U.S. Government Workshttps://www.usa.gov/government-works
License information was derived automatically
Aggregated and anonymized purchase data from consumer credit and debit card spending. Spending is reported based on the ZIP code where the cardholder lives, not the ZIP code where transactions occurred. Data from Affinity Solutions, compiled by Opportunity Insights.
Update Frequency: Weekly Date Range: January 13th until the most recent date available.
Data Frequency: Data is daily until the final two weeks of the series, and the daily data is presented as a 7 day lookback moving average. For the final two weeks of the series, the data is weekly and presented as weekly data points.
Index Period: January 4th - January 31st
Indexing Type: Seasonally adjusted change since January 2020. Data is indexed in 2019 and 2020 as the change relative to the January index period. We then seasonally adjust by dividing year-over-year, which represents the difference between the change since January observed in 2020 compared to the change since January observed since 2019. We account for differences in the dates of federal holidays between 2019 and 2020 by shifting the 2019 reference data to align the holidays before performing the year-over-year division.
In February 2024, consumer card spending on retail categories saw significant decreases in a number of categories. Compared to the same month in 2023, while spending on general retail items saw growth at *** percent; spending in discount stores declined. Overall, retail spending increased by *** percent in February 2024.
Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
License information was derived automatically
Analysis of Visa card spending data, including domestic, international, and combined percentage of face-to-face spending on tourism-related industries.
Predict revenue surprises, track market share, and compare performance metrics for thousands of companies based on anonymized debit and credit card data of millions of US households. Orion data is sourced from a variety of US financial institutions with broad geographic and demographic representation, combined to create one of the most comprehensive and accurate views of the consumer economy. AI-powered earnings predictions available for over 450 tickers on this dataset through EarnestAI Reported Metric Predictions.
Consumers' card spending in the United Kingdom (UK) slowed down considerably following **********, due to the impact of the coronavirus (Covid-19) pandemic. According to the most recently reported data, consumer card spending in the UK picked up pace again, growing by **** percent as of ********** compared to the pre-pandemic levels in the same month of 2019. In this statistic, in order to give a more accurate comparison, data from ********** onwards were provided as comparisons to 2019.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Consumer Credit in the United States decreased to 5.10 USD Billion in May from 16.87 USD Billion in April of 2025. This dataset provides the latest reported value for - United States Consumer Credit Change - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.
https://www.aiceltech.com/termshttps://www.aiceltech.com/terms
Credit card is the most widely used form of payments in Korea – in 2019, personal card transaction volume appeared to be 76% of Korea’s private consumption expenditure. Timeliness and frequency of the card transaction data allow investors or corporates to observe any trend in household consumption and draw useful insights for their business. KED Aicel consumer transaction headline figure showed a correlation of 90%+ to the official total consumer spending data during 2015 through 2019.
https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain
Graph and download economic data for Sources of Revenue: Credit Card Income from Consumers for Credit Intermediation and Related Activities, All Establishments, Employer Firms (REVCICEF522ALLEST) from 2013 to 2022 about finance companies, intermediate, employer firms, consumer credit, credit cards, accounting, companies, revenue, finance, establishments, financial, loans, consumer, services, income, and USA.
Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
License information was derived automatically
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.
Envestnet®| Yodlee®'s Spending Data (Aggregate/Row) Panels consist of de-identified, near-real time (T+1) USA credit/debit/ACH transaction level data – offering a wide view of the consumer activity ecosystem. The underlying data is sourced from end users leveraging the aggregation portion of the Envestnet®| Yodlee®'s financial technology platform.
Envestnet | Yodlee Consumer Panels (Aggregate/Row) include data relating to millions of transactions, including ticket size and merchant location. The dataset includes de-identified credit/debit card and bank transactions (such as a payroll deposit, account transfer, or mortgage payment). Our coverage offers insights into areas such as consumer, TMT, energy, REITs, internet, utilities, ecommerce, MBS, CMBS, equities, credit, commodities, FX, and corporate activity. We apply rigorous data science practices to deliver key KPIs daily that are focused, relevant, and ready to put into production.
We offer free trials. Our team is available to provide support for loading, validation, sample scripts, or other services you may need to generate insights from our data.
Investors, corporate researchers, and corporates can use our data to answer some key business questions such as: - How much are consumers spending with specific merchants/brands and how is that changing over time? - Is the share of consumer spend at a specific merchant increasing or decreasing? - How are consumers reacting to new products or services launched by merchants? - For loyal customers, how is the share of spend changing over time? - What is the company’s market share in a region for similar customers? - Is the company’s loyal user base increasing or decreasing? - Is the lifetime customer value increasing or decreasing?
