[New] Generative AI could push U.S. fraud losses to $40 billion by 2027, up from $12.3 billion in 2023.
TorchLight
[New] Generative AI fraud in the U.S. is expected to hit $40 billion by 2027, up from $12.3 billion in 2023, a compound annual growth rate of 32%.
Bright Defense
[New] Taken together, the enforcement signals for 2026 are clear: Regulators will continue to pursue familiar fraud and abuse priorities, but with better data and more coordination across federal and state agencies.
Medical Economics
[New] By 2026, the industry benchmark will transition from periodic reviews to real-time fraud detection and fully automated Suspicious Activity Report filing.
Gemba
[New] Feedzai is an enterprise fraud platform, adopted by global banks and payment processors for real-time risk scoring and financial crime management.
DataVisor, Inc.
[New] Agility remains one of the biggest challenges: most organizations still struggle to rapidly update fraud models, risk rules, or scoring logic when new attack patterns emerge.
DataVisor, Inc.
[New] Nearly one in 10 (8%) of respondents say their organizations use agentic AI for fraud fighting, and nearly one-third more expect to deploy it by 2028 - the highest near-term adoption expectation of any emerging technology category examined.
Security MEA
[New] More than half of respondents expect their organizations to increase their anti-fraud technology budgets over the next two years.
Security MEA
The parallel risk: generative AI-enabled fraud losses are projected at $40 billion in the US by 2027 - nearly 3.3×2023's $12.3 billion.
BusinessStats
Finance and banking fraud trends for 2026 are expected to include growing use of deepfakes and AI-generated documents that challenge the effectiveness of traditional identity verification systems.
Sumsub
Sectors where user identity is crucial are particularly at risk, with the top-five industries most affected by identity fraud in 2025 and 2026 being dating, online media, financial services, crypto, and professional services.
Sumsub
More than two-thirds of respondents expect more fraud attacks in 2026.
BiometricUpdate.com
Deepfake threats are accelerating faster than current defences, with fraud attempts rising 2137% in three years, projected U.S. losses reaching $40 billion by 2027, and human detection accuracy falling to 24.5% for advanced fakes.
Bright Defense
By 2026, 30% of enterprises will no longer rely solely on identity verification to prevent fraud.
Bright Defense
AI-powered fraud is now 4.5 times more profitable than traditional schemes, Interpol has warned.
AML Intelligence
Impersonation fraud now accounts for more than 85% of fraudulent attempts in some datasets, and AI-facilitated fraud losses in the US are projected to reach $40bn by 2027.
RegTech Analyst
Financial losses to businesses due to deepfakes and AI fraud in the U.S. could reach $40 billion by 2027, up from $12.3 billion in 2023.
Information Week
By 2026, AI-driven verification will filter out 99.8% of synthetic identity fraud.
Gemba
Deepfake-driven social engineering already works at a professional level, fraud teams are almost entirely unprepared for it, and by 2026 every serious investigator who has not built deepfake-aware workflows will be systematically outmaneuvered.
CaraComp
Federal prosecutors have already uncovered that the situation in Minnesota could surpass $9 billion in fraud with dozens of people already charged.
cloud
Last updated: 05 May 2026
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