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.

The tables and interactive maps below allow users to explore the ratio of debt to income by state, metropolitan statistical area, and county for each year since 1999. Household debt is calculated from Federal Reserve Bank of New York (FRBNY) Consumer Credit Panel/Equifax Data, and household income is reported by the Bureau of Labor Statistics.

Debt Balance Credit Cards in the United States decreased to 1.18 Trillion USD in the first quarter of 2025 from 1.21 Trillion USD in the fourth quarter of 2024. This dataset includes a chart with historical data for the United States Debt Balance Credit Cards.

Key information about United States Household Debt

• United States Household Debt reached 18,036.0 USD bn in Dec 2024, compared with the reported number of 17,943.0 USD bn in the previous quarter
• US Household Debt: USD mn data is updated quarterly, available from Mar 1999 to Dec 2024
• The data reached an all-time high of 18,036.0 USD bn in Dec 2024 and a record low of 4,540.0 USD bn in Mar 1999

• In the latest reports, United States Household Debt accounted for 61.7 % of the country's Nominal GDP in Dec 2024
• Money Supply M2 in United States increased 21,533.8 USD bn YoY in Dec 2024
• United States Foreign Exchange Reserves was measured at 34.9 USD bn in Dec 2024
• The Foreign Exchange Reserves equaled 0.1 Months of Import in Dec 2024
• United States Domestic Credit reached 30,648.3 USD bn in Mar 2024, representing an drop of 0.3 % YoY

Graph and download economic data for Consumer Loans: Credit Cards and Other Revolving Plans, All Commercial Banks (CCLACBW027SBOG) from 2000-06-28 to 2025-07-09 about revolving, credit cards, loans, consumer, banks, depository institutions, and USA.

Consumer Credit in Canada increased to 788638 CAD Million in May from 787087 CAD Million in April of 2025. This dataset provides - Canada Consumer Credit - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Graph and download economic data for Delinquency Rate on Credit Card Loans, All Commercial Banks (DRCCLACBS) from Q1 1991 to Q1 2025 about credit cards, delinquencies, commercial, loans, banks, depository institutions, rate, and USA.

Daily, weekly and monthly data showing seasonally adjusted and non-seasonally adjusted UK spending using debit and credit cards. These are official statistics in development. Source: CHAPS, Bank of England.

Debt service ratios, interest and obligated principal payments on debt, and related statistics for households, Canada.

Housing data for proportion of outstanding debt, schedule payment and financial obligations by credit type can aid with your research. This adapted Equifax data is by Canada and by average CMA size. A detailed table with each CMA is available. Both tables are broken into debt by: mortgages HELOCs lines of credit auto loans credit cards all other credit Note: Quarterly data ranges from 2019 Q1 to 2023. Source: Equifax with calculations from CMHC

Underlying data from annex B for the report that uses data from the YouGov DebtTrack surveys to update trend information about credit use and the extent of consumer indebtedness in Britain. The analysis suggests a continued decrease in the proportion of households using unsecured credit, but little change in the average amount of unsecured debt among credit users. The data also indicated a decline in the incidence of financial difficulty.

This dataset provides values for HOUSEHOLDS DEBT TO INCOME reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

Note. k = number of analyses, N = number of participants, ESr = (mean) effect size correlation r.+p

The Family Resources Survey (FRS) has been running continuously since 1992 to meet the information needs of the Department for Work and Pensions (DWP). It is almost wholly funded by DWP.

The FRS collects information from a large, and representative sample of private households in the United Kingdom (prior to 2002, it covered Great Britain only). The interview year runs from April to March.

The focus of the survey is on income, and how much comes from the many possible sources (such as employee earnings, self-employed earnings or profits from businesses, and dividends; individual pensions; state benefits, including Universal Credit and the State Pension; and other sources such as savings and investments). Specific items of expenditure, such as rent or mortgage, Council Tax and water bills, are also covered.

Many other topics are covered and the dataset has a very wide range of personal characteristics, at the adult or child, family and then household levels. These include education, caring, childcare and disability. The dataset also captures material deprivation, household food security and (new for 2021/22) household food bank usage.

The FRS is a national statistic whose results are published on the gov.uk website. It is also possible to create your own tables from FRS data, using DWP’s Stat Xplore tool. Further information can be found on the gov.uk Family Resources Survey webpage.

