Jiayu Yao, Mingfeng Lin, D.J. Wu. Revealed Wisdom of the Crowd: Bids Predict Loan Quality. Under 3rd round review at Management Science.
Despite the popularity of the phrase “wisdom of the crowd,” not all crowds are wise because not everyone in them acts in an informed, rational manner. Identifying informative actions, therefore, can help to isolate the truly “wise” part of a crowd. Motivated by this idea, we evaluate the informational value of investors’ bids using data from online, debt-based crowdfunding, where we were able to track both investment decisions and ultimate repayment statuses for individual loans. We propose several easily scalable variables derived from the heterogeneity of investors’ bids in terms of size and timing. We first show that loans funded with larger bids relative to the typical bid amount in the market, or to the bidder’s historical baseline, particularly early in the bidding period, are less likely to default. More importantly, these variables improve the predictive performance of state-of-the-art models that have been proposed in this context. Even during the fundraising process, these variables improve predictions of both funding likelihood and loan quality. We discuss the implications of these variables, including loan pricing in secondary markets, crowd wisdom in different market mechanisms, and financial inclusion. Crowdfunding platforms can easily implement these variables to improve market efficiency without compromising investor privacy.
Keywords: wisdom of the crowd, platform, crowdfunding, fintech
Invited talk at Chinese University of Hong Kong, Lehigh University, Nanyang Technological University, University of Hong Kong, University of New Hampshire, University of Texas at Austin, University of Texas at San Antonio
2023 The Workshop on Information Systems Economics (WISE)
2021 MIS Quarterly Virtual Author Development Workshop
2020 Conference on Information Systems and Technology (CIST)
2020 INFORMS Annual Meeting
Jiayu Yao, Kai Lu, Mingfeng Lin. Bewildered or Empowered? The Ambiguous Effects of Information Provision on Sequential Investors. Preparing for submission.
2023 Conference on Information Systems and Technology (CIST)
2022 INFORMS Annual Meeting
2021 INFORMS Annual Meeting
Jiayu Yao, Xuan Wei, Mingfeng Lin. Beyond the Financial Value of Crowdfunding: Evidence from an Interpretable Machine Learning Approach. Manuscript in preparation.
2023 INFORMS Annual Meeting
Li Ding*, Jiayu Yao*. Learning on crowdfunding platforms: Evidence from Kickstarter. Under data analysis. (* equal contribution)