Graph and download economic data for Large Bank Consumer Credit Card Balances: Total Balances (RCCCBBALTOT) from Q3 2012 to Q2 2025 about FR Y-14M, credit cards, consumer credit, large, balance, loans, consumer, banks, depository institutions, and USA.

Credit card debt in the United States has been growing at a fast pace between 2021 and 2025. In the fourth quarter of 2024, the overall amount of credit card debt reached its highest value throughout the timeline considered here. COVID-19 had a big impact on the indebtedness of Americans, as credit card debt decreased from *** billion U.S. dollars in the last quarter of 2019 to *** billion U.S. dollars in the first quarter of 2021. What portion of Americans use credit cards? A substantial portion of Americans had at least one credit card in 2025. That year, the penetration rate of credit cards in the United States was ** percent. This number increased by nearly seven percentage points since 2014. The primary factors behind the high utilization of credit cards in the United States are a prevalent culture of convenience, a wide range of reward schemes, and consumer preferences for postponed payments. Which companies dominate the credit card issuing market? In 2024, the leading credit card issuers in the U.S. by volume were JPMorgan Chase & Co. and American Express. Both firms recorded transactions worth over one trillion U.S. dollars that year. Citi and Capital One were the next banks in that ranking, with the transactions made with their credit cards amounting to over half a trillion U.S. dollars that year. Those industry giants, along with other prominent brand names in the industry such as Bank of America, Synchrony Financial, Wells Fargo, and others, dominate the credit card market. Due to their extensive customer base, appealing rewards, and competitive offerings, they have gained a significant market share, making them the preferred choice for consumers.

View quarterly updates and historical trends for US Credit Card Debt. from United States. Source: Federal Reserve Bank of New York. Track economic data wi…

Debt Balance Credit Cards in the United States increased to 1.23 Trillion USD in the third quarter of 2025 from 1.21 Trillion USD in the second quarter of 2025. This dataset includes a chart with historical data for the United States Debt Balance Credit Cards.

Graph and download economic data for Large Bank Consumer Credit Card Balances: 30 or More Days Past Due Rates: Balances Based (RCCCBBALDPD30P) from Q3 2012 to Q2 2025 about 30 days +, FR Y-14M, credit cards, consumer credit, large, balance, loans, consumer, banks, depository institutions, rate, and USA.

Total credit card debt in the UK grew by over ****billion British pounds between March and April 2025, now reaching a similar level of debt as seen in early 2020. The annual growth rate of credit card debt stayed about the same in April 2025, reaching *** percent when compared to aApril 2024. The growth rate in 2024 has been decreasing until 2025 where it started to increase again, which may potentially be attributed to growing interest rates and the cost of living crisis.

Graph and download economic data for Consumer Loans: Credit Cards and Other Revolving Plans, All Commercial Banks (CCLACBW027SBOG) from 2000-06-28 to 2025-11-19 about revolving, credit cards, loans, consumer, banks, depository institutions, and USA.

In 2024, the value of outstanding credit card balances in Japan amounted to around **** trillion Japanese yen. The value increased by **** percent year on year. Credit cards have been the leading cashless payment method in Japan over the past decade.

This statistic presents the average credit card debt of Americans in 2017, by income. In that year, the credit card debt of Americans who earned more than *** thousand U.S. dollars amounted to ****** U.S. dollars.

Graph and download economic data for Large Bank Consumer Credit Card Balances: Revolving Balances Only (RCCCBBALREV) from Q3 2012 to Q2 2025 about revolving, FR Y-14M, credit cards, consumer credit, large, balance, loans, consumer, banks, depository institutions, and USA.

This statistic presents the distribution of credit card debt in the United States in 2019, by generation. In March 2019, ** percent of Millennials had not credit card debt at all, *** percentage point lower than the national rate.

United States HH Debt: Balance: New Delinquent Loan: Credit Card data was reported at 6.840 % in Mar 2020. This records a decrease from the previous number of 6.950 % for Dec 2019. United States HH Debt: Balance: New Delinquent Loan: Credit Card data is updated quarterly, averaging 8.081 % from Mar 2003 (Median) to Mar 2020, with 69 observations. The data reached an all-time high of 13.780 % in Dec 2009 and a record low of 5.073 % in Jun 2016. United States HH Debt: Balance: New Delinquent Loan: Credit Card data remains active status in CEIC and is reported by Federal Reserve Bank of New York. The data is categorized under Global Database’s United States – Table US.KB027: Household Debt.

Large Bank Credit Card Balances - Historical chart and current data through 2025.