Secure Access FRS data
In addition to the standard End User Licence (EUL) version, Secure Access datasets, containing unrounded data and additional variables, are also available for FRS from 2005/06 onwards - see SN 9256. Prospective users of the Secure Access version of the FRS will need to fulfil additional requirements beyond those associated with the EUL datasets. Full details of the application requirements are available from http://ukdataservice.ac.uk/media/178323/secure_frs_application_guidance.pdf" style="background-color: rgb(255, 255, 255);">Guidance on applying for the Family Resources Survey: Secure Access.

FRS, HBAI and PI
The FRS underpins the related Households Below Average Income (HBAI) dataset, which focuses on poverty in the UK, and the related Pensioners' Incomes (PI) dataset. The EUL versions of HBAI and PI are held under SNs 5828 and 8503, respectively. The Secure Access versions are held under SN 7196 and 9257 (see above).

FRS 2023-24

Alongside the usual topics covered, the 2023-2024 FRS includes new variables on veterans (ex-armed forces, former regulars and reserves); care leavers (where young adults were previously living in care, during their teenage years); and, for the self-employed, length of time in that occupation. For doctors, we add clarifying variables for NHS vs private earnings streams. There are new variables on food support from friends/relatives, which complement the existing food bank and household food security set. 2023-2024 also includes Cost of Living Payment variables, including those on certain state benefits and the Warm Homes Discount scheme.

The achieved sample was over 16,500 households (28,500+ adults). A large majority of interviews were face-to-face with a minority being by telephone.

The BENUNIT table contains a raft of variables on the new material deprivation question set; see GOV.UK for background.

This version of the dataset (End User Licence) adds the DEBT table for the first time this year. The table contains responses on credit card debt, loan debt, hire purchase debt and store card debt.

Please send any feedback directly to the FRS Team Inbox: team.frs@dwp.gov.uk

Documentation

Many variables in the data files are fully labelled, but additional details can be found in the frs2324_variable_listing_eul.xlsx document.

Debt financing (mortgage, line of credit, term loan, credit card) terms and conditions, average interest rates and average length of term for small and medium enterprises in 2020 by region, CMA level, North American Industry Classification System (NAICS), demographics, age of business, employment size, rate of growth, etc.

Information on mortgage and consumer debt activity in Canada, the provinces and CMAs. These EXCEL tables give you insight on mortgage and consumer debt activity in Canada, the provinces and Census Metropolitan Areas (CMAs). This housing data looks at: mortgage holders and lenders average payments credit scores consumer debt mortgage insurance mortgage performance arrear and foreclosure rates

Households Debt in Canada decreased to 99.58 percent of GDP in the first quarter of 2025 from 100.39 percent of GDP in the fourth quarter of 2024. This dataset provides - Canada Households Debt To Gdp- actual values, historical data, forecast, chart, statistics, economic calendar and news.

