AI is transforming fraud itself, not just fraud detection. This global survey of 202 fraud, risk, and technology leaders examines AI-driven fraud trends, the deployment gap between AI ambition and production scale, false positive challenges, and investment priorities over the next 24 months.
Key figures
. Over 26% of organizations report fraud attempt increases above 51%, with AI acting as an accelerant across every fraud type simultaneously.
. Only 28% have fully deployed AI/ML fraud detection models at scale, a significant vulnerability as threats evolve.
. 33% report high false positive rates, creating customer friction that undermines trust at critical moments.
. 99% agree on the need for enterprise-wide fraud orchestration, yet few have achieved it. Third-party vendor models have the greatest influence on fraud decision-making.
. Identity verification and AI/ML for fraud detection lead investment priorities over the next 24 months.
Financial institutions have built their fraud defenses the way cities build highways — with one urgent patch at a time — leaving behind a patchwork of disconnected tools, isolated data, and strategies that stop at the edge of each product line, leaving a path of vulnerability. „These fragmented fraud architectures assembled under pressure are among the most costly liabilities on the balance sheet.” – FICO said in a press release.
The institutions winning the fight against fraud are not necessarily running the most models; they are running unified ones. Organizations pulling ahead are those that have replaced fragmented tooling with a single, trusted decisioning layer — one that orchestrates ML-driven models in real-time, across every product, portfolio, and channel, while drawing on global consortium data, internal signals, and third-party intelligence to drive the right outcome at every touchpoint.
The Gap Between Ambition and Execution
New research* reveals the scale of the disconnect, with 99% of organizations saying enterprise-wide fraud management is a priority. Yet only 28% have fully-deployed AI-driven fraud detection at scale. Nearly half (47%) identify integration complexity as their primary barrier.
The Bottleneck: Decisioning Infrastructure
Institutions with confidence gaps in their detection capabilities are accelerating adoption of agentic AI — but in doing so, may be widening the gap rather than closing it. Detection capabilities continue to outpace orchestration maturity. The constraint is not model quality. It is whether consistent strategies are being applied across the enterprise, and whether the resulting decisions are executed holistically.
The (Not So) Hidden Cost: Your Customers
The damage is not confined to fraud losses. One in three organizations report a high or very high false-positive rate. In Asia-Pacific, the figure reaches 50%. In high-growth digital markets where customer acquisition is expensive and loyalty is fragile, friction incurs a direct and measurable cost. Every declined transaction, every flagged account, every unnecessary step in a customer journey is an opening for a competitor.
Institutions that rely on friction to manage risk are treating symptoms, not disease. It is a workaround masquerading as a strategy. It signals an architectural problem that better detection models alone will never solve.
The Infrastructure Reckoning
When strategy is aligned, the differentiator is no longer intent; it’s execution and having the infrastructure to sustain it.
As fraud grows more sophisticated and coordinated, success will not be measured by the number of models deployed but by the underlying architecture. What separates the clear leaders is the ability to orchestrate every fraud decision at the individual level, delivering protection that is contextual, personalized, and consistent across the enterprise.
Unified decisioning is not a feature to be added to a product roadmap. It is the foundation. Every model, every signal, every strategy either builds on it or operates beneath its potential. Those still building around it — rather than from it — are not just behind. They are exposed.
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*Fraud in the Age of AI: Trends, Threats, and Management Tactics – The FICO and Finextra global survey included responses from more than 200 senior professionals across retail banks, neobanks, and fintechs in North America, Europe, Latin America, and Asia-Pacific; with expert commentary from JPMorgan Chase, BNY, and LHV Bank.
Banking 4.0 – „how was the experience for you”
„To be honest I think that Sinaia, your conference, is much better then Davos.”
Many more interesting quotes in the video below:
