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

• 成果类型: Article
• 署名作者: Lu, Kai; Wei, Zaiyan; Chan, Tat Y.
• 署名单位: Chinese Academy of Sciences; University of Science & Technology of China, CAS; Purdue University System; Purdue University; Washington University (WUSTL)
• 刊物名称: INFORMATION SYSTEMS RESEARCH
• ISSN/ISSBN: 1047-7047
• DOI: 10.1287/isre.2021.1084
• 发表日期: 2022
• 页码: 824-845
• 关键词: Auctions; networks; internet; DESIGN; rules; ebay

摘要

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 frominvestors 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 frominformed investors. For funded loans, informed investors aremore 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.