Leveraging Network Topology for Credit Risk Assessment in P2p Lending: A Comparative Study Under the Lens of Machine Learning

59 Pages Posted: 24 Aug 2023

See all articles by Lennart John Baals

Lennart John Baals

University of Twente

Yiting Liu

University of Twente; Bern University of Applied Sciences

Joerg Osterrieder

University of Twente; Bern Business School

Branka Hadji Misheva

Zurich University of Applied Sciences

Abstract

Peer-to-Peer (P2P) lending markets have witnessed remarkable growth, revolutionizing the way borrowers and lenders interact. Despite their increasing popularity, P2P lending poses significant challenges related to credit risk assessment and default prediction with meaningful implications for financial stability. Traditional credit risk models have been widely employed in the field of P2P lending; however, they may not be fully capable to capture the complexity of the loan networks and the nuances of borrower behavior that are specifically evident in P2P lending markets. Thus, in this study we propose an enhanced two-step machine learning (ML) approach that first utilises insights from network analysis and subsequently combines derived network centrality metrics with traditional credit risk factors to improve the prediction accuracy in the credit risk modelling process.

Keywords: P2P-lending, Credit-Default Prediction, machine learning (ML), Network Centrality

Suggested Citation

Baals, Lennart John and Liu, Yiting and Osterrieder, Joerg and Hadji Misheva, Branka, Leveraging Network Topology for Credit Risk Assessment in P2p Lending: A Comparative Study Under the Lens of Machine Learning. Available at SSRN: https://ssrn.com/abstract=4550985 or http://dx.doi.org/10.2139/ssrn.4550985

Lennart John Baals (Contact Author)

University of Twente ( email )

Yiting Liu

University of Twente ( email )

Postbus 217
Twente
Netherlands
(+41)798122239 (Phone)

Bern University of Applied Sciences ( email )

Quellgasse 21
CP 1180
Biel/Bienne, BE 2501
Switzerland
(+41)798122239 (Phone)

Joerg Osterrieder

University of Twente ( email )

Drienerlolaan 5
Departement of High-Tech Business and Entrepreneur
Enschede, 7522 NB
Netherlands

Bern Business School ( email )

Brückengasse
Institute of Applied Data Sciences and Finance
Bern, BE 3005
Switzerland

Branka Hadji Misheva

Zurich University of Applied Sciences ( email )

IDP
Technikumstrasse 9
Winterthur, CH 8401
Switzerland

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