Additional Use Cases: - Use spending data to analyze sales/revenue broadly (sector-wide) or granular (company-specific). Historically, our tracked consumer spend has correlated above 85% with company-reported data from thousands of firms. Users can sort and filter by many metrics and KPIs, such as sales and transaction growth rates and online or offline transactions, as well as view customer behavior within a geographic market at a state or city level. - Reveal cohort consumer behavior to decipher long-term behavioral consumer spending shifts. Measure market share, wallet share, loyalty, consumer lifetime value, retention, demographics, and more.) - Study the effects of inflation rates via such metrics as increased total spend, ticket size, and number of transactions. - Seek out alpha-generating signals or manage your business strategically with essential, aggregated transaction and spending data analytics.
Use Cases Categories (Our data provides an innumerable amount of use cases, and we look forward to working with new ones): 1. Market Research: Company Analysis, Company Valuation, Competitive Intelligence, Competitor Analysis, Competitor Analytics, Competitor Insights, Customer Data Enrichment, Customer Data Insights, Customer Data Intelligence, Demand Forecasting, Ecommerce Intelligence, Employee Pay Strategy, Employment Analytics, Job Income Analysis, Job Market Pricing, Marketing, Marketing Data Enrichment, Marketing Intelligence, Marketing Strategy, Payment History Analytics, Price Analysis, Pricing Analytics, Retail, Retail Analytics, Retail Intelligence, Retail POS Data Analysis, and Salary Benchmarking
Investment Research: Financial Services, Hedge Funds, Investing, Mergers & Acquisitions (M&A), Stock Picking, Venture Capital (VC)
Consumer Analysis: Consumer Data Enrichment, Consumer Intelligence
Market Data: AnalyticsB2C Data Enrichment, Bank Data Enrichment, Behavioral Analytics, Benchmarking, Customer Insights, Customer Intelligence, Data Enhancement, Data Enrichment, Data Intelligence, Data Modeling, Ecommerce Analysis, Ecommerce Data Enrichment, Economic Analysis, Financial Data Enrichment, Financial Intelligence, Local Economic Forecasting, Location-based Analytics, Market Analysis, Market Analytics, Market Intelligence, Market Potential Analysis, Market Research, Market Share Analysis, Sales, Sales Data Enrichment, Sales Enablement, Sales Insights, Sales Intelligence, Spending Analytics, Stock Market Predictions, and Trend Analysis
See earnings predictions for hundreds of public companies, powered by Earnest AI solutions suite. Predict revenue surprises, track market share, and compare performance metrics for thousands of companies based on the anonymized aggregate credit and debit data of millions of US accounts. Vela data is sourced from a variety of US financial institutions with broad geographic and demographic representation, combined to create one of the most comprehensive and accurate views of the consumer economy. AI-powered earnings predictions available for over 450 tickers on this dataset through EarnestAI Reported Metric Predictions.
https://dataintelo.com/privacy-and-policyhttps://dataintelo.com/privacy-and-policy
The global credit cards market size was valued at approximately USD 3.2 trillion in 2023 and is projected to reach USD 5.4 trillion by 2032, growing at a CAGR of 6.2% during the forecast period. This impressive growth is driven by a combination of factors including increased consumer spending, advances in digital payment technologies, and the globalization of financial services. The proliferation of e-commerce and the shift towards cashless economies have further fueled the demand for credit cards as a preferred mode of payment worldwide. The ease of transaction, enhanced security features, and attractive rewards programs are also playing a pivotal role in the expansion of the credit cards market.
One of the primary growth factors in the credit cards market is the rapid digitization of financial services. As consumers increasingly favor online shopping and digital payment methods, credit cards have become essential tools for facilitating these transactions. Financial institutions and card issuers are continuously enhancing their digital platforms to cater to the tech-savvy populace, which demands seamless, quick, and secure payment solutions. The adoption of technologies like tokenization and biometric authentication has further strengthened the security of credit card transactions, instilling greater confidence among consumers. Additionally, the growing penetration of smartphones and internet connectivity across emerging markets is anticipated to boost credit card usage significantly.
The evolving consumer lifestyle and spending habits are also key contributors to the market's expansion. Credit cards offer unparalleled convenience and purchasing power, enabling consumers to meet their immediate needs and desires without the constraint of immediate cash flow. Beyond mere financial flexibility, credit cards are increasingly being integrated with rewards programs, cash-back offers, travel perks, and various other incentives that appeal to different consumer segments. This strategic marketing by banks and card issuers is not only attracting new users but also encouraging existing cardholders to increase usage, thereby contributing to market growth.
