Rating manipulation and creditworthiness for platform economy: Evidence from peer-to-peer lending
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 list...
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Veröffentlicht in: | International review of financial analysis 2022-11, Vol.84, p.102393, Article 102393 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | 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.
•This study uses over five million P2P listings to investigate the credit risk.•A credit risk mismatch is detected: Listings with high rating have higher default rate.•The mismatch is associated with listings asking more loans or provide less borrower information.•The mismatch is more pronounced when the release of periodical financial report is due. |
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ISSN: | 1057-5219 1873-8079 |
DOI: | 10.1016/j.irfa.2022.102393 |