期刊
INTERNATIONAL REVIEW OF FINANCIAL ANALYSIS
卷 84, 期 -, 页码 -出版社
ELSEVIER SCIENCE INC
DOI: 10.1016/j.irfa.2022.102393
关键词
Peer-to-peer lending; Credit risk; Rating manipulation; Fintech Financial inclusion
资金
- R&D Program of Beijing Municipal Education Commission [SM202210038005]
- Capital University of Economics and Business [QNTD202004]
This study found a mismatch between credit rating and default risk in P2P lending projects, and the mismatch was more pronounced in projects with high ratings, large loan amounts, and less personal information. The study questions the credibility of using internal credit ratings in related research, as they can be manipulated by the platform.
Credit rating provides essential information on a project's credit risk to both lenders and borrowers. On exploring over five million lending listings from a leading peer-to-peer (P2P) lending platform, a mismatch phenomenon was observed between credit rating and default probability of P2P listings across different credit rating groups, despite controlling for common credit-related characteristics. Further looking into the misevaluation of credit risk, it was found that this phenomenon was more pronounced when an unexpected intervention was likely to be applied in rating projects, such as listings with high credit ratings, large loan amounts, and less personal information. The study results question the credibility of related research that uses internal credit ratings, because this variable is likely to be manipulated by the platform.
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