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

Kai Lu (), Zaiyan Wei () and Tat Y. Chan ()
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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

Information Systems Research, 2022, vol. 33, issue 3, 824-845

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.

Keywords: peer-to-peer lending; online auctions; information asymmetry; sniping; squatting (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (4)

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