Data-driven Technologies and Local Information Advantages in Small Business Lending

Abstract

We investigate whether banks' adoption of data-driven technologies influences competitive dynamics in local small business lending by diminishing the information advantages traditionally held by local banks. Using local newspaper closures as an adverse shock to the local information available to non-local banks, we show that banks with higher local market concentration increase their share of small business loans in their local counties after these closures. However, these information advantages gradually diminish after cloud platforms—a key data-driven technology infrastructure—are widely implemented. We find that local banks' information advantages disappear in counties where they compete against banks that heavily invest in these technologies: those with greater AI-related human capital, AI patents, or web analytics technologies. We further support our findings by instrumenting banks' AI-related hiring activity with their proximity to AI research institutions. Overall, our results suggest that data-driven technologies can reduce local banks' information advantages and reshape the competitive landscape in local lending markets.

Keywords: Data-driven Technologies, Local Information Advantages, Local Banks, Relationship Lending, Small Business Loans

JEL Classification: D80, G21, M40, O16, O30