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

Abstract

The proposal for new financial products has been accompanied by new tools for risk management and profit in the Peer-to-Peer (P2P) lending market, one market in evolution, as an alternative for traditional investment and financing. For understanding this development, a systematic literature review and a bibliometric analysis of 104 papers published in the Web of Science database in the last decade are carried out using Scimat software. Our aim is to identify methodological elements, modelling components, analysis of variables and business aspects that generate opportunities for deepening its development and application. Developments of algorithms of artificial intelligence (AI) and machine learning (ML) support most of new proposals. Regulators, supervisors and users tend to increasingly seek these new alternatives in a natural project of financial digitalization demanded by technological advances, innovation and market development. Based on this study, recommendations in future research directions are provided for researchers.

A Bibliometric mapping of peer-to-peer lending research based on economic and business perspective

“…In contrast to this study, which took data from scientific publications from Scopus indexed journals. The results of the bibliometric analysis by Ariza-Garzón et al. (2021) conclude that several business problems in peer-to-peer lending have not been explored in previous literature, especially those related to fraud, debt collection, credit provision (LGD), third-party collateral warranties, etc.…”

“…Previously, there have been several studies conducting bibliometric studies in related fields. Ariza-Garzón et al. (2021) in their study identified the most influential scientific publications and study developments in the field of peer-to-peer lending using bibliometric analysis techniques.…”

“…Based on literature review related to peer-to-peer lending bibliometric studies, it can be concluded that there is a gap on the research area. The first is related to the source of publication database used, which almost all related research takes from the WoS index ( Ariza-Garzón et al., 2021 ; Ribeiro-Navarrete et al., 2021 ; Li et al., 2020 ; Martínez-climent et al., 2018 ). Considering this fact, it is clear that academics need to investigate further regarding peer-to-peer lending from an economic and business perspective as a relatively new issue.…”

How Can We Learn from Borrowers’ Online Behaviors? The Signal Effect of Borrowers’ Platform Involvement on Their Credit Risk

“…Identify borrowers' credit risk is one of the key concerns of the credit industry (Ariza-Garzon et al, 2021;Crook et al, 2007). Numerous studies have been conducted on the models used in credit scoring to identify the credit risk of borrowers more efficiently.…”

“…Providing digital credit services and issuing its products through the Internet channel has made them more convenient for Internet platforms, third-party financial institutions, as well as borrowers (Francis et al, 2017). Particularly, it expands the range of applications for credit scoring, allowing for the identification of borrowers' credit risk with more useful information (Ariza-Garzon et al, 2021).…”