Abstract copyright UK Data Service and data collection copyright owner. The Wealth and Assets Survey (WAS) is a longitudinal survey, which aims to address gaps identified in data about the economic well-being of households by gathering information on level of assets, savings and debt; saving for retirement; how wealth is distributed among households or individuals; and factors that affect financial planning. Private households in Great Britain were sampled for the survey (meaning that people in residential institutions, such as retirement homes, nursing homes, prisons, barracks or university halls of residence, and also homeless people were not included). The WAS commenced in July 2006, with a first wave of interviews carried out over two years, to June 2008. Interviews were achieved with 30,595 households at Wave 1. Those households were approached again for a Wave 2 interview between July 2008 and June 2010, and 20,170 households took part. Wave 3 covered July 2010 - June 2012, Wave 4 covered July 2012 - June 2014 and Wave 5 covered July 2014 - June 2016. Revisions to previous waves' data mean that small differences may occur between originally published estimates and estimates from the datasets held by the UK Data Service. Data are revised on a wave by wave basis, as a result of backwards imputation from the current wave's data. These revisions are due to improvements in the imputation methodology.Note from the WAS team - November 2023:“The Office for National Statistics has identified a very small number of outlier cases present in the seventh round of the Wealth and Assets Survey covering the period April 2018 to March 2020. Our current approach is to treat cases where we have reasonable evidence to suggest the values provided for specific variables are outliers. This approach did not occur for two individuals for several variables involved in the estimation of their pension wealth. While we estimate any impacts are very small overall and median pension wealth and median total wealth estimates are unaffected, this will affect the accuracy of the breakdowns of the pension wealth within the wealthiest decile, and data derived from them. We are urging caution in the interpretation of more detailed estimates.” Survey Periodicity - "Waves" to "Rounds" Due to the survey periodicity moving from “Waves” (July, ending in June two years later) to “Rounds” (April, ending in March two years later), interviews using the ‘Wave 6’ questionnaire started in July 2016 and were conducted for 21 months, finishing in March 2018. Data for round 6 covers the period April 2016 to March 2018. This comprises of the last three months of Wave 5 (April to June 2016) and 21 months of Wave 6 (July 2016 to March 2018). Round 5 and Round 6 datasets are based on a mixture of original wave-based datasets. Each wave of the survey has a unique questionnaire and therefore each of these round-based datasets are based on two questionnaires. While there may be some changes in the questionnaires, the derived variables for the key wealth estimates have not changed over this period. The aim is to collect the same data, though in some cases the exact questions asked may differ slightly. Detailed information on Moving the Wealth and Assets Survey onto a financial years’ basis was published on the ONS website in July 2019. A Secure Access version of the WAS, subject to more stringent access conditions, is available under SN 6709; it contains more detailed geographic variables than the EUL version. Users are advised to download the EUL version first (SN 7215) to see if it is suitable for their needs, before considering making an application for the Secure Access version.Further information and documentation may be found on the ONS Wealth and Assets Survey webpage. Users are advised to the check the page for updates before commencing analysis.Occupation data for 2021 and 2022 data files The ONS have identified an issue with the collection of some occupational data in 2021 and 2022 data files in a number of their surveys. While they estimate any impacts will be small overall, this will affect the accuracy of the breakdowns of some detailed (four-digit Standard Occupational Classification (SOC)) occupations, and data derived from them. None of ONS' headline statistics, other than those directly sourced from occupational data, are affected and you can continue to rely on their accuracy. For further information on this issue, please see: https://www.ons.gov.uk/news/statementsandletters/occupationaldatainonssurveys.Latest edition informationFor the 18th edition (May 2023), the inheritance variables 'ivalb1r7' and 'ivalb1r7_i' which had been omitted in error have been added. Main Topics: The WAS questionnaire is divided into two parts with all adults aged 16 years and over (excluding those aged 16 to 18 currently in full-time education) being interviewed in each responding household. Household schedule: This is completed by one person in the household (usually the head of household or their partner) and predominantly collects household level information such as the number, demographics and relationship of individuals to each other, as well as information about the ownership, value and mortgages on the residence and other household assets. Individual schedule: This is given to each adult in the household and asks questions about economic status, education and employment, business assets, benefits and tax credits, saving attitudes and behaviour, attitudes to debt, insolvency, major items of expenditure, retirement, attitudes to saving for retirement, pensions, financial assets, non-mortgage debt, investments and other income. Multi-stage stratified random sample Telephone interview Face-to-face interview 2006 2020 ADOPTION PAY AGE AIRCRAFT ASSETS ATTITUDES TO SAVING BANK ACCOUNTS BICYCLES BOATS BONDS BUSINESS OWNERSHIP BUSINESS RECORDS BUSINESSES CARAVANS CARE OF DEPENDANTS CARERS BENEFITS CARS CHILD BENEFITS CHILD SUPPORT PAYMENTS CHILD TRUST FUNDS COHABITING COMMERCIAL BUILDINGS COST OF LIVING COSTS CREDIT CARD USE DEBILITATIVE ILLNESS DEBTS DISABILITIES EARLY RETIREMENT ECONOMIC ACTIVITY EDUCATIONAL BACKGROUND EDUCATIONAL COURSES EDUCATIONAL FEES EDUCATIONAL STATUS EMPLOYEES EMPLOYMENT EMPLOYMENT HISTORY EMPLOYMENT PROGRAMMES ENDOWMENT ASSURANCE ESTATES ETHNIC GROUPS FAMILY BENEFITS FAMILY INCOME FAMILY MEMBERS FINANCIAL ADVICE FINANCIAL COMPENSATION FINANCIAL DIFFICULTIES FINANCIAL SERVICES FRINGE BENEFITS FULL TIME EMPLOYMENT FURNISHED ACCOMMODA... GIFTS Great Britain HEALTH HEALTH STATUS HIRE PURCHASE HOME BUILDINGS INSU... HOME BUYING HOME CONTENTS INSUR... HOME OWNERSHIP HOUSE PRICES HOUSEHOLD BUDGETS HOUSEHOLD HEAD S EC... HOUSEHOLD HEAD S SO... HOUSEHOLD INCOME HOUSEHOLDERS HOUSEHOLDS HOUSING AGE HOUSING ECONOMICS HOUSING FINANCE HOUSING TENURE ILL HEALTH INCOME INCONTINENCE INFORMAL CARE INHERITANCE INSOLVENCIES INSURANCE CLAIMS INTELLECTUAL IMPAIR... INVESTMENT Income JOB HUNTING JOB SEEKER S ALLOWANCE LAND OWNERSHIP LANDLORDS LOANS Labour and employment MAIL ORDER SERVICES MARITAL STATUS MATERNITY BENEFITS MATERNITY PAY MATHEMATICS MOBILE HOMES MORTGAGE ARREARS MORTGAGE PROTECTION... MORTGAGES MOTOR VEHICLE VALUE MOTOR VEHICLES MOTORCYCLES OCCUPATIONAL PENSIONS OCCUPATIONAL QUALIF... OCCUPATIONS OLD AGE BENEFITS ONE PARENT FAMILIES OVERDRAFTS PART TIME EMPLOYMENT PARTNERSHIPS BUSINESS PATERNITY BENEFITS PATERNITY PAY PENSION BENEFITS PENSION CONTRIBUTIONS PENSIONS PERSONAL DEBT REPAY... PERSONAL FINANCE MA... PHYSICAL MOBILITY PLACE OF BIRTH PRIVATE PENSIONS PRIVATE PERSONAL PE... PROFIT SHARING PROFITS QUALIFICATIONS REDUNDANCY PAY RELIGIOUS AFFILIATION RELIGIOUS ATTENDANCE RENTED ACCOMMODATION RENTS RESIDENTIAL BUILDINGS RETIREMENT AGE SAVINGS SAVINGS ACCOUNTS AN... SECOND HOMES SELF EMPLOYED SELLING SHARED HOME OWNERSHIP SHARES SICK PAY SICKNESS AND DISABI... SOCIAL HOUSING SOCIAL SECURITY BEN... SOCIO ECONOMIC STATUS SPOUSES STAKEHOLDER PENSIONS STATE RETIREMENT PE... STATUS IN EMPLOYMENT STUDENT LOANS SUBSIDIARY EMPLOYMENT SUPERVISORY STATUS TAX RELIEF TENANTS HOME PURCHA... TIED HOUSING TOP MANAGEMENT TRANSPORT FARES TRUSTS UNEARNED INCOME UNEMPLOYED UNFURNISHED ACCOMMO... UNWAGED WORKERS WAGES WEALTH WILLS WINNINGS WORKPLACE property and invest...

