Feedzai index exposes 13-point AI readiness gap in global banking

A 1,000-leader survey finds banks overrate their fraud readiness by 13 points while agentic AI adoption stalls on data fragmentation.

By Disrupts Editorial Team Wed, 14 October 2026 AI level 2 of 5

AI level 2 of 5: drafted by our AI editorial assistant from the company's announcement; fact-checked, edited and signed off by Mark Walker, Editorial Director. What the levels mean

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Financial institutions worldwide are spending aggressively on AI-powered fraud defences while simultaneously overstating how effective those defences actually are. That is the headline finding from Feedzai's Fraud Readiness Index 2026, a survey of 1,030 senior fraud and financial crime leaders across 12 countries published on 8 October 2026.

Banks and fintechs rated their own fraud readiness at an average of 80.2 out of 100. When scored against measurable capabilities across data infrastructure, AI maturity, network intelligence, and operational structure, the actual average fell to 66.9. That 13.3-point gap is not a rounding error; it is a structural blind spot in how the industry perceives its own resilience against a threat landscape that is itself being accelerated by AI.

The data plumbing problem

The report's most consistent finding is operational rather than technological. Seventy-three per cent of fraud analysts say they spend too much time pulling data manually from siloed systems rather than analysing threats. Only 41% of institutions have fully connected data flows across fraud, anti-money laundering, compliance, and cybersecurity functions. In practice, an analyst investigating a suspicious payment may need to check multiple separate systems before assembling a complete customer picture, and every minute spent doing so is a minute not spent stopping fraud.

Budget is not the bottleneck. Ninety-six per cent of surveyed leaders expect their AI fraud-tool budgets to grow over the next two years. The constraint is integration: the plumbing that would allow AI agents to act on unified, real-time data simply does not yet exist at most institutions. Just 25.5% of institutions reached the Index's "leading" tier, scoring 76 or above, and the differentiator was precisely their ability to connect data and reduce manual analyst burden.

Nuno Sebastião, Co-founder, Chairman and CEO of Feedzai, framed the problem clearly: "Banks aren't short on ambition or budget. What's holding them back is inefficiency: data that doesn't connect and analysts spending their day hunting for information instead of stopping fraud with modern technology such as AI. Criminals don't target one bank at a time, so the industry can't defend itself one bank at a time either."

The agentic AI wager and the collective defence shift

That last point is shaping an unlikely strategic pivot. Scams, defined as criminals tricking customers into transferring money themselves, are now the largest single source of fraud losses in 10 of the 12 countries surveyed. Fraudsters share intelligence and infrastructure fluidly across institutions. Banks, historically fiercely competitive on customer data, are beginning to respond in kind: 87% say they would consider securely sharing fraud intelligence with direct competitors.

This is a material shift in the competitive calculus of retail financial services. The logic mirrors dynamics already observed in cybersecurity, where threat-intelligence sharing consortia have become a baseline expectation for regulated entities. If the same norm takes hold in fraud prevention, it creates a platform opportunity for intermediaries, whether dedicated fraud-intelligence networks or AI vendors positioned to act as trusted brokers, that could reshape the fintech infrastructure market.

The agentic AI angle compounds this. Sixty-eight per cent of institutions are using or planning agentic AI for three or more fraud use cases, a significant adoption signal. Yet trust in autonomous decision-making remains the industry's top concern, a tension that will reverberate into regulatory conversations around AI governance in financial services. The EU AI Act's requirements for human oversight of high-risk automated decisions, which include fraud scoring in consumer credit and payments, will test whether banks can deploy agentic systems at the speed the threat environment demands while remaining compliant.

For cross-sector investors, the Index points to a clear infrastructure gap: the institutions best placed to capitalise on the next wave of AI-native fraud prevention are not those spending the most, but those that have solved the underlying data integration problem first. That makes data connectivity and real-time orchestration platforms the quiet winners of a market that 96% of decision-makers expect to grow.