Unrepaid Loans and Financial Performance of Savings and Credit Co-Operatives in Kajiado County, Kenya

Abstract

The study aimed to establish how unrepaid loans affect the financial performance of savings and credit co-operatives (SACCOs) in Kajiado County, Kenya. The research objective was to examine the correlation between social factors on SACCOs' financial performance. The study was anchored on Asymmetric Information Theory, the Theory of Human Motivation, and Pecking Order Theory. The theories discussed h ighlighted the link between unrepaid loans and financial performance, suggesting that in a perfect market without taxes or transaction costs, the value of a firm with debt should match that of a firm without debt. This study used a correlation research design, and data was collected from SACCOs in Kajiado County using questionnaires. The target population comprises 372 respondents from 97 SACCOs, with a sample size of 193 respondents determined using purposive sampling and the Yamane formula. Data was analyzed through SPSS Version 25, with the results displayed using histograms and tables. The Pearson correlation method assessed the relationship between variables. The study's findings helped SACCO management better understand the factors leading to unrepaid loans and their impact on financial performance. Moreover, the government can use the results to evaluate unrepaid loans trends within Kenya's SACCO sector. Regression analysis showed a complex relationship between social factors and SACCO’s financial performance. They had a great impact, indicated by a coefficient of 0.5956 and a highly significant p-value of 0.00. This strong positive correlation indicated that improvements in social dynamics, such as robust support systems, were associated with increased likelihoods of unrepaid loans. Lenders are encouraged to consider borrowers' social environments when assessing creditworthiness, as this could play a crucial role in repayment behaviors. The study identified significant influence of social factors on unrepaid loans, highlighting the importance of understanding borrowers' social environments in credit assessments.