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Peer-to-peer loan returns: heterogeneous effects across quantiles

Author

Listed:
  • Štefan Lyócsa
  • Petra Vašaničová
  • Oleg Deev

Abstract

In this study, we examine how loan and borrowers’ characteristics have a different impact on profitable and non-performing loans. Using a quantile regression profit-scoring model estimated with $472,106$472,106 loans from the U.S. P2P lending platform Lending Club, we show that higher loan amounts, loan term, interest rate and lower income are associated with lower returns for less creditworthy borrowers, i.e. for under-performed loans. Conversely, for performing loans, higher loan amounts, loan term, interest rates and lower income are associated with higher returns. We also find that borrowers’ credit (debt-to-income and FICO score) matters mostly for the tails of the return distribution, to mitigate losses for non-performing loans and improve profits for highest-performing loans. The results have broader implications for the design of credit risk models.

Suggested Citation

  • Štefan Lyócsa & Petra Vašaničová & Oleg Deev, 2025. "Peer-to-peer loan returns: heterogeneous effects across quantiles," Applied Economics Letters, Taylor & Francis Journals, vol. 32(7), pages 960-965, April.
  • Handle: RePEc:taf:apeclt:v:32:y:2025:i:7:p:960-965
    DOI: 10.1080/13504851.2023.2298412
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