Automated credit limit increases and consumer welfare

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. • US banks proactively raise credit card limits, a practice often restricted abroad. • Limit increases supply nearly half as much credit as new credit card originations. • Limit increases most likely for revolving borrowers, who are more profitable. • Borrowing rises after limit increases, even for unconstrained consumers. • In a structural model, restricting proactive credit limit increases improves welfare.