources; a situation that has the tendency to exacerbate credit default risk. This is so because, FIs do not have the means to share credit information especially about new borrowers (Kipyego and Wandera, 2013). What is worrying is that, SMEs that borrow from multiple sources tend to delay loan repayment (see Kutsuna and Crowling, 2013; Dukuly, 2012; Fraser, 2009).

The rising incidence of multiple borrowing in recent times is attributed to proliferation of FIs in developing countries, especially micro-finance institutions which encourages loan recycling by customers (Tilakaratna and Hulme, 2015). According to Wisniwski (2010), the growth in the number of micro-finance institutions offers choice to borrowers and promotes competition for borrowers by FIs. This competition results in little attention given to loan repayment ability of these borrowers; a practice described by Bloem and Gorter (2001) as poor risk management practice of FIs credit officers. This emphasises the assertion by Kocisova and Stavarek (2018) that sustainability and stability of FIs is dependent on quality of loans approved and the ability to recoup amount disbursed. As a result, issues of loan default among FIs have attracted policy discourse and attention in the literature (see Abu et al., 2017; Jabra et al., 2017; Murthy and Mariadas, 2017; Addae-Korankye, 2014; Mokhtar et al., 2012). This is because loan default has negative repercussion not only on FIs but also on individuals, businesses and the economy as a whole. However, these studies have not emphasised the role of multiple borrowing in loan default. Again, the occurrence of multiple borrowing coupled with virtually no study regarding its impact on loan default especially on Ghana to the best of the authors’ knowledge is undoubtedly an issue of concern.

Objective and significance of the study

The study seeks to investigate the potential effect of multiple borrowing on loan default so as to avert the increasing loan default cases that has the tendency of collapsing financial institutions in the country. The contributions of the present study are vast. First, it provides the first empirical evidence on the impact of multiple borrowing on loan default in Ghana. Second, the study highlights the factors to be given the utmost attention before financial institutions approve and disburse loans to prospective borrowers. Further, the findings of this study will inform policymakers and various stakeholders including the Bank of Ghana on the strategies to be adopted in order to curb loan default which is on the ascendancy in the country. Finally, compared to all loan default studies on Ghana (see, for example, Abu et al., 2017; Addae-Korankye, 2014; Dadson, 2012) this study uses a larger sample size for analysis which facilitates the generalization of our results for effective policy purposes.

A brief theoretical underpinning and methodology

Information asymmetry (which leads to adverse selection and moral hazard) by Akerlof (1970) and Stiglitz (1982) and credit rationing (which results in a prospective borrower receiving only a fraction of loan applied for) by Stiglitz and Weiss (1981) are used to explain the link between multiple borrowing and loan default in this research. With regard to methodology, the study relies on primary data (elicited through a structured questionnaire) from small and medium scale enterprises (SMEs) in the Eastern and Greater Accra regions of Ghana. A total of 1000 questionnaires (500 in each region) were administered. However, after data cleaning and management, 710 respondents (400 and 310 from Greater Accra and Eastern regions respectively) were used for the analysis. The estimation of the potential effect of multiple borrowing on loan default is done using the binary probit regression.

Brief research findings

Consistent with the study’s a priori expectation, the results show that there is a positive relationship between multiple borrowing and loan default. This means that, SMEs that have multiple loans from different financial institutions are more likely to default on loan repayment compared with counterparts without multiple borrowing. The marginal effect from the estimation shows that having multiple borrowing increases the probability of defaulting by 98 percentage points at 1 percent significance level.

The positive relationship between multiple borrowing and loan default can be attributed to higher financial burden of borrowers. Having multiple borrowing increases firms’ indebtedness which in turn makes it difficult for firms to meet all loan repayment obligations. This result justifies Nzomo (2017) who reports that, multiple borrowing increases the indebtedness of firms and makes loan repayment very difficult. Afroze et al. (2014) also report that individuals who have multiple loans from different financial institutions often delay in loan repayment. The positive relationship in this study is also consistent with the finding by Mokhtar et al. (2012). These are studies on Kenya, Bangladesh and Malaysia respectively. Other important findings are that, larger size of management (employees in high ranking positions who oversee firm’s activities) increases the likelihood of loan default. High profit level and pledging of collateral reduce the likelihood of loan default.

Conclusions and policy recommendations

The findings from the present study have some important policy implications especially for financial institutions, SMEs, policymakers and other stakeholders in the financial industry. First, given that having multiple borrowing increases the probability of defaulting on loan repayment, the study recommends that loan and credit officers of financial institutions should be more diligent and circumspect in their quality control checks as well as credit appraisal of prospective borrowers. These will help expose borrowers who are likely to default should the loan be approved and disbursed. In addition, financial institutions can discover and avoid SMEs with multiple borrowing through the establishment of more Credit Reference Bureaus under the Credit Reporting Act, 2007 (Act 726) which facilitate information sharing among financial institutions about SMEs credit activities.

Again, based on the positive relationship between size of management and loan default, it is recommended that, SME owners should reduce the number of employees in high ranking positions who oversee the firms’ activities. This will reduce management expenses and free resources that can be used to fulfill loan repayment obligations. Moreover, the savings to be made from the reduction in management expenses such as salaries and allowances may preclude the need for additional loans to finance firms’ activities and consequently, avoid multiple borrowing.

Finally, with regard to level of profit, the study recommends that SME owners should be more innovative and efficient in their operations to increase profit to ensure that loans are paid within agreed repayment period to avoid default. Avoiding loan default will guarantee future loan approval and disbursement in order to take advantage of available investment opportunities as well as possible expansion of the firm.


I would like to acknowledge the contributions by my co-authors: Dr. Jacob Benson Aidoo (Securities and Exchange Commission, Accra), Dr. Daniel Sakyi and Prof. Hadrat Yusif (Department of Economics, KNUST-Kumasi).

The author is a PhD Candidate, Department of Economics – KNUST)

(Email: [email protected])

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