September 2025

Automated Credit Limit Increases and Consumer Welfare

Vitaly M. Bord, Agnes Kovacs, and Patrick Moran

Abstract:

In the United States, credit card companies frequently use machine learning algorithms to proactively raise credit limits for borrowers. In contrast, an increasing number of countries have begun to prohibit credit limit increases initiated by banks rather than consumers. In this paper, we exploit detailed regulatory micro data to examine the extent to which bank-initiated credit limit increases are directed towards individuals with revolving debt. We then develop a model that captures the costs and benefits of regulating proactive credit limit increases, which we use to quantify their importance and evaluate the implications for household well-being.

Keywords: Algorithmic lending, Behavioral Finance, Consumer protection, Credit Cards, Credit limit increases, Financial regulation

DOI: https://doi.org/10.17016/FEDS.2025.088

PDF: Full Paper

Disclaimer: The economic research that is linked from this page represents the views of the authors and does not indicate concurrence either by other members of the Board's staff or by the Board of Governors. The economic research and their conclusions are often preliminary and are circulated to stimulate discussion and critical comment. The Board values having a staff that conducts research on a wide range of economic topics and that explores a diverse array of perspectives on those topics. The resulting conversations in academia, the economic policy community, and the broader public are important to sharpening our collective thinking.

Back to Top
Last Update: September 24, 2025