BORROWERS SOCIO-ECONOMIC DETERMINANTS OF LOAN REPAYMENT: A SURVEY OF PERSPECTIVE OF NANDI MSME’S OWNERS

Abstract

Loan repayment is an obligation of the borrowers in which is depended on the conditions created by the lenders. The competition in the banking sector has prompted many lenders to provide credit with fewer restrictions, and this has led to an increase in non-performing loans. Lenders have reported a larger number of defaulted or serviced loans with them moving away from security guaranteed loans. This has meant that they have to relook at ways of enhancing loan repayments. Therefore, the study sought to investigate the borrower’s socio-economic determinants of loan repayment a perspective of MSMEs in Nandi County. The specific objectives include: to establish the influence of product knowledge on loan repayments among MSMEs loan borrowers, to investigate the influence of income on loan repayments among MSMEs loan borrowers, Nandi County, to assess the influence of 5c’s on loan repayments among MSMEs loan borrowers, Nandi County, and to evaluate the influence of the firm’s value on loan repayments among MSMEs loan borrowers, Nandi County. The agency and Theory of Planned behavior (1991) were the theories that guided the study. The study did employ a descriptive research design and correlational research design. The target population of the study was 306 MSMEs loan beneficiaries registered under the trade and licensing department in 2021/2022 financial year in Nandi County. The study employed stratified simple random sampling technique to obtain 173 samples of MSMEs loan beneficiaries from the sub-counties of Nandi County. The selected samples were given self-administered structured questionnaires. The raw primary data were then analyzed using inferential and descriptive statistics. Regression and correlation analysis were the inferential statistics used by the study. Descriptive statistics showed that product knowledge, income, 5c’s and firms value influence loan repayment. Inferential findings showing that a combination of predictors (product knowledge, income, 5Cs, and firm’s value) contributes 95.7% of the loan repayments at 95% significance level. The beta values of predictors at p<0.05 include; product knowledge (𝛽1=0.103), income (𝛽2=0.212), SCs (𝛽3=0.014, and 𝛽4=0.001). The study concludes that borrower’s socio-economic determinants of loan repayment have a significant effect on loan repayment. Therefore, the study recommends policy makers in financial institutions to develop credit policies that are take consideration of socio-economic determinants that aid in reducing loan defaults.