Why Banks are Falling Behind in the Cyber Arms Race

In an era where technology is advancing at breakneck speed, a troubling gap has emerged