Credit Risk Dynamics in Digital Lending via Mobile Apps: An Empirical Analysis of Alternative Data Utilization for SME Financing in West Africa

Abstract

The emergence of mobile based lending through applications has revolutionised the access of finance by the small to medium enterprises (SMEs) in West Africa, where conventional banking infrastructure fails to satisfy credit demands. This paper empirically checks the dynamics of credit risk in digital lending, using the workings of alternative data, including mobile money transactions, airtime use, and digital payment history, as risk predictors and loan decision-makers. Based on the SME loan performance data provided by mobile lending services in the chosen markets in West Africa, the results indicate that the predictive value of credit scoring models is enhanced greatly when alternative data are incorporated in comparison with traditional ones. Findings also indicate that digital lending systems are able to decrease information asymmetry and widen credit access to underbanked SMEs, but there are still difficulties pertaining to privacy of data, access to information by borrowers, regulatory framework, etc. The research offers important insights to policy makers, financial innovators and financial institutions who want to enhance SME financing by using digital credit ecosystems within emerging economies.