In this episode of The Fintech Show, Tristan Prince from NOTO and Robert Brooker from Opus Advisory Group broke down the converging forces that are mandating a radical shift in financial crime prevention. Their central argument is that organizations are now caught between two major pressures: the immediate threat of high-velocity, AI-enabled financial crime and stringent new regulatory accountability.
Prince opened the discussion by focusing on the Economic Crime and Corporate Transparency Act (ECCTA), which now includes a provision for a failure to prevent fraud. This act places a heavy burden on organizations to definitively prove that they have sufficient processes and systems, across all employees and affiliates, to stop financial crime. This is where the industry faces its core challenge: fractured, siloed technology. Many firms have layered on various point solutions over the years for application fraud, biometrics, and transaction monitoring.
The issue is that these systems rarely communicate, creating “operational drag” and making it impossible for analysts to connect disparate data points across the customer journey. Prince shared the stark example of a customer who fails a KYC check at a call center, only to have their account emptied via an ATM shortly after, a scenario that happens because crucial signals are not shared between systems.
The need to consolidate is made urgent by AI-enabled fraud as fraud is now the UK’s largest crime, accounting for over 40% of registered offenses. NOTO warned that the sheer velocity and volume of attacks, from an organization expecting 100,000 applications suddenly facing 10 million, will overwhelm heritage controls. Prince starkly illustrated this mismatch: how can a legacy system limited to one transaction per second manage an AI-enabled attack hitting at a thousand? This surge in volume and frequency has fundamentally changed the nature of fraud, which is no longer a contained risk but a competitive differentiator; customers judge institutions on how they treat them after they have been victimized.
The current strategy of layering on more technology is not working as a recent Gartner survey found that while 53% of UK businesses plan to increase their fraud spending, 70% admit that risk levels are still climbing. Prince noted an unusual “bell curve” effect: when spending exceeds 10% of an IT budget, the effectiveness of identifying fraud actually starts to drop due to the complexity of managing these fragmented systems.
To counter this, NOTO advocates for a move to enterprise fraud management platforms. Prince suggests using a single API to migrate the entire estate to a real-time rules engine and a unified case management view. Crucially, their strategy involves supervised machine learning, which Prince argues is more effective long-term than an unsupervised approach, provided the underlying data governance is in place.
However, technology alone is not enough as Brooker stressed that to satisfy regulators, compliance requires a cultural shift. Organizations must adopt a “tone from the top,” establishing accountability at the board level rather than relying on “simple spot fixing or buying a new piece of shiny kit”.
This cultural change must address the urgent insider threat, particularly in fintech where organized crime places “foot soldiers” in contract centers for short stints. Brooker advises senior leadership to set an example by making internal examples of fraudsters, rather than dismissing staff quietly to avoid reputational damage. Ultimately, both Prince and Brooker agree that the true cost of fraud includes “operational cost bloat” and lost customer trust, making it imperative to move away from outdated systems now.
