自动提高信用额度和消费者福利

Federal Reserve Board, Washington, D.C.ISSN 1936-2854 (Print)ISSN 2767-3898 (Online) Automated Credit Limit Increases and Consumer Welfare Vitaly M. Bord, Agnes Kovacs, and Patrick Moran 2025-088 NOTE: Staff working papers in the Finance and Economics Discussion Series (FEDS) are preliminarymaterials circulated to stimulate discussion and critical comment.The analysis and conclusions set forthare those of the authors and do not indicate concurrence by other members of the research staff or theBoard of Governors. References in publications to the Finance and Economics Discussion Series (other thanacknowledgement) should be cleared with the author(s) to protect the tentative character of these papers. Automated Credit Limit Increases and Consumer Welfare∗ Vitaly M. Bord†Agnes Kovacs‡Patrick Moran§ September 17, 2025 Click for most recent version Abstract In the United States, credit card companies frequently use machine learning algo-rithms to proactively raise credit limits for borrowers.In contrast, an increasingnumber of countries have begun to prohibit credit limit increases initiated by banksrather than consumers.In this paper, we exploit detailed regulatory micro datato examine the extent to which bank-initiated credit limit increases are directedtowards individuals with revolving debt. We then develop a model that capturesthe costs and benefits of regulating proactive credit limit increases, which we use toquantify their importance and evaluate the implications for household well-being. 1Introduction As algorithmic decision-making reshapes consumer finance, a critical tension has emergedbetween the efficiency of automated credit decisions and the protection of vulnerableconsumers.In the credit card market, limit increases are a particularly important butunderstudied source of credit, affecting more than 12% of accounts each year. Countriesdiffer in their approach to regulating limit increases. For example, in the United States,the overwhelming majority of these increases are implemented automatically by lendersusing proprietary models rather than requested by consumers.By contrast, reflectingconcerns about indebtedness and consumer protection, several countries have restrictedbanks’ ability to raise credit limits: for instance, the UK now prohibits limit increasesfor borrowers who have been in persistent revolving debt, while Canada prohibits bank-initiated credit limit increases without consumers’ consent. Policy makers face an important question: to what extent should they regulate algo-rithmic decision-making in credit markets, particularly when banks increase credit limitsautomatically? On the one hand, automatic credit limit increases can be beneficial, asthey relax credit constraints and give households greater flexibility to smooth consump-tion over adverse shocks.On the other hand, such increases may also be detrimental.Most of a bank’s credit card profits come from consumers who carry persistent debt(Adams et al., 2022), creating incentives for banks to direct limit increases toward theseindividuals. If some consumers struggle with self-control, additional credit may lead togreater indebtedness (Laibson, 1997; Gul and Pesendorfer, 2004). Indeed, empirical evi-dence shows that consumers borrow more after credit limit increases, even when they didnot request the increase and are not observably constrained (Gross and Souleles, 2002). In this paper, we exploit regulatory data on credit card lending to investigate who re-ceives bank-initiated credit limit increases, then develop a quantitative model to evaluatethe costs and benefits of allowing banks to proactively raise credit limits. We make threemain sets of contributions. First, in the data, we present several new stylized facts aboutthe importance of limit increases in credit card lending strategies, the role of proactivebank-initiated increases that are not requested by consumers, and their relationship torevolving debt.Second, we examine the extent to which bank-initiated credit limit in-creases are directed towards individuals with revolving debt, and consistent with existingliterature, document that debt rises after limit increases.Third, we develop a modelof household behavior that allows us to perform the first quantitative analysis of thepositive and normative implications of restricting bank-initiated credit limits increases,examining both the UK approach of prohibiting increases for revolving borrowers andthe Canadian approach of requiring explicit consumer consent. Overall, we believe ourresults have important implications for consumer protection and the emerging field of algorithmic regulation in consumer finance.Indeed, while many aspects of credit cardmarkets are regulated, there is little oversight of the factors lenders can use to proactivelyraise credit limits. Our empirical analysis utilizes regulatory data on credit card lending from FederalReserve’s Capital Assessments and Stress Testing Reports (Y-14) filed