Smart Natural Disaster Relief: Assisting Victims with Artificial Intelligence in Lending

• 成果类型: Article
• 署名作者: Liu, Yidi; Li, Xin; Zheng, Zhiqiang (Eric)
• 署名单位: The Chinese University of Hong Kong, Shenzhen; The Chinese University of Hong Kong, Shenzhen; City University of Hong Kong; University of Texas System; University of Texas Dallas
• 刊物名称: INFORMATION SYSTEMS RESEARCH
• ISSN/ISSBN: 1047-7047
• DOI: 10.1287/isre.2023.1230
• 发表日期: 2024
• 关键词: credit; RISK; INFORMATION; experience; default

摘要

Natural disasters wreak economic havoc and cause financial distress for victims. Commercial loans provided by lending firms play a key role in helping victims recover from disasters. This research note studies whether lenders' use of artificial intelligence (AI) in the lending process can, through reducing delinquency, benefit borrowers who experience natural disasters. Collaborating with a leading credit-scoring company, we track borrowers' loan applications and lenders' use of customized AI solutions in assessing loan risks. We find that borrowers who apply to AI-empowered lenders fare better in reducing delinquency rates after experiencing natural disasters. Notably, such a disaster mitigation effect is more pronounced for borrowers with lower credit scores. We explore the possible mechanisms at play and discuss the implications of our findings.