Increasing the credit limit at the initiative of the bank encourages the debtor to spend borrowed funds, a study published in Finance and Economics Discussion Series.

About four out of five credit limit increases in the United States are initiated by banks rather than as a result of customer requests. These automatic increases add than $40 billion in available credit each quarter, with much of it offered to customers who already have debt, according to the researchers.

Even though borrowers did not actually request an increase, they will, in most cases, begin to use the additional funds. The study found that revolving debt rose by about 30% after these limit increases—meaning algorithmic decision-making had become “a powerful but largely hidden driver of rising household debt burdens.”

Limits are rising for those already in debt

Much often, banks increase limits for those borrowers who already have debt. Researchers estimate that about a third of all outstanding credit card debt in the United States exists solely because of limit increases made after the card was opened. Among borrowers with low credit ratings, this figure reaches 60%.

Technologies behind growth

As Americans find themselves in credit card debt, a new study finds a link between new AI-powered algorithms and increased lending.

“Banks are using increasingly sophisticated models to predict which customers will borrow if their limit is increased. For many, this means an automatic promotion that they did not ask for and which they may not fully understand,” explained study author Agnes Kovacs, a senior lecturer in economics at the business school. King’s College London.

An automatic increase in the limit can serve as a temporary “safety cushion” to help pay bills or unexpected expenses when there is a lack of cash. But researchers warn that when algorithms target borrowers who are already in debt, the result is often borrowing and increased financial vulnerability.

How increasing the limit leads to spending

Debt only increases when customers use additional funds, but research shows that raising the limit often changes consumer behavior even if they didn’t ask for it or need it.

Thus, economist Deniz Aydin, in a large-scale field experiment, found that borrowers who received a randomly assigned increase in their line of credit over time began to borrow and spend , rather than simply saving additional funds “for a rainy day.” The results of that study were published in American Economic Review in 2022.

New work has revealed a similar pattern in the modern credit card market. When banking systems increase a customer’s limit, the outstanding balance does not remain at the same level.

The credit utilization ratio (leverage load) drops immediately as the limit becomes larger, but then gradually recovers as borrowers build up revolving debt in subsequent months—even in groups that were not previously actively using their credit.

The authors also demonstrate that lenders are likely to initiate limit increases specifically for those who already regularly have outstanding balances, which increases the likelihood of using additional funds rather than simply reserving them.

World practice in comparison

The authors found out how things stand with such unseemly practices in other countries. It turned out that in the UK, for example, there are restrictions on increasing credit limits for customers with debts without their consent, and in Canada banks are required to obtain consumer consent for any increase in the limit.

The introduction of similar protective measures in the United States would improve overall consumer welfare by about one percent and reduce the amount of revolving debt and the share of income spent on interest payments, without worsening the availability of credit, the researchers believe.

“Our model suggests that modest regulation, such as requiring consent or limiting increases for over-leveraged customers, could improve the welfare of many households while only modestly restricting access to credit. This is an example of how smart policy can guide the use of data-driven decision-making systems in the financial sector,” concluded Kovacs.