Investment priorities
Investment is following the fastest-moving threats
Investment priorities are shifting towards AI
Investment priorities offer an early indication of where organisations believe financial crime risks are heading, not just where they are today. Respondents are directing resources towards AI-enabled fraud and governance capabilities, reflecting the view that technological change is outpacing existing controls. Rather than waiting for greater regulatory certainty, firms are investing in the capabilities they believe will be needed to respond to an increasingly dynamic threat landscape.
The findings suggest investment decisions are becoming more proactive than reactive. Organisations are balancing immediate operational priorities with longer-term resilience, strengthening both fraud prevention and the governance needed to deploy AI responsibly. This points to a broader shift in strategy: investment is increasingly driven by anticipated risk rather than historical experience alone.
Key statistic
Half are backing AI fraud prevention
Investment is following the fastest-moving risk. Half of respondents, 50%, say their organisation is most likely to invest in AI fraud prevention over the next 12 months, comfortably the top answer, with internal AI governance second on 38% (base: 100). The top two priorities are both AI. That is a clear reading of where firms think the threat is heading, and it is being backed before the guidance to spend it well exists. Making AI fraud prevention work needs standards, shared definitions and a common view of what good looks like, and none of that can be bought by a single firm on its own. That is why respondents, asked what would help most, point somewhere other than their own budgets.
Plan to invest in AI fraud prevention
The findings reveal a disconnect between operational challenges and investment priorities. While AI dominates planned investment, data-sharing infrastructure attracts relatively little attention despite widespread recognition of its importance.
Investment is not confined to the largest institutions. Organisations of all sizes report similar intentions to invest, indicating that AI fraud prevention is becoming a baseline capability across the sector.
Of 99 responses name cross-industry data and intelligence sharing
Key statistic
The ask is shared data and intelligence
Asked what would benefit most from greater collaboration, respondents point to data. Cross-industry data and intelligence sharing is the most common theme, appearing in 32 of 99 responses, with joint fraud and mule account detection close behind on 31. Responses were coded on meaning rather than keyword against an eight-theme codeframe plus a residual category, with multi-coding allowed. The two leading themes overlap heavily. Many respondents describe data sharing not as a general principle but as the mechanism for one specific job—spotting mule accounts and fraud faster than a single institution can alone. That is a narrow, practical ask. It is also one no firm can deliver by itself, which is what separates it from everything else in this report. The rest of the findings describe pressures firms can act on individually. This one names infrastructure the industry has to build together.