Can credit ratings predict defaults in peer-to-peer online lending? Evidence from a Chinese platform

Yu Wu and Tong Zhang

Finance Research Letters, 2021, vol. 40, issue C

Abstract: By investigating a Chinese peer-to-peer online lending platform, Renrendai, we find that the credit ratings of new borrowers do not accurately predict their default. Moreover, we find that on this platform the probability of default by new borrowers is 56%. These findings indicate that in China, in the absence of authoritative credit agencies, platforms’ assigning credit ratings themselves, not only induces high investment risk for lenders, but also high systemic risk for platforms since most of these platforms guarantee the loan principal. Our results might explain why over 86% of Chinese lending platforms experience operational difficulties.11This percentage is calculated based on data published on p2peye.com.

Keywords: Peer-to-peer online lending; Default risk; Credit rating; New borrowers (search for similar items in EconPapers)
JEL-codes: G10 G11 G14 G20 G23 G29 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:finlet:v:40:y:2021:i:c:s1544612319312772

DOI: 10.1016/j.frl.2020.101724

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