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Working Paper
Automated Credit Limit Increases and Consumer Welfare
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 ...
Discussion Paper
More Credit, More Debt: New Evidence on Automated Credit Decisions
Behind the scenes of every credit card lies an increasingly complex algorithmic infrastructure that determines who receives more credit and when, largely outside the inspection or knowledge of credit card users. Credit card issuers deploy sophisticated algorithms that continuously analyze consumer spending and borrowing behaviors, often increasing credit limits without consumers requesting such changes.