{"title":"Consequences of China’s 2018 Online Lending Regulation and the Promise of PolicyTech","authors":"Yidi Liu, Xin Li, Zhiqiang (Eric) Zheng","doi":"10.1287/isre.2021.0580","DOIUrl":null,"url":null,"abstract":"Swift and unexpected shifts of financial regulations can have profound implications for the general population. This is evidenced by China’s abrupt transition in its stance on P2P lending in 2018. Initially embracing these platforms, the abrupt regulatory pivot to widespread shutdowns. Our empirical research, drawing upon credit application data, demonstrates how this indiscriminate approach hindered economic development opportunities for a significant portion of borrowers, particularly the underprivileged. As a remedy, we advocate for the implementation of AI-driven regulatory frameworks. Rather than a monolithic approach to all borrowers, AI helps distinguish between real financial risks and those that can be managed. This nuanced strategy safeguards individuals’ economic progression, while efficiently mitigating financial hazards. For policymakers and industry stakeholders, our findings underscore the importance of contemplating the broader ramifications of regulatory decisions and harnessing innovative methodologies, such as AI, to strike an optimal balance.","PeriodicalId":48411,"journal":{"name":"Information Systems Research","volume":"47 1","pages":"0"},"PeriodicalIF":5.0000,"publicationDate":"2023-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Information Systems Research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1287/isre.2021.0580","RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"INFORMATION SCIENCE & LIBRARY SCIENCE","Score":null,"Total":0}
引用次数: 1
Abstract
Swift and unexpected shifts of financial regulations can have profound implications for the general population. This is evidenced by China’s abrupt transition in its stance on P2P lending in 2018. Initially embracing these platforms, the abrupt regulatory pivot to widespread shutdowns. Our empirical research, drawing upon credit application data, demonstrates how this indiscriminate approach hindered economic development opportunities for a significant portion of borrowers, particularly the underprivileged. As a remedy, we advocate for the implementation of AI-driven regulatory frameworks. Rather than a monolithic approach to all borrowers, AI helps distinguish between real financial risks and those that can be managed. This nuanced strategy safeguards individuals’ economic progression, while efficiently mitigating financial hazards. For policymakers and industry stakeholders, our findings underscore the importance of contemplating the broader ramifications of regulatory decisions and harnessing innovative methodologies, such as AI, to strike an optimal balance.
期刊介绍:
ISR (Information Systems Research) is a journal of INFORMS, the Institute for Operations Research and the Management Sciences. Information Systems Research is a leading international journal of theory, research, and intellectual development, focused on information systems in organizations, institutions, the economy, and society.