The UK's average credit card debt per household grew by *** British pounds between December 2021 and December 2022, the first increase since 2020. Standing at ***** British pounds at December 2022, the figure contrasts with the decline in 2020 – when the debt declined from ***** British pounds to ***** British pounds. That particular drop was likely a result of Covid-19's economic impact, and consumers trying to get rid of their credit card debt. The increase in 2022 may be caused by growing interest rates and the cost of living crisis beginning to take shape.

This statistic presents median debt of credit card balances of the families in the United States in 2013, by age of family head. Families with the age of the family head between 45 and 54 years held a median debt in credit card balances of ***** U.S. dollars in the United States in 2013.

Dataset

This dataset was created by Johar M. Ashfaque

Contents

Credit Card Customer Data Description This dataset contains information about credit card customers, including their account balances, transaction behaviors, and payment patterns. The data is structured in a tabular format with the following columns:

CUST_ID: Unique identifier for each customer. BALANCE: Current balance on the credit card account. BALANCE_FREQUENCY: Frequency of the balance updates (range: 0 to 1). PURCHASES: Total purchases made with the credit card. ONEOFF_PURCHASES: Total one-off purchases made with the credit card. INSTALLMENTS_PURCHASES: Total purchases made in installments. CASH_ADVANCE: Total cash advances taken from the credit card. PURCHASES_FREQUENCY: Frequency of purchases made (range: 0 to 1). ONEOFF_PURCHASES_FREQUENCY: Frequency of one-off purchases (range: 0 to 1). PURCHASES_INSTALLMENTS_FREQUENCY: Frequency of installment purchases (range: 0 to 1). CASH_ADVANCE_FREQUENCY: Frequency of cash advances taken (range: 0 to 1). CASH_ADVANCE_TRX: Total number of cash advance transactions. PURCHASES_TRX: Total number of purchase transactions. CREDIT_LIMIT: Credit limit assigned to the customer’s account. PAYMENTS: Total payments made towards the credit card balance. MINIMUM_PAYMENTS: Minimum payments required. PRC_FULL_PAYMENT: Percentage of full payments made (range: 0 to 1). TENURE: Duration (in months) the account has been active. Insights This dataset can be used to analyze customer spending behavior, assess credit risk, and identify trends in credit card usage. It provides a comprehensive overview of customer transactions, payment patterns, and credit management.

Use Cases Customer Segmentation: Group customers based on their spending habits and payment behaviors. Credit Risk Assessment: Evaluate risk levels associated with different customer profiles. Predictive Modeling: Develop models to predict future spending or likelihood of default.

This table contains 40 series, with data starting from 1956 (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (Not all combinations are available): Geography (1 items: Canada ...), Monthly (2 items: At month-end; Average at month-end ...), Seasonal adjustment (2 items: Unadjusted; Seasonally adjusted ...), Components (10 items: Total outstanding balances; Finance companies and other institutions; Chartered banks; Total of foregoing ...).

The “Customer Credit Card Data” dataset provides valuable insights into credit card usage patterns and financial behavior. Each record represents an individual credit card holder, and the dataset includes the following features:

Id | Features | Description --|:---------|:----------- 1|**Cust_Id:** | Identification of credit card holder
2|**Balance:** | A credit card balance or Total amount left in their account to make purchases 3|**Balance_Frequency:** | How frequently the balance is updated, score between 0 and 1 (1 = frequently updated, 0 = not frequently updated) 4|**Purchases:** | Total amount of purchases made from account 5|**One_Off_Purchases:** | Maximum purchase amount done in one-go 6|**Installments_Purchases:** | Amount of purchase done in installment 7|**Cash_Advance:** | Cash in advance given by the user 8|**Purchases_Frequency:** | How frequently the Purchases are being made, score between 0 and 1 (1 = frequently purchased, 0 = not frequently purchased)
9|**One_Off_Purchases_Frequency:** | How frequently Purchases are happening in one-go (1 = frequently purchased, 0 = not frequently purchased)
10|**Purchases_Installments_Frequency:** | How frequently purchases in installments are being done (1 = frequently done, 0 = not frequently done)
11|**Cash_Advance_Frequency:** | How frequently the cash in advance being paid
12|**Cash_Advance_Trx:** | Number of Transactions made with "Cash in Advanced"
13|**Purchases_Trx:** | Number of purchase transactions made
14|**Credit_Limit:** | Limit of Credit Card for user
15|**Payments:** | Total amount of payments done by user
16|**Minimum_Payments:** | Minimum amount of payments made by user 17|**Prc_Full_Payment:** | Percentage of full payment paid by user
18|**Tenure:** | Tenure of credit card service for user

This dataset is valuable for analyzing credit card behavior, identifying trends, and building predictive models related to credit usage. Researchers, analysts, and financial institutions can leverage this data to gain deeper insights into customer profiles and optimize credit card services.

The percentage of respondents who report they paid off all credit card balances in full by their due date.