U.S. Banks’ Artificial Intelligence and Small Business Lending: Evidence from the Census Bureau’s Annual Business Survey

Jeffery Piao, K. Philip Wang and Diana L. Weng

Working Papers from U.S. Census Bureau, Center for Economic Studies

Abstract: Utilizing confidential microdata from the Census Bureau’s new technology survey (technology module of the Annual Business Survey), we shed light on U.S. banks’ use of artificial intelligence (AI) and its effect on their small business lending. We find that the percentage of banks using AI increases from 14% in 2017 to 43% in 2019. Linking banks’ AI use to their small business lending, we find that banks with greater AI usage lend significantly more to distant borrowers, about whom they have less soft information. Using an instrumental variable based on banks’ proximity to AI vendors, we show that AI’s effect is likely causal. In contrast, we do not find similar effects for cloud systems, other types of software, or hardware surveyed by Census, highlighting AI’s uniqueness. Moreover, AI’s effect on distant lending is more pronounced in poorer areas and areas with less bank presence. Last, we find that banks with greater AI usage experience lower default rates among distant borrowers and charge these borrowers lower interest rates, suggesting that AI helps banks identify creditworthy borrowers at loan origination. Overall, our evidence suggests that AI helps banks reduce information asymmetry with borrowers, thereby enabling them to extend credit over greater distances.

Date: 2025-02
New Economics Papers: this item is included in nep-ain, nep-ent, nep-fdg and nep-fmk
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https://www2.census.gov/library/working-papers/2025/adrm/ces/CES-WP-25-07.pdf First version, 2025 (application/pdf)

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Persistent link: https://EconPapers.repec.org/RePEc:cen:wpaper:25-07

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