Credit bureaus and rating agencies in the US have experienced notable growth in recent years due to heightened demand for information. The reliance on data analytics has driven increased interest in these services, which provide vital information on creditworthiness for both individuals and businesses. This has been particularly significant as businesses and individuals seek to make well-informed financial decisions. Despite challenges related to the pandemic, inflation and high interest rates, the industry has thrived and profit has soared, indicating its resilience and the critical nature of the services it offers in a data-driven economy. While long-term demand for information has buoyed the industry, providers’ trajectory has been influenced by broader economic conditions, notably equity market fluctuations. The industry weathered initial pandemic-related disruptions, which precipitated a sharp fall in stock prices and corporate profit. Nonetheless, rapid fiscal and monetary responses bolstered investor confidence and led to a robust rebound in equity markets, contributing to massive revenue growth in 2020 and 2021. Soaring interest rates in 2022 and 2023 boosted recessionary fears among investors, hindering demand for equities, reducing stock prices and thus contributing to a major drop in revenue in 2022. These effects have percolated into the real economy as consumer and business borrowing has slowed, constraining aggregate household debt and corporate debt. These effects have negatively impacted the industry in 2023 and 2024, though a rebound in the stock market has prevented a major collapse in revenue. Overall, revenue for credit bureaus and rating agencies in the US is anticipated to soar at a CAGR of 4.3% over the past five years, reaching $16.4 billion in 2024. This includes a 1.3% drop in revenue in that year. Looking ahead, credit bureaus and rating agencies will face a more tempered growth trajectory over the next five years. The broad adoption of online services and data analytics has led to market saturation, reducing opportunities for exponential revenue growth. Nonetheless, stable economic growth and business formation should sustain a steady demand for credit reporting and rating services. The predicted slower growth in equity prices will moderate financial institutions' borrowing capacity, which will also contribute to the slowdown in revenue growth. Overall, revenue for credit bureaus and rating agencies in the United States is forecast to inch upward at a CAGR of 1.1% over the next five years, reaching $17.4 billion in 2029.

Debt financing (mortgage, line of credit, term loan, credit card) terms and conditions, average interest rates and average length of term for small and medium enterprises in 2020 by region, CMA level, North American Industry Classification System (NAICS), demographics, age of business, employment size, rate of growth, etc.