An Empirical Analysis of the Determinants of Digital Credit Default in Kenya

Abstract

Kenya has a vibrant Digital Financial Services sector characterized by innovative and technology-driven products. The mobile money revolution has pioneered financial inclusion through services such as M-PESA and recently through digital credit providers such as M-Shwari, Tala and Branch among others. This paper sought to examine the determinants of digital credit default in Kenya. The objectives of the study were: i) to determine how digital illiteracy influences loan default, ii) to analyze the correlation between betting behavior and digital credit distress and iii) to assess the impact of economic shocks on the likelihood of default. The study utilized a quantitative, cross sectional research design using secondary data from the 2024 FinAccess survey in Kenya to examine the relationship between borrower characteristics and the probability of default. From a sampling frame of 20872 borrowers, stratified sampling technique was used to identify 6571 digital borrowers that formed the sample size. A probit model was estimated using maximum likelihood estimation on E-views. Findings indicate a marginal effect for illiteracy, showing that an illiterate borrower is 4.5 per cent more likely to default compared to a digitally literate one. Similarly gambling and sickness yielded 8.4 per cent and 13 per cent respectively on the probability of default. On demographic characteristics, male borrowers were found to be riskier than female, with a coefficient value of -0.037377, implying that being male increases default risk by 3.7 per cent. Income had a negative effect on default, implying that higher income reduces the probability of default. Based on these findings, the study concludes that credit default is largely contributed by a combination of factors including financial literacy, sickness, gambling and income level. The study recommends that credit reference bureau listing mechanism be reviewed to account for verifiable shocks such as illness and that gambling should be considered as one of the eligibility criteria for digital lending since it enhances default rate.