Peer-to-Peer Lending and Credit Risk Assessment

Abstract

Peer-to-peer (P2P) lending platforms have emerged as a disruptive force in the financial services industry, providing an alternative to traditional banking by allowing individuals to lend and borrow money directly from each other. While P2P lending offers significant advantages, such as lower transaction costs and greater access to credit, it also presents new challenges in terms of credit risk assessment. This paper explores the role of credit risk assessment in P2P lending platforms, particularly in emerging markets like Pakistan. Using a sample of P2P lending data from 2015 to 2024, the study examines the key factors that influence the creditworthiness of borrowers, including income levels, credit history, and collateral availability. The findings suggest that while traditional credit scoring models remain useful, P2P lending platforms must incorporate alternative data sources and machine learning algorithms to improve risk assessment. The study concludes with recommendations for policymakers and P2P platforms to enhance credit risk evaluation and ensure the stability of P2P lending markets.