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Information Asymmetry Among Investors and Strategic Bidding in Peer-to-Peer Lending

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  • Kai Lu

    (International Institute of Finance, School of Management, University of Science and Technology of China, Hefei, Anhui 230026, China)

  • Zaiyan Wei

    (Krannert School of Management, Purdue University, West Lafayette, Indiana 47907)

  • Tat Y. Chan

    (Olin Business School, Washington University in St. Louis, St. Louis, Missouri 63130)

Abstract

We study how investors in peer-to-peer (P2P) lending use their information advantages in decisions on when to place bids. Literature documents that better-informed bidders may withhold bidding until the last moment (i.e., “sniping”) to avoid competition. We argue that, because a collective effort from investors is required in P2P lending, it could be optimal for informed investors to bid early in projects with a low probability of being funded with the purpose of signaling the quality of these projects. With a unique data set from Prosper.com, we use a matching analysis to show that, for projects with low credit grades, the probability of being successfully funded is positively correlated with early bids from informed investors. For funded loans, informed investors are more likely to bid in the early stage than uninformed investors, whereas uninformed investors will follow and bid at the late stage. Finally, there are more early bids from informed investors for “good” loans than for “bad” loans, indicating that the bids are informative for the quality of those projects. Our findings have important implications for managing the information asymmetry and strategic behaviors among investors on P2P lending platforms.

