SEON, the command centre for immediate Fraud Prevention and AML Compliance, has unveiled AI Reality Check: 2026 Fraud & AML Leaders Report, the second iteration of its sector research, derived from a worldwide survey of 1,010 leaders in fraud, risk, and compliance spanning payments, fintech, financial services, retail, eCommerce, and gaming.

The figures reveal an unforeseen narrative: AI is ubiquitous, yet operations are not becoming easier to manage. Currently, 98% of organizations utilize AI in fraud and AML processes, with 95% expressing confidence in its effectiveness; meanwhile, headcount plans rose from 88% to 94% year-over-year, and 83% anticipate budget increases in 2026.

Complexity Is Surpassing Automation

AI has not lessened the workload — it has revealed the extent of work that has always existed. Fraud losses are increasingly approaching revenue growth, threats are advancing more rapidly, and disjointed systems restrict the true potential of AI at scale. Key year-over-year shift:​

Leadership’s confidence in their teams’ performance is lagging. The number of leaders who disagreed with the statement, “fraud losses are growing faster than revenue,”​ dropped by almost 40% from the previous year

Inside the Numbers:​

AI is baseline, not experimental​

• 98% already integrate AI into daily workflows (only 2% still planning)​
• 95% are confident AI can detect and prevent fraud (52% very confident)​
• Top use case: AI/ML for transaction monitoring (30%)​

Fraud and AML investment keeps climbing​

• 83% expect fraud/AML budgets to increase in 2026​
• 94% plan to add at least one full-time hire (up from 88% in 2025)​
• 85% plan to add a vendor, 49% plan to replace one​

Fragmentation is the bottleneck​

• 95% claim “some integration” between fraud and AML systems​
• Only 47% run fully integrated workflows; the rest rely on partial connections​
• 80% say getting a unified view of data is challenging​

For many, time-to-value remains slow​

Only 10% go live in under two weeks​
38% take 1–3 months, 24% take 4+ months​
When implementations run long, top impacts include increased costs (52%) and prolonged fraud exposure (47%)​

Teams are growing, not shrinking​

94% plan to increase headcount despite automation gains​
85% see AI agents as support/augmentation, not replacement (only 12% see eventual replacement)​

Top fraud threats reported:​

• Account takeovers: 26%
• Promo/discount abuse: 18%
• Return fraud: 18%​

“Fraud and financial crime were supposed to become more manageable as AI matured,” said Tamas Kadar, CEO and co-founder, SEON. “Instead, 2026 is the year leaders are confronting a more complicated reality. AI adoption is real, confidence is high, but the scale and pace of fraud — compounded by fragmented systems — continue to drive increased investment rather than reduced overhead. The bottleneck is no longer whether AI works. It’s everything around it: disconnected data, siloed teams, slow implementations. The organisations that pull ahead will be the ones that unify fraud and AML intelligence, shorten the distance between threats and controls, and treat integration as strategy, not plumbing.”​

Fast-Growing Companies Invest in Integration Early​

Organisations growing 51%+ are nearly twice as likely as slower peers to report that achieving unified visibility is “not very challenging.” They treat integration as infrastructure, not an IT project.​

What’s Next: From “Does AI Work?” to “Can We Trust It?”​

With adoption near-universal, the conversation is shifting to governance, explainability and accountability:​

• 78% say decentralised digital identity will become central to fraud/AML​
• 33% cite data privacy regulations (GDPR, CCPA) as the biggest external force shaping AML​
• 25% point to criminals’ advancing use of AI and obfuscation techniques​

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