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Study: Deepfake Fraud Surges – And Only 7% Of Organizations Are Firmly Ready

Reeba Asghar by Reeba Asghar
April 24, 2026
in Analysis
Woman in a cafe having problems with her credit card ++++ NOTE for the inspector: Credit card is fake and is made especially for the photo session++++

Global survey finds organizations under-equipped as AI-charged threats escalate across industries

As fraudsters sprint ahead with AI, organizations report they are struggling to keep pace. That’s the sobering verdict delivered in the latest fraud research by the Association of Certified Fraud Examiners (ACFE) and data and AI leader SAS: Only 7% of anti-fraud professionals say their organizations are more than moderately prepared to detect or prevent AI-fueled fraud – even as criminals hijack inexpensive and plentiful AI tools to drive social engineering schemes, digital forgery and consumer scams to record highs.

The 2026 Anti-Fraud Technology Benchmarking Report – the fourth installment in a research series debuted by the ACFE and SAS in 2019 – is based on a survey of 713 fraud fighters across eight regions worldwide.

“The data paints a worrisome picture: fraud is evolving faster than most organizations can defend against it,” said John Gill, J.D., CFE, President of the ACFE. “AI-powered threats aren’t on the horizon – they’re already here, and they’re accelerating quickly. The profession has made real strides in adopting AI, but this report is a wake-up call. Organizations that don’t strengthen their defenses against AI-charged fraud risk as others do will become bigger targets.”

As fraud risk rises globally, the UAE and Saudi Arabia are uniquely positioned to lead the next generation of fraud prevention. Strong regulatory alignment, government-led digital transformation, and modern financial infrastructure give both markets a structural advantage. With central banks CBUAE and SAMA acting as ecosystem orchestrators, the region has a rare opportunity to leapfrog legacy approaches and move directly to supporting a secure, seamless, and future-ready financial ecosystem.

Abed Hamandi, Senior Director, EMEA Consulting, Fraud and Security Intelligence Practice, SAS

“Few regions combine high growth with such strong regulatory leadership,” said Abed Hamandi, Senior Director, EMEA Consulting, Fraud and Security Intelligence Practice, SAS. “The UAE and Saudi Arabia are not constrained by legacy in the same way as many mature markets. By embracing real-time, AI-driven, and identity-centric fraud prevention, they can stop fraud before it happens, while delivering the low-friction customer experiences that modern digital economies demand.”

Industries at a crossroads – and in the crosshairs

Respondents represent more than a dozen industries, most prominently government and public sector (26%) and banking and financial services (23%), alongside meaningful participation from professional services, manufacturing, insurance, technology, education, energy and health care. Survey insights reveal that:

  • Fraudsters are winning the AI race. Every AI-powered fraud modality examined has risen over the past two years, according to the anti-fraud professionals surveyed. Deepfake social engineering saw the sharpest surge, with 77% of respondents reporting a slight-to-significant increase – followed closely by consumer fraud/scams (75%), generative AI document fraud/forgery (75%) and deepfake digital injection (72%). Looking ahead, 55% expect deepfake social engineering and GenAI document fraud/forgery to increase significantly over the next 24 months.
  • AI and machine learning (ML) adoption are accelerating but remain far from ideal. One-quarter of organizations (exactly 25%) now use AI/ML in their anti-fraud programs, according to respondents, up from 18% in 2024. Another 28% expect to adopt it by 2028. For organizations still on the sidelines, the window to build AI competency before competitors and criminals widen the gap is narrowing fast.
  • Governance lags dangerously behind AI adoption. Nearly nine in 10 (86%) organizations rate accuracy of results as important or very important in adopting GenAI, yet less than one in five (18%) respondents say their organization tests AI models for bias or fairness. Similarly, 82% say explainability is important, but just 6% feel completely confident explaining how their AI/ML models make anti-fraud decisions. For banks, insurers and other regulated entities in particular, deploying AI in this manner risks regulatory consequences and legal liability on top of reputational damage.
  • Budgets are growing – but so are constraints. More than half of respondents (55%) expect their organizations to increase their anti-fraud technology budgets over the next two years. Even so, budgetary and financial restrictions remain the leading barrier to implementation, cited as a major or moderate challenge by 84% of respondents.

Emerging tech: Promise, progress and the cost of waiting

Physical biometrics, agentic and generative AI – and yes, even quantum AI – the technologies transforming the war on fraud are maturing rapidly. But fraudsters’ readiness to exploit them is advancing in parallel, and bad actors have a tremendous advantage.

“Cybercriminals don’t have governance committees, and they don’t wait for budget cycles or regulatory clarity – they just act,” said Stu Bradley, Senior Vice President of Risk, Fraud and Compliance Solutions at SAS. “Every quarter business leaders spend evaluating a technology is another quarter lawbreakers get to weaponize it and find organizations underprepared.”

The question isn’t whether to adopt anti-fraud innovations, but rather, can organizations afford to wait? The study revealed these trends in value-proven, emerging technologies:

  • GenAI is moving from aspiration to application. Although only 16% of respondents indicate their organizations currently use generative AI as an anti-fraud tool, another 58% plan to in the future. Among those already using GenAI, top applications are phishing and scam detection (49%), risk identification/assessment (46%) and report writing (45%).
  • AI agents are hotter still. Nearly one in 10 (8%) of respondents say their organizations use agentic AI for fraud fighting, and nearly one-third (31%) more expect to deploy it by 2028 – the highest near-term adoption expectation of any emerging technology category examined.
  • Physical biometrics leads emerging tech adoption – while many neglect the benefits of automation and the cloud. The use of physical biometrics is now the most widely adopted emerging technology in anti-fraud programs gauged in the study, used by nearly half of organizations (45%) surveyed – up from roughly one-third (34%) in 2022. In contrast, cloud-native fraud detection platforms and automation remain significantly underutilized, used by only 10% and 29% of organizations, respectively.
  • Quantum computing’s impact on the anti-fraud battlefield is closer than most expect. Most respondents (62%) expect quantum computing and quantum AI to materially impact fraud detection and prevention by 2030 – and a surprising 11% say it already is.

Ready or not…

Whatever their level of preparedness, organizations across sectors face the same AI-accelerated fraud threats. The differentiator? Their ability to fight back. Fraud fighters must be equipped with the right data and technology – and also the appropriate speed, scale and governance – to combat modern-day risks. Explore the most prominent AI-accelerated fraud modalities and counter strategies by downloading the ACFE and SAS’ joint 2026 Anti-Fraud Technology Benchmarking Report at SAS.com/fraudreport.

For a hands-on exploration of the survey data – with filters for region, industry, respondent profile and more – investigate the data dashboard at SAS.com/fraudsurvey.

Tags: ACFEAI fraudAI Governanceanti-fraudbanking securitycybercrimecybersecuritydata securitydeepfake fraudDigital Securitydigital transformationenterprise riskfinancial crimefintech riskfraudgenerative AIidentity fraudMachine Learningregulatory complianceSASscam detectionTechnology Trends
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