The banking industry is finding that the hard work is only just beginning. While AI Is everywhere, fraud teams are still growing.
SEON has released its ‘2026 AI Reality Check – Fraud & AML Leaders’ report, based on a global survey of 1,010 fraud, risk and compliance leaders.
The report found that, while AI is widely embedded and trusted, it has not materially reduced the scope of operations. In many cases, the pace of threats, including criminals’ use of AI, is stretching that scope faster than efficiency gains can keep up.
One year-on-year signal stands out. The number of leaders who disagreed with the statement that “fraud losses are growing faster than revenue” dropped by almost 40% from the previous year – suggesting losses are pressing closer to, or even outpacing, growth for many organizations. AI is everywhere, but operations are not getting more manageable. While 98% of organizations now use AI in fraud and AML workflows and 95% are confident it works, headcount plans jumped from 88% to 94% year-over-year, and 83% expect budgets to increase in 2026.
The report unpacks what sits behind that shift, including why teams and budgets are still rising even with near-universal AI adoption, and how fragmented fraud and AML systems continue to block unified visibility and governance at scale.
Key highlights of the report (global and APAC) include:
- 98% already integrate AI into daily workflows, with the top use case being AI/ML for transaction monitoring (30% globally, 45% APAC)
- While 95% (91% APAC) report “some integration” between fraud and AML systems, only 47% (51% APAC) run fully integrated workflows, with many still relying on partial connections
- 94% (94% APAC) plan to add at least one full-time fraud/AML hire despite automation gains, with 85% (84% APAC) seeing AI agents as support or augmentation rather than replacement
- Top fraud threats reported include account takeovers (26% globally, 24% APAC), promo/discount abuse (18% globally, 26% APAC) and return fraud (18% globally, 8% APAC)
The report unpacks what sits behind that shift, including why teams and budgets are still rising even with near-universal AI adoption, and how fragmented fraud and AML systems continue to block unified visibility and governance at scale.
Organizations 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.
“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 organizations 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.”
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 decentralized 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