Another factor driving the credit cards market is the competitive landscape among card issuers and networks. The presence of a wide array of products catering to different consumer needs—ranging from standard cards for everyday purchases to premium cards offering luxury benefits—ensures broad market appeal. This competitive environment is fostering innovation as issuers continuously strive to differentiate their offerings through enhanced features and services. Additionally, partnerships between card issuers and retailers, airlines, and hospitality businesses are creating co-branded cards that further enhance customer value, thus driving market adoption.
Regionally, North America holds the largest share in the credit cards market due to its mature financial infrastructure and high consumer spending capacity. However, the Asia Pacific region is expected to witness the fastest growth, propelled by rapid urbanization, a burgeoning middle-class population, and increasing adoption of digital payment methods. In countries like China and India, government initiatives promoting cashless transactions are creating a fertile ground for credit card penetration. Europe, with its sophisticated banking systems and consumer base, continues to display steady growth, while Latin America and the Middle East & Africa regions are gradually catching up as financial inclusion efforts intensify.
In the credit cards market, different card types serve varied consumer needs and preferences, each contributing uniquely to the market dynamics. Standard cards, typically offering basic credit functions without additional perks, cater primarily to the mass market. These cards remain popular due to their accessibility and ease of use, often being the introductory product for new credit card users. Standard cards serve as a gateway for consumers to build their credit history and gain familiarity with credit products. As such, they represent a significant portion of the market, particularly in regions where credit card adoption is still in its nascent stages.
Premium cards, on the other hand, are designed for high-income individuals seeking exclusive benefits and services. These cards often come with higher credit limits and are loaded with features such as travel insurance, concierge services, airport lounge access, and significant reward points. The market for premium cards is expanding as affluen
Envestnet®| Yodlee®'s Credit Card Data (Aggregate/Row) Panels consist of de-identified, near-real time (T+1) USA credit/debit/ACH transaction level data – offering a wide view of the consumer activity ecosystem. The underlying data is sourced from end users leveraging the aggregation portion of the Envestnet®| Yodlee®'s financial technology platform.
Envestnet | Yodlee Consumer Panels (Aggregate/Row) include data relating to millions of transactions, including ticket size and merchant location. The dataset includes de-identified credit/debit card and bank transactions (such as a payroll deposit, account transfer, or mortgage payment). Our coverage offers insights into areas such as consumer, TMT, energy, REITs, internet, utilities, ecommerce, MBS, CMBS, equities, credit, commodities, FX, and corporate activity. We apply rigorous data science practices to deliver key KPIs daily that are focused, relevant, and ready to put into production.
We offer free trials. Our team is available to provide support for loading, validation, sample scripts, or other services you may need to generate insights from our data.
Investors, corporate researchers, and corporates can use our data to answer some key business questions such as: - How much are consumers spending with specific merchants/brands and how is that changing over time? - Is the share of consumer spend at a specific merchant increasing or decreasing? - How are consumers reacting to new products or services launched by merchants? - For loyal customers, how is the share of spend changing over time? - What is the company’s market share in a region for similar customers? - Is the company’s loyal user base increasing or decreasing? - Is the lifetime customer value increasing or decreasing?
Additional Use Cases: - Use spending data to analyze sales/revenue broadly (sector-wide) or granular (company-specific). Historically, our tracked consumer spend has correlated above 85% with company-reported data from thousands of firms. Users can sort and filter by many metrics and KPIs, such as sales and transaction growth rates and online or offline transactions, as well as view customer behavior within a geographic market at a state or city level. - Reveal cohort consumer behavior to decipher long-term behavioral consumer spending shifts. Measure market share, wallet share, loyalty, consumer lifetime value, retention, demographics, and more.) - Study the effects of inflation rates via such metrics as increased total spend, ticket size, and number of transactions. - Seek out alpha-generating signals or manage your business strategically with essential, aggregated transaction and spending data analytics.
