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P2P Lending: Information Externalities, Social Networks and Loans Substitution

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  • Faia, Ester
  • Pagel, Michaela

Abstract

Despite the lack of delegated monitor and of collateral guarantees P2P lending platforms exhibit relatively low loan and delinquency rates. The adverse selection is indeed mitigated by a new screening technology (information processing through machine learning) that provides costless public signals. Using data from Prosper and Lending Club we show that loans' spreads, proxing asymmetric information, decline with credit scores or hard information indicators and with indications from "group ties" (soft information from social networks). Also an increase in the risk of bank run in the traditional banking sector increases participation in the P2P markets and reduces their rates (substitution effect). We rationalize this evidence with a dynamic general equilibrium model where lenders and borrowers choose between traditional bank services (subject to the risk of bank runs and early liquidation) and P2P markets (which clear at a pooling price due to asymmetric information, but where public signals facilitate screening).

Suggested Citation

  • Faia, Ester & Pagel, Michaela, 2017. "P2P Lending: Information Externalities, Social Networks and Loans Substitution," CEPR Discussion Papers 12235, C.E.P.R. Discussion Papers.
  • Handle: RePEc:cpr:ceprdp:12235
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    References listed on IDEAS

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    Cited by:

    1. Liu, Zhengchi & Shang, Jennifer & Wu, Shin-yi & Chen, Pei-yu, 2020. "Social collateral, soft information and online peer-to-peer lending: A theoretical model," European Journal of Operational Research, Elsevier, vol. 281(2), pages 428-438.
    2. Giorgio Nuzzo & Stefano Piermattei, 2020. "Discussing Measures of Financial Inclusion for the Main Euro Area Countries," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 148(3), pages 765-786, April.
    3. Giorgio Nuzzo & Stefano Piermattei, 2019. "Measuring financial inclusion in the main euro area countries: the role of electronic cards," Questioni di Economia e Finanza (Occasional Papers) 504, Bank of Italy, Economic Research and International Relations Area.
    4. Bertsch, Christoph & Hull, Isaiah & Qi, Yingjie & Zhang, Xin, 2020. "Bank misconduct and online lending," Journal of Banking & Finance, Elsevier, vol. 116(C).

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    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G23 - Financial Economics - - Financial Institutions and Services - - - Non-bank Financial Institutions; Financial Instruments; Institutional Investors

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