Determinants Impacting Default Risk in the Online Peer-to-Peer (P2P) Lending Industry: An Empirical Investigation Using Data From Indian P2P Lending Websites

The rise of the sharing economy and technological innovations has firmly established the peer-to-peer model across various industries. This study decisively examines the factors shaping default risk in Indian P2P lending platforms, leveraging data from 13 Indian P2P lending platform websites and analyzing 10 independent variables. Through OLS regression analysis, the findings clearly demonstrate that financial factors, such as higher minimum investment amounts, firm age, registration capital, credit ratings, business diversification, and digital duality, play a pivotal role in reducing default risk. In contrast, non-financial factors like excessive information disclosure, CEO education, social soft factors, and artificial intelligence usage are shown to increase risk, underscoring the critical need for balanced risk management strategies. Despite the small sample size, this study delivers significant insights and sets the stage for future research to expand the scope by incorporating additional variables and exploring long-term trends in the P2P lending landscape.