The market size for credit cards in the United States grew by over *** percent between 2022 and 2023, a continuation of previous years. This according to estimates from on the value of transactions conducted with cards with a credit function. Credit cards are the most popular payment method available in the country for several years in a row, with a market share that slightly increased during the first year of COVID-19. The United States' credit card penetration is forecast to reach more than ** percent come 2025.

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.

The value of credit card purchases made in the UK grew to a record in July 2024, at ***** billion British pounds. It contrasted the low point in April 2020, when monthly credit card spending fell to approximately *** billion British pounds. As of May 2025 the credit card purchases made it to 2**** billion British pounds.

This dataset provides values for CREDIT CARD SPENDING reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

Daily Card Payments by Irish Households. A subset of the monthly Card Payment Statistics. The onset of the Covid-19 pandemic created the need for timely, high-frequency data, such as the Daily Credit and Debit Card Statistics, to better understand the impact of the pandemic on personal expenditure and economic activity. This high-frequency daily Credit and Debit Data captures expenditure of euro-denominated credit and debit cards issued to Irish residents. The dataset consists of total daily debit and credit card spending and ATM withdrawals, while from 1 October 2020, expenditure in a number of key sectors of the economy, and a split of online and in-store spending is also available.

The value of payments made with cards that have a credit function in Austria from 2006 to 2020 increased with some fluctuation during the period observed with a significant decrease in 2020. In 2013, the value of payments amounted to approximately ************ euros, by 2019 this had increased to roughly *********** euros, an increase of *********** euros. In 2020, the value dropped to approximately ************ euros. Credit cards have become increasingly popular over this period, with around **** credit cards per capita in 2019. Originally denominated in euros, the data was converted to U.S. dollars by Statista to allow for cross-country comparisons worldwide.

Credit Card Spending in New Zealand increased to 6938 NZD Million in August from 6889 NZD Million in July of 2025. This dataset provides - New Zealand Credit Card Spending- actual values, historical data, forecast, chart, statistics, economic calendar and news.

Thailand Credit Card: Spending Value: DU: Foreign Issued Card data was reported at 16,825.900 THB mn in May 2018. This records a decrease from the previous number of 18,944.350 THB mn for Apr 2018. Thailand Credit Card: Spending Value: DU: Foreign Issued Card data is updated monthly, averaging 13,265.450 THB mn from Jan 2005 (Median) to May 2018, with 161 observations. The data reached an all-time high of 25,584.880 THB mn in Jan 2018 and a record low of 5,281.500 THB mn in Mar 2005. Thailand Credit Card: Spending Value: DU: Foreign Issued Card data remains active status in CEIC and is reported by Bank of Thailand. The data is categorized under Global Database’s Thailand – Table TH.KA012: Credit Card Statistics.

This dataset provides values for CREDIT CARD SPENDING reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

In 2024, the value of credit card spending in China amounted to **** trillion yuan. Credit card usage buckled under the pressure of increasingly widespread mobile payments. The growth rate of credit card spending had been declining over the past years.

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

1. Investment Research: Financial Services, Hedge Funds, Investing, Mergers & Acquisitions (M&A), Stock Picking, Venture Capital (VC)

2. Consumer Analysis: Consumer Data Enrichment, Consumer Intelligence

3. 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

Thailand Credit Card: Spending Value: Cash Advance: CB: Other Corporations data was reported at 3,476.530 THB mn in Sep 2018. This records a decrease from the previous number of 4,273.420 THB mn for Aug 2018. Thailand Credit Card: Spending Value: Cash Advance: CB: Other Corporations data is updated monthly, averaging 4,689.890 THB mn from Jan 2012 (Median) to Sep 2018, with 81 observations. The data reached an all-time high of 7,239.800 THB mn in Jan 2013 and a record low of 3,278.880 THB mn in Sep 2014. Thailand Credit Card: Spending Value: Cash Advance: CB: Other Corporations data remains active status in CEIC and is reported by Bank of Thailand. The data is categorized under Global Database’s Thailand – Table TH.KA012: Credit Card Statistics.

Thailand Credit Card: Spending Value: Cash Advance: CB: Bank Card data was reported at 0.000 THB mn in Oct 2018. This stayed constant from the previous number of 0.000 THB mn for Sep 2018. Thailand Credit Card: Spending Value: Cash Advance: CB: Bank Card data is updated monthly, averaging 0.000 THB mn from Jan 2012 (Median) to Oct 2018, with 82 observations. Thailand Credit Card: Spending Value: Cash Advance: CB: Bank Card data remains active status in CEIC and is reported by Bank of Thailand. The data is categorized under Global Database’s Thailand – Table TH.KA012: Credit Card Statistics.

