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Information asymmetries and identification bias in P2P social microlending

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  • Frederick J. Riggins
  • David M. Weber

Abstract

The Internet has created new opportunities for peer-to-peer (P2P) social lending platforms, which have the potential to transform the way microfinance institutions raise and allocate funds used for poverty reduction. Depending upon where decision-making rights are allocated, there is the potential for identification bias whereby lenders may be motivated to give to specific projects with which they have an affinity without regard to whether it represents a sound financial investment. Using data collected from Kiva, we present empirical evidence that distant upstream lenders do not have adequate information about local business and loan conditions to make sound microfinance funding decisions, but instead make decisions based on identification biases. Furthermore, more information provided on the P2P lending site about the prospective loan does not improve the lender’s information about the loan conditions, but rather exacerbates the identification bias effect.

Suggested Citation

  • Frederick J. Riggins & David M. Weber, 2017. "Information asymmetries and identification bias in P2P social microlending," Information Technology for Development, Taylor & Francis Journals, vol. 23(1), pages 107-126, January.
    • Handle: RePEc:taf:titdxx:v:23:y:2017:i:1:p:107-126
    DOI: 10.1080/02681102.2016.1247345
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    Cited by:

    1. Gaigalienė Asta & Česnys Dovydas, 2018. "Determinants of Default in Lithuanian Peer-To-Peer Platforms," Management of Organizations: Systematic Research, Sciendo, vol. 80(1), pages 19-36, December.
    2. Liu, Aiping & Urquía-Grande, Elena & López-Sánchez, Pilar & Rodríguez-López, Ángel, 2023. "Research into microfinance and ICTs: A bibliometric analysis," Evaluation and Program Planning, Elsevier, vol. 97(C).
    3. Rendao Ye & Ya Lin, 2023. "Relationship Between Interest Rate and Risk of P2P Lending in China Based on the Skew-Normal Panel Data Model," SAGE Open, , vol. 13(4), pages 21582440231, October.
    4. Cai, Wanxiang & Polzin, Friedemann & Stam, Erik, 2021. "Crowdfunding and social capital: A systematic review using a dynamic perspective," Technological Forecasting and Social Change, Elsevier, vol. 162(C).
    5. Klepsch, Markus, 2023. "Do birds of a feather always flock together? A multidimensional examination of homophily in crowdfunding," Junior Management Science (JUMS), Junior Management Science e. V., vol. 8(1), pages 237-269.
    6. Ji-Wen Li & Qinghui Cui & Jia-Jia Zhang, 2021. "Examining failure learning in online lending: Complete failure vs. incomplete failure," PLOS ONE, Public Library of Science, vol. 16(11), pages 1-17, November.
    7. Jian Mou & J. Christopher Westland & Tuan Q. Phan & Tianhui Tan, 2020. "Microlending on mobile social credit platforms: an exploratory study using Philippine loan contracts," Electronic Commerce Research, Springer, vol. 20(1), pages 173-196, March.
    8. Kollenda, Philipp, 2022. "Financial returns or social impact? What motivates impact investors’ lending to firms in low-income countries," Journal of Banking & Finance, Elsevier, vol. 136(C).

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