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

  • Yidi Liu
  • , Xin Li
  • , Zhiqiang Eric Zheng

Research output: Journal article publication › Journal article › Academic research › peer-review

Abstract

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.

Original languageEnglish
Pages (from-to)489-504
Number of pages16
JournalInformation Systems Research
Volume35
Issue number2
DOIs
Publication statusPublished - Jun 2024
Externally publishedYes

Keywords

  • AI
  • credit scoring
  • fintech
  • • delinquency
  • • lending
  • • natural disasters

ASJC Scopus subject areas

  • Management Information Systems
  • Information Systems
  • Computer Networks and Communications
  • Information Systems and Management
  • Library and Information Sciences

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