The Determinants of probability of default for digital credit by youth in Nairobi, Kenya: moderating effect of loan size

Abstract

Digital credit has been widely recognized as a form of financial inclusion in modern financial markets, with its origins in Kenya dating back over a decade through M-Shwari. This has since evolved into a market with several independent Digital Credit Providers and banks offering digital credit which are regulated by the Central Bank of Kenya. Despite its benefits, digital credit had presented challenges, particularly around consumer data protection by digital lenders and the effect of these facilities on the borrowers’ financial capability, often inducing debt distress. This is evidenced by the high rates of default that had been observed for these facilities in Kenya and other global markets. Consequently, the main objective of this study was to investigate the determinants of the probability of default for digital credit facilities by youth in Nairobi County. The specific objectives of the study were to determine the effects of borrower characteristics, loan characteristics, and lender characteristics on the probability of default for digital credit facilities by youth in Nairobi County. The borrower characteristics analysed included age, gender, default history, student loan status, marital status, level of income, occupation, and level of education. The loan characteristics investigated were the loan interest rate, loan tenure, and loan purpose. The lender characteristics explored were the lender’s business model, the applied mode of payment, and the loan appraisal period. The study was based on the adverse selection theory and the financial intermediation theory. The population of interest for this study was the Nairobi County youth and the sample size was determined using Cochran’s formula and through stratified random sampling. Primary data collection was done using structured questionnaires. A probit regression model was used to analyse the data. The study concluded that borrower characteristics, loan features, and lender practices have a positive and statistically significant influence on the probability of default on digital credit facilities among youth in Nairobi County. The study recommends that digital credit providers refine their assessment models, invest in financial literacy programs, and adopt flexible loan terms, while urging policymakers to implement regulations that enhance transparency, promote financial education, and reduce information asymmetry to improve youth access to credit and reduce default rates.

Key words: Digital credit, probability of default, youth, borrower characteristics, loan characteristics, lender characteristics, Digital Credit Providers, loan size