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AI In Fraud Management Market Revenue Growth Supported By A CAGR Of 37.27% Through 2030
The AI in fraud management market size has seen rapid expansion over recent years. It is projected to increase from $15.53 billion in 2025 to $18.48 billion in 2026, exhibiting a compound annual growth rate (CAGR) of 19.1%. This historical growth can be attributed to factors such as manual fraud detection methods, a rise in financial fraud incidents, an increase in digital transactions, the expansion of banking and financial services, and the adoption of basic analytics tools.
The market for AI in fraud management is anticipated to experience significant expansion in the coming years. This market is projected to reach $37.27 billion by 2030, demonstrating a compound annual growth rate (CAGR) of 19.2%. Factors contributing to this growth during the forecast period include progress in machine learning algorithms, the incorporation of AI into payment platforms, increasing investments in fraud prevention, the proliferation of cloud-based fraud detection systems, and stricter regulatory compliance mandates. Key trends expected during this period encompass real-time fraud detection, predictive risk scoring, automated transaction monitoring, AI-powered identity verification, and managed fraud detection services.
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AI In Fraud Management Market Industry Drivers: What Is Driving Revenue Growth?
The increasing prevalence of digital payments and international transactions is set to fuel the expansion of AI in the fraud management market. These payments involve electronic monetary exchanges via mobile, computer, or other linked platforms, enabling secure, cashless, and instant transfers for individuals and businesses. Their appeal is on the rise due to enhanced convenience, greater accessibility, and the proliferation of fintech platforms and global e-commerce. AI in the fraud management market facilitates this growth by employing smart algorithms and predictive analytics to detect, oversee, and thwart fraudulent actions within extensive financial systems, thus safeguarding transaction integrity and user confidence. A notable illustration of this is from September 2025, when JPMorgan Chase & Co., a US-based investment banking company, reported handling over $10 trillion daily across 60 million transactions in more than 200 countries and territories and 120 currencies, maintaining a 99.5% straight-through processing (STP) rate. Consequently, the growing adoption of digital payments and cross-border transactions is a primary catalyst for the growth of AI in the fraud management market.
AI In Fraud Management Market Segment Analysis Highlighting Growth Areas
The AI in fraud management market covered in this report is segmented –
1) By Solution: AI-Powered Fraud Prevention Software, Services
2) By Enterprise Size: Small And Medium Enterprises (SMEs), Large Enterprises
3) By Application: Identity Theft Protection, Payment Fraud Prevention, Anti-Money Laundering, Other Applications
4) By Industry: Banking, Financial Services And Insurance, IT And Telecom, Healthcare, Government, Education, Retail And Consumer packaged goods (CPG), Media And Entertainment, Other Industries
Subsegments:
1) By AI-Powered Fraud Prevention Software: Real-Time Transaction Monitoring, Fraud Detection And Analysis Tools, Risk Scoring And Assessment Solutions
2) By Services: Consulting Services, Implementation Services, Training And Support Services, Managed Fraud Detection Services
AI In Fraud Management Market Industry Trends Shaping Future Revenue Growth
Leading companies in the AI fraud management market are concentrating on developing advanced technologies, such as generative AI-facilitated fraud solutions, to strengthen real-time defenses against increasingly complex financial and identity-based fraud. Generative AI-facilitated fraud solutions utilize generative artificial intelligence (AI) models to identify and counteract fraudulent behavior by simulating potential attack patterns, pinpointing anomalies, and adapting promptly to emerging threats. For instance, in October 2023, DataVisor, a US-based fraud and risk detection software company, unveiled AI Co-Pilot, a generative AI-powered fraud management solution designed to automate fraud detection, reduce false positives, and minimize user friction. This system leverages generative AI to assist analysts by automatically generating and refining detection rules, producing and debugging feature scripts, and providing descriptive insights into detected anomalies. This innovation empowers financial institutions and digital platforms to enhance fraud prevention strategies, maintain seamless customer experiences, and improve overall operational resilience against evolving cyber threats.
AI In Fraud Management Market Leading Companies: Who Holds Significant Market Presence?
Major companies operating in the AI in fraud management market are Trusteer; Hewlett Packard Enterprise; BAE Systems plc; Capgemini SE; Cognizant Technology Solutions India Private Limited; SAS Institute Inc.; Splunk Inc.; Temenos AG; Shift Technology SAS; Riskified Ltd.; NICE Actimize Inc.; Jumio Corp.; Onfido Ltd.; Subex Limited; BehavioSec Inc.; Arxan Technologies Inc.; Socure Inc.; ACTICO GmbH; BioConnect Inc.; Matellio Inc.; MaxMind Inc.; Zest AI Inc.; Chargeback.com Inc.; Brighterion Inc.
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AI In Fraud Management Market Regional Analysis And Leading Geography
North America was the largest region in the AI in fraud management market in 2025. The regions covered in the AI in fraud management 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.