Use Cases Categories (Our data provides an innumerable amount of use cases, and we look forward to working with new ones): 1. Market Research: Company Analysis, Company Valuation, Competitive Intelligence, Competitor Analysis, Competitor Analytics, Competitor Insights, Customer Data Enrichment, Customer Data Insights, Customer Data Intelligence, Demand Forecasting, Ecommerce Intelligence, Employee Pay Strategy, Employment Analytics, Job Income Analysis, Job Market Pricing, Marketing, Marketing Data Enrichment, Marketing Intelligence, Marketing Strategy, Payment History Analytics, Price Analysis, Pricing Analytics, Retail, Retail Analytics, Retail Intelligence, Retail POS Data Analysis, and Salary Benchmarking
Investment Research: Financial Services, Hedge Funds, Investing, Mergers & Acquisitions (M&A), Stock Picking, Venture Capital (VC)
Consumer Analysis: Consumer Data Enrichment, Consumer Intelligence
Market Data: AnalyticsB2C Data Enrichment, Bank Data Enrichment, Behavioral Analytics, Benchmarking, Customer Insights, Customer Intelligence, Data Enhancement, Data Enrichment, Data Intelligence, Data Modeling, Ecommerce Analysis, Ecommerce Data Enrichment, Economic Analysis, Financial Data Enrichment, Financial Intelligence, Local Economic Forecasting, Location-based Analytics, Market Analysis, Market Analytics, Market Intelligence, Market Potential Analysis, Market Research, Market Share Analysis, Sales, Sales Data Enrichment, Sales Enablement, Sales Insights, Sales Intelligence, Spending Analytics, Stock Market Predictions, and Trend Analysis
https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain
Graph and download economic data for Consumer Loans: Credit Cards and Other Revolving Plans, Large Domestically Chartered Commercial Banks (CCLLCBW027NBOG) from 2000-06-28 to 2025-07-23 about revolving, credit cards, large, domestic, loans, consumer, banks, depository institutions, and USA.
Credit Card Payments Market Size 2025-2029
The credit card payments market size is forecast to increase by USD 181.9 billion, at a CAGR of 8.7% between 2024 and 2029.
The market is experiencing significant growth, driven by the increasing prevalence of online transactions. The digital shift in consumer behavior, fueled by the convenience and accessibility of e-commerce platforms, is leading to a surge in credit card payments. Another key trend shaping the market is the adoption of mobile biometrics for payment processing. This advanced technology offers enhanced security and ease of use, making it an attractive option for both consumers and merchants. However, the market also faces challenges. In developing economies, a lack of awareness and infrastructure for online payments presents a significant obstacle. Bridging the digital divide and educating consumers about the benefits and security of online transactions will be crucial for market expansion in these regions. Effective strategies, such as partnerships with local financial institutions and targeted marketing campaigns, can help overcome this challenge and unlock new opportunities for growth.
What will be the Size of the Credit Card Payments Market during the forecast period?
Explore in-depth regional segment analysis with market size data - historical 2019-2023 and forecasts 2025-2029 - in the full report.
Request Free SampleThe market continues to evolve, driven by advancements in technology and shifting consumer preferences. Payment optimization through EMV chip technology and payment authorization systems enhances security and streamlines transactions. Cross-border payments and chargeback prevention are crucial for businesses expanding globally. Ecommerce payment solutions, BNPL solutions, and mobile payments cater to the digital age, offering flexibility and convenience. Payment experience is paramount, with user interface design and alternative payment methods enhancing customer satisfaction. Merchant account services and payment gateway integration enable seamless transaction processing. Payment analytics and loyalty programs help businesses understand customer behavior and boost retention. Interchange fees, chargeback management, and dispute resolution are essential components of credit card processing.
Data encryption and fraud detection ensure payment security. Multi-currency support and digital wallets cater to diverse customer needs. Customer support and subscription management are vital for maintaining positive relationships and managing recurring billing. Processing rates, settlement cycles, and PCI compliance are key considerations for businesses seeking efficient and cost-effective payment solutions. The ongoing integration of these elements shapes the dynamic and evolving credit card payments landscape.
How is this Credit Card Payments Industry segmented?
The credit card payments industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD billion' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments. End-userConsumer or individualCommercialProduct TypeGeneral purpose credit cardsSpecialty credit cardsOthersApplicationFood and groceriesHealth and pharmacyRestaurants and barsConsumer electronicsOthersGeographyNorth AmericaUSCanadaEuropeGermanyUKAPACChinaIndiaJapanSouth KoreaSouth AmericaArgentinaBrazilRest of World (ROW).
