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Payment Card Skimming Market Size Forecast Points To $6.97 Billion In Revenue By 2030
The payment card skimming market has experienced rapid expansion recently. This market is projected to expand from $3.99 billion in 2025 to reach $4.49 billion by 2026, exhibiting a compound annual growth rate (CAGR) of 12.5%. Historically, this growth has been driven by factors such as an increase in payment fraud incidents, the proliferation of ATM and POS networks, wider adoption of digital payments, mandates for payment security, and the presence of anti-skimming hardware options.
The payment card skimming market is anticipated to experience substantial expansion over the upcoming years. This market is projected to reach $6.97 billion by 2030, exhibiting a compound annual growth rate (CAGR) of 11.6%. This expansion during the forecast period is fueled by several factors, including the increasing uptake of cloud-based fraud prevention tools, the broader application of predictive analytics for detecting fraud, a heightened emphasis on zero-trust security models, the greater incorporation of IoT-enabled security devices, and increased investment in payment security innovation. Key trends expected during this period involve the wider implementation of advanced anti-skimming technologies, the increasing utilization of AI-based fraud detection systems, a growing integration of real-time transaction monitoring, the expansion of secure POS and ATM infrastructure, and an intensified focus on protecting consumer data.
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Payment Card Skimming Market Driver Analysis: Key Factor Supporting Revenue Growth
The rising occurrences of automated teller machine (ATM) fraud are anticipated to drive the expansion of the payment card skimming market in the future. An automated teller machine (ATM) is a specialized digital device that allows individuals to conduct diverse banking operations remotely, without needing a human teller or visiting a physical bank branch. Due to technological progress and the extensive utilization of ATMs for banking activities, ATM fraud has seen a substantial increase. Payment card skimming measures are implemented to guard against fraudulent activities and unauthorized entry, thereby ensuring the secure functioning of automated teller machines (ATMs) and protecting users’ financial data. Such measures encompass PIN validation, data encryption, monitoring, and various physical security components. For example, in April 2025, the European Association for Secure Transactions, a UK-based association that tracks payment terminal crime and ATM fraud, reported that terminal-related fraud attacks in 2024 doubled compared to 2023, escalating from 7,115 incidents to 14,664 incidents. Consequently, the escalating incidents of automated teller machine (ATM) financial fraud are expected to fuel the expansion of the payment card skimming market.
Payment Card Skimming Market Segmentation Framework: Major Segments At A Glance
The payment card skimming market covered in this report is segmented –
1) By Component: Solution, Service
2) By Deployment Mode: On-Premise, Cloud
3) By Organization Size: Large Enterprise, Small And Medium-sized Enterprises
4) By Application: Identity Theft, Payment Fraud, Automated Teller Machine (ATMs), Other Applications
Subsegments:
1) By Software Solutions: Fraud Detection Software, Skimming Prevention Software, Transaction Monitoring Systems, Data Encryption Solutions, Point-Of-Sale (POS) Security Software
2) By Service: Consulting Services, Risk Assessment And Security Audits, Skimming Prevention And Security Strategy Consulting, Training And Awareness Services, Employee Training On Skimming Detection, Consumer Awareness Programs, Maintenance And Support Services, System Maintenance For Anti-Skimming Technologies, Software Updates And Upgrades, Managed Security Services, Real-Time Monitoring Of Payment Card Transactions, Incident Response Services
Latest Payment Card Skimming Market Developments And Emerging Trends
Leading firms within the payment card skimming sector are incorporating artificial intelligence, including generative AI, to improve their detection abilities and strengthen security protocols for card transactions. Generative AI plays a crucial role in preventing skimming by pinpointing patterns and irregularities within transaction data, thereby proactively identifying and reducing fraudulent actions. As an example, in May 2024, Mastercard Inc., a US-based payment card services company, introduced an innovative technology capable of quickly analyzing transaction data from billions of cards and millions of merchants, outperforming prior processing speeds. This particular system leverages Mastercard’s predictive technology, which is based on generative AI, to identify and flag new fraud patterns, consequently doubling the rate at which compromised cards are detected. It also substantially cuts down false positives by up to 200% when detecting fraud on potentially affected cards and speeds up the identification of merchants vulnerable to or already impacted by fraudsters by 300%.
Which Companies Are Shaping The Payment Card Skimming Market?
Major companies operating in the payment card skimming market are Fiserv Inc., NCR Voyix Corporation, Diebold Nixdorf Incorporated, Ingenico Group SA, Verifone Systems Inc., MagTek Inc., ACI Worldwide Inc., Fair Isaac Corporation, IDEMIA Identity & Security, Bluefin Payment Systems LLC, Fortinet Inc., Check Point Software Technologies Ltd., Trend Micro Incorporated, McAfee LLC, CyberArk Software Ltd., Trustwave Holdings Inc., Axis Communications AB, Zebra Technologies Corporation, SAI360 Inc., Matrix IFS Ltd.
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Payment Card Skimming Market Regional Distribution: Where Is Revenue Concentrated?
North America was the largest region in the payment card skimming market in 2025. The regions covered in the payment card skimming market report are Asia-Pacific, South East Asia, Western Europe, Eastern Europe, North America, South America, Middle East, Africa.
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Wasay has over a decade of experience in market research, data modelling, and analytics, with prior experience at GlobalData and Decision Tree Consulting Services. At The Business Research Company , he leads research operations across syndicated studies, customized consulting engagements, and the Global Market Model platform. His professional experience includes supporting organizations such as Boston Consulting Group, KPMG, and Ernst & Young. Wasay holds a degree in Electronics and Communications Engineering, postgraduate management qualifications from International Management Institute Belgium and Indian School of Business and Entrepreneurship, and completed the Integrated Program in Business Analytics from Indian Institute of Management Indore.
