Risk-return modelling in the p2p lending market: Trends, gaps, recommendations and future directions

Abstract

• This study reviews the literature on risk-return modeling in p2p lending market. • Our research identifies the most influential works and critical references. • Our paper shows the research trends through bibliometric visualization tools. • ML support most new approaches and improve the performance of traditional models. • Several works lack explainability and a genuine understanding of business use. Peer-to-peer (P2P) lending is a market with significant growth in recent years. We review the academic literature published during the last decade on P2P lending to identify the main research trends and find potential gaps that limit stakeholders' use of research proposals. We perform both a bibliometric and systematic analysis. The bibliometric analysis will identify the most influential papers and the relationship and evolution of the main topics. In the systematic analysis, we categorized the documents according to methodological elements and business aspects. Remarkably, many proposals include artificial intelligence or machine learning algorithms. However, many of them lack a proper understanding of the application context, the definition of potential variables in a business framework, explainability, etc. Such elements should be recognized as essential elements to exploit their benefits. In this respect, we provide some recommendations and show future research directions.