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Description-text related soft information in peer-to-peer lending – Evidence from two leading European platforms

Author

Listed:
  • Dorfleitner, Gregor
  • Priberny, Christopher
  • Schuster, Stephanie
  • Stoiber, Johannes
  • Weber, Martina
  • de Castro, Ivan
  • Kammler, Julia

Abstract

We examine the relation of soft factors that are derived from the description texts to the probability of successful funding and to the default probability in peer-to-peer lending for two leading European platforms. We find that spelling errors, text length and the mentioning of positive emotion evoking keywords predict the funding probability on the less restrictive of both platforms, which even accepts applications without credit scores. This platform also shows a better risk-return profile. Conditional on being funded, text-related factors hardly predict default probabilities in peer-to-peer lending for both platforms.

Suggested Citation

  • Dorfleitner, Gregor & Priberny, Christopher & Schuster, Stephanie & Stoiber, Johannes & Weber, Martina & de Castro, Ivan & Kammler, Julia, 2016. "Description-text related soft information in peer-to-peer lending – Evidence from two leading European platforms," Journal of Banking & Finance, Elsevier, vol. 64(C), pages 169-187.
    • Handle: RePEc:eee:jbfina:v:64:y:2016:i:c:p:169-187
    DOI: 10.1016/j.jbankfin.2015.11.009
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    More about this item

    Keywords

    Peer-to-peer lending; Soft information; Funding probability; Probability of default;
    All these keywords.

    JEL classification:

    • G20 - Financial Economics - - Financial Institutions and Services - - - General
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill

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