By End-user Insights
The consumer or individual segment is estimated to witness significant growth during the forecast period.The market is a dynamic and evolving landscape that caters to businesses and consumers alike. Recurring billing enables merchants to automatically charge customers for goods or services on a regular basis, streamlining the payment process for both parties. EMV chip technology enhances payment security, reducing the risk of fraud. Payment optimization techniques help businesses minimize transaction costs and improve authorization rates. Cross-border payments facilitate international business, while chargeback prevention measures protect merchants from revenue loss due to disputed transactions. Ecommerce payment solutions provide convenience for consumers and merchants, with payment gateway integration ensuring seamless transactions. Rewards programs and buy now, pay later (BNPL) solutions incentivize consumer spending. Mobile payments and digital wallets offer flexibility and convenience. Merchants can accept various payment methods, including cryptocurrencies, and benefit from payment analytics and conversion rate optimization. Payment volume continues to grow, necessitating robust fraud detection systems and multi-currency support. Customer support is crucial for resolving disputes and addressing payment issues. Alternative payment methods cater to diverse consumer preferences. The payment experience is key
https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain
Graph and download economic data for Large Bank Consumer Credit Card Balances: Total Commitments (RCCCBCOMTOT) from Q3 2012 to Q4 2024 about commitments, FR Y-14M, consumer credit, credit cards, large, balance, loans, consumer, banks, depository institutions, and USA.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
United States Retail Sales Nowcast: sa: YoY: Contribution: Payment System: Consumer Spending: Credit Card Transactions: Health & Personal Care: Median data was reported at 2.228 % in 06 May 2024. This records a decrease from the previous number of 2.253 % for 29 Apr 2024. United States Retail Sales Nowcast: sa: YoY: Contribution: Payment System: Consumer Spending: Credit Card Transactions: Health & Personal Care: Median data is updated weekly, averaging 0.012 % from Nov 2020 (Median) to 06 May 2024, with 181 observations. The data reached an all-time high of 3.429 % in 09 Jan 2023 and a record low of 0.000 % in 12 Feb 2024. United States Retail Sales Nowcast: sa: YoY: Contribution: Payment System: Consumer Spending: Credit Card Transactions: Health & Personal Care: Median data remains active status in CEIC and is reported by CEIC Data. The data is categorized under Global Database’s United States – Table US.CEIC.NC: CEIC Nowcast: Retail Sales.
More than **** of consumers in the United States pointed to one clear reason in 2024 why their credit cards had maxed out that year. A survey held by a personal finance firm in October 2024 named inflation as the most likely reason why consumers had reached their credit card spending limit, ahead of emergency expenses. The total credit card debt in the United States was over *** trillion U.S. dollars - up ** billion U.S. dollars between Q2 2024 and Q3 2024. The source adds that people who maxed out their cards were likely to fall into credit card delinquency.
Predict revenue surprises, track market share, and compare performance metrics for thousands of companies based on the anonymized aggregate credit and debit data of millions of US accounts. Vela data is sourced from a variety of US financial institutions with broad geographic and demographic representation, combined to create one of the most comprehensive and accurate views of the consumer economy.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
United States Retail Sales Nowcast: sa: YoY: Contribution: Payment System: Consumer Spending: Credit Card Transactions: Miscellaneous Store Retailers: Median data was reported at 0.045 % in 06 May 2024. This records an increase from the previous number of 0.021 % for 29 Apr 2024. United States Retail Sales Nowcast: sa: YoY: Contribution: Payment System: Consumer Spending: Credit Card Transactions: Miscellaneous Store Retailers: Median data is updated weekly, averaging 0.003 % from Nov 2020 (Median) to 06 May 2024, with 181 observations. The data reached an all-time high of 1.902 % in 28 Nov 2022 and a record low of 0.000 % in 08 Jan 2024. United States Retail Sales Nowcast: sa: YoY: Contribution: Payment System: Consumer Spending: Credit Card Transactions: Miscellaneous Store Retailers: Median data remains active status in CEIC and is reported by CEIC Data. The data is categorized under Global Database’s United States – Table US.CEIC.NC: CEIC Nowcast: Retail Sales.
U.S. Government Workshttps://www.usa.gov/government-works
License information was derived automatically
Aggregated and anonymized purchase data from consumer credit and debit card spending. Spending is reported based on the ZIP code where the cardholder lives, not the ZIP code where transactions occurred. Data from Affinity Solutions, compiled by Opportunity Insights.
Update Frequency: Weekly Date Range: January 13th until the most recent date available.
Data Frequency: Data is daily until the final two weeks of the series, and the daily data is presented as a 7 day lookback moving average. For the final two weeks of the series, the data is weekly and presented as weekly data points.
Index Period: January 4th - January 31st
Indexing Type: Seasonally adjusted change since January 2020. Data is indexed in 2019 and 2020 as the change relative to the January index period. We then seasonally adjust by dividing year-over-year, which represents the difference between the change since January observed in 2020 compared to the change since January observed since 2019. We account for differences in the dates of federal holidays between 2019 and 2020 by shifting the 2019 reference data to align the holidays before performing the year-over-year division.