Predicting Credit Card Customer Segmentation

Exploring Key Customer Characteristics

By [source]

About this dataset

This dataset contains a wealth of customer information collected from within a consumer credit card portfolio, with the aim of helping analysts predict customer attrition. It includes comprehensive demographic details such as age, gender, marital status and income category, as well as insight into each customer’s relationship with the credit card provider such as the card type, number of months on book and inactive periods. Additionally it holds key data about customers’ spending behavior drawing closer to their churn decision such as total revolving balance, credit limit, average open to buy rate and analyzable metrics like total amount of change from quarter 4 to quarter 1, average utilization ratio and Naive Bayes classifier attrition flag (Card category is combined with contacts count in 12months period alongside dependent count plus education level & months inactive). Faced with this set of useful predicted data points across multiple variables capture up-to-date information that can determine long term account stability or an impending departure therefore offering us an equipped understanding when seeking to manage a portfolio or serve individual customers

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How to use the dataset

This dataset can be used to analyze the key factors that influence customer attrition. Analysts can use this dataset to understand customer demographics, spending patterns, and relationship with the credit card provider to better predict customer attrition.

Research Ideas

• Using the customer demographics, such as gender, marital status, education level and income category to determine which customer demographic is more likely to churn.
• Analyzing the customer’s spending behavior leading up to churning and using this data to better predict the likelihood of a customer of churning in the future.
• Creating a classifier that can predict potential customers who are more susceptible to attrition based on their credit score, credit limit, utilization ratio and other spending behavior metrics over time; this could be used as an early warning system for predicting potential attrition before it happens

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

License: CC0 1.0 Universal (CC0 1.0) - Public Domain Dedication No Copyright - You can copy, modify, distribute and perform the work, even for commercial purposes, all without asking permission. See Other Information.

Columns

File: BankChurners.csv | Column name | Description | |:---------------------------------------------------------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------------------------| | CLIENTNUM | Unique identifier for each customer. (Integer) | | Attrition_Flag | Flag indicating whether or not the customer has churned out. (Boolean) | | Customer_Age | Age of customer. (Integer) | | Gender | Gender of customer. (String) | | Dependent_count | Number of dependents that customer has. (Integer) | | Education_Level ...

This dataset contains details of Wiltshire Council expenditure on corporate credit cards. Data published monthly.

This dataset provides granular credit card transaction records, including customer demographics, card details, merchant information, and transaction metadata. It is ideal for banks and fintechs seeking to analyze spending patterns, segment customers, and model risk, enabling data-driven product design and market research.

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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 to customer retention and a

The global personal credit card market, valued at $1,404,430 million in 2025, is projected to experience robust growth, driven by a compound annual growth rate (CAGR) of 4.3% from 2025 to 2033. This expansion is fueled by several key factors. Increasing disposable incomes, particularly in developing economies, are leading to higher consumer spending and a greater reliance on credit cards for purchases. The proliferation of digital payment platforms and fintech innovations has streamlined the application and usage processes, making credit cards more accessible to a wider population. Furthermore, attractive rewards programs, such as cashback offers and travel points, are incentivizing card adoption and usage. However, the market also faces challenges, including rising interest rates which can increase the cost of borrowing, stricter lending regulations aimed at mitigating credit risk, and the potential for increased competition from alternative payment methods like Buy Now, Pay Later (BNPL) services. The market is highly competitive, with major players like JPMorgan Chase, Citibank, Bank of America, and others vying for market share through innovative product offerings and aggressive marketing strategies. Regional variations in market growth are expected, with developing economies potentially experiencing faster growth rates compared to mature markets. The segmentation of the personal credit card market includes various card types (e.g., rewards cards, secured cards, travel cards) and pricing models (e.g., annual fees, interest rates). This segmentation reflects the diverse needs and preferences of consumers. The competitive landscape is shaped by ongoing mergers and acquisitions, technological advancements, and strategic partnerships between banks and fintech companies. The long-term outlook remains positive, with continued growth anticipated, though the pace might be influenced by macroeconomic factors such as inflation and economic recessionary pressures. The market’s evolution will continue to be defined by technological innovation, regulatory changes, and the ever-shifting preferences of consumers in a dynamic financial landscape.

Mexicans made **** trillion pesos worth of credit card transactions in 2021, a recovery from the decline observed in 2020. The change from 2020 to 2021 was an increase of roughly ** percent in Mexican pesos, although the growth change when estimating this value in U.S. dollars was not as big. Mexico did not feature in a comparison of credit card penetration across 161 countries worldwide in 2021, but before that year it was considered the least likely country in the world where credit cards saw much use.

This dataset contains anonymized credit card transaction records, enriched with behavioral cluster assignments and key transaction attributes such as merchant category, transaction type, and customer demographics. Designed for segmentation and marketing analytics, it enables organizations to identify spending patterns, target customer segments, and optimize marketing strategies.