Consequences of China’s 2018 Online Lending Regulation and the Promise of PolicyTech

Yidi Liu (), Xin Li () and Zhiqiang (Eric) Zheng ()
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Yidi Liu: School of Management and Economics and Shenzhen Finance Institute, Chinese University of Hong Kong, Shenzhen, Shenzhen 518172, China
Xin Li: Department of Information Systems, College of Business, City University of Hong Kong, Hong Kong, China
Zhiqiang (Eric) Zheng: Department of Information Systems and Operations Management, Jindal School of Management, University of Texas at Dallas, Richardson, Texas 75080

Information Systems Research, 2024, vol. 35, issue 3, 1235-1256

Abstract: Financial regulators often focus on containing risks in financial services; however, they may not simultaneously pay adequate attention to regulation’s adverse effects. This study examines how the economic development of borrowers was affected by China’s suppressive regulation of peer-to-peer (P2P) lending in 2018, which unexpectedly switched from an “all-in” policy to an “all-shutdown” policy, leading to a massive closure of P2P lending companies and the eventual shutdown of the entire industry by 2021. Leveraging data on individuals’ credit applications, we show that this one-size-fits-all regulation obstructed borrowers’ economic development potential, especially for underprivileged and underserved borrowers, as reflected by their credit scores and their selection of financial channels. To alleviate the unintended adverse effects, we advocate using artificial intelligence (AI) to stipulate personalized regulation as a PolicyTech solution. We demonstrate that by restricting some borrowers’ access to P2P lending according to their AI-predicted financial risk, it is possible to protect borrowers’ overall economic development opportunity, while containing credit risks. This work yields significant theoretical and societal implications.

Keywords: individual economic development; P2P lending regulation; AI; fintech (search for similar items in EconPapers)
Date: 2024
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