A computational model of the effects of borrower default on the stability of P2P lending platforms

Abstract

Peer-to-peer (P2P) lending has attracted scholarly attention because of its economic significance and potential to democratize access to finance. However, P2P lending platforms face many challenges and failures that we need to understand more clearly. We build a computational model to study how borrower default affects P2P platform lending. We show that borrower default disrupts the P2P network formation process and undermines platform stability. Moreover, we find that defaults increase the inequality in accessing funding and provide a rationale for using curation rules, widely used in P2P platforms, in contrast to P2P insurance, which fosters cascading defaults. We also address a new trend in P2P lending platforms in which large companies (institutional investors) play an increasingly important role. We f ind that the presence of large companies creates a denser network (more loans) but generates a trade-off between making the platform more resilient to cascading defaults and more dependent on specific players. Overall, we explain how borrower defaults affect platform stability and what makes a platform vulnerable, threatening its survival. We discuss research and managerial insights into platform stability and the economic effect of P2P lending platforms.