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

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.

History: This paper has been accepted for the Information Systems Research Special Section on Unleashing the Power of Information Technology for Strategic Management of Disasters. Ahmed Abbasi, Robin Dillon-Merrill, H. Raghav Rao, and Olivia Sheng, Senior Editors; Zhepeng (Lionel) Li, Associate Editor.

Funding: This work was partially supported by the Research Grants Council of the Hong Kong Special Administrative Region, University Grants Committee [General Research Fund Grants 11501722 and 11500519]; the City University of Hong Kong [Strategic Research Grants 7005474 and 7005767]; the InnoHK Initiative; the government of the Hong Kong Special Administrative Region; and the Laboratory for AI-Powered Financial Technologies.

Supplemental Material: The online appendix is available at https://doi.org/10.1287/isre.2023.1230.