Suggested Citation

  • Kai Lu & Zaiyan Wei & Tat Y. Chan, 2022. "Information Asymmetry Among Investors and Strategic Bidding in Peer-to-Peer Lending," Information Systems Research, INFORMS, vol. 33(3), pages 824-845, September.
    • Handle: RePEc:inm:orisre:v:33:y:2022:i:3:p:824-845
    DOI: 10.1287/isre.2021.1084
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    as
    1. Rajkamal Iyer & Asim Ijaz Khwaja & Erzo F. P. Luttmer & Kelly Shue, 2016. "Screening Peers Softly: Inferring the Quality of Small Borrowers," Management Science, INFORMS, vol. 62(6), pages 1554-1577, June.
    2. Ravi Bapna & Paulo Goes & Alok Gupta, 2003. "Analysis and Design of Business-to-Consumer Online Auctions," Management Science, INFORMS, vol. 49(1), pages 85-101, January.
    3. Uri Simonsohn & Dan Ariely, 2008. "When Rational Sellers Face Nonrational Buyers: Evidence from Herding on eBay," Management Science, INFORMS, vol. 54(9), pages 1624-1637, September.
    4. Yang Jiang & Yi-Chun (Chad) Ho & Xiangbin Yan & Yong Tan, 2020. "When Online Lending Meets Real Estate: Examining Investment Decisions in Lending-Based Real Estate Crowdfunding," Information Systems Research, INFORMS, vol. 31(3), pages 715-730, September.
    5. Mingfeng Lin & Siva Viswanathan, 2016. "Home Bias in Online Investments: An Empirical Study of an Online Crowdfunding Market," Management Science, INFORMS, vol. 62(5), pages 1393-1414, May.
    6. Ockenfels, Axel & Roth, Alvin E., 2006. "Late and multiple bidding in second price Internet auctions: Theory and evidence concerning different rules for ending an auction," Games and Economic Behavior, Elsevier, vol. 55(2), pages 297-320, May.
    7. Devin G. Pope & Justin R. Sydnor, 2011. "What’s in a Picture?: Evidence of Discrimination from Prosper.com," Journal of Human Resources, University of Wisconsin Press, vol. 46(1), pages 53-92.
    8. Jeffrey C. Ely & Tanjim Hossain, 2009. "Sniping and Squatting in Auction Markets," American Economic Journal: Microeconomics, American Economic Association, vol. 1(2), pages 68-94, August.
    9. Katz, Michael L & Shapiro, Carl, 1985. "Network Externalities, Competition, and Compatibility," American Economic Review, American Economic Association, vol. 75(3), pages 424-440, June.
    10. Chen, Ning & Ghosh, Arpita & Lambert, Nicolas S., 2014. "Auctions for social lending: A theoretical analysis," Games and Economic Behavior, Elsevier, vol. 86(C), pages 367-391.
    11. Freedman, Seth & Jin, Ginger Zhe, 2017. "The information value of online social networks: Lessons from peer-to-peer lending," International Journal of Industrial Organization, Elsevier, vol. 51(C), pages 185-222.
    12. Mingfeng Lin & Nagpurnanand R. Prabhala & Siva Viswanathan, 2013. "Judging Borrowers by the Company They Keep: Friendship Networks and Information Asymmetry in Online Peer-to-Peer Lending," Management Science, INFORMS, vol. 59(1), pages 17-35, August.
    13. Kei Kawai & Ken Onishi & Kosuke Uetake, 2021. "Signaling in Online Credit Markets," NBER Working Papers 29268, National Bureau of Economic Research, Inc.
    14. Juanjuan Zhang & Peng Liu, 2012. "Rational Herding in Microloan Markets," Management Science, INFORMS, vol. 58(5), pages 892-912, May.
    15. Xiaoquan (Michael) Zhang & Juan Feng, 2011. "Cyclical Bid Adjustments in Search-Engine Advertising," Management Science, INFORMS, vol. 57(9), pages 1703-1719, February.
    16. Thomas Hildebrand & Manju Puri & Jörg Rocholl, 2017. "Adverse Incentives in Crowdfunding," Management Science, INFORMS, vol. 63(3), pages 587-608, March.
    17. De Liu & Jianqing Chen & Andrew B. Whinston, 2010. "Ex Ante Information and the Design of Keyword Auctions," Information Systems Research, INFORMS, vol. 21(1), pages 133-153, March.
    18. Zaiyan Wei & Mingfeng Lin, 2017. "Market Mechanisms in Online Peer-to-Peer Lending," Management Science, INFORMS, vol. 63(12), pages 4236-4257, December.
    19. Alvin E. Roth & Axel Ockenfels, 2002. "Last-Minute Bidding and the Rules for Ending Second-Price Auctions: Evidence from eBay and Amazon Auctions on the Internet," American Economic Review, American Economic Association, vol. 92(4), pages 1093-1103, September.
    20. Xiaomeng Du & Meng Su & Xiaoquan (Michael) Zhang & Xiaona Zheng, 2017. "Bidding for Multiple Keywords in Sponsored Search Advertising: Keyword Categories and Match Types," Information Systems Research, INFORMS, vol. 28(4), pages 711-722, December.
    21. Adair Morse, 2015. "Peer-to-Peer Crowdfunding: Information and the Potential for Disruption in Consumer Lending," Annual Review of Financial Economics, Annual Reviews, vol. 7(1), pages 463-482, December.
    22. Shengsheng Xiao & Yi‐Chun (Chad) Ho & Hai Che, 2021. "Building the Momentum: Information Disclosure and Herding in Online Crowdfunding," Production and Operations Management, Production and Operations Management Society, vol. 30(9), pages 3213-3230, September.
    23. John R. Nofsinger & Richard W. Sias, 1999. "Herding and Feedback Trading by Institutional and Individual Investors," Journal of Finance, American Finance Association, vol. 54(6), pages 2263-2295, December.
    24. Adair Morse, 2015. "Peer-to-Peer Crowdfunding: Information and the Potential for Disruption in Consumer Lending," NBER Working Papers 20899, National Bureau of Economic Research, Inc.
    25. Amy Greenwald & Karthik Kannan & Ramayya Krishnan, 2010. "On Evaluating Information Revelation Policies in Procurement Auctions: A Markov Decision Process Approach," Information Systems Research, INFORMS, vol. 21(1), pages 15-36, March.
    26. Jefferson Duarte & Stephan Siegel & Lance Young, 2012. "Trust and Credit: The Role of Appearance in Peer-to-peer Lending," The Review of Financial Studies, Society for Financial Studies, vol. 25(8), pages 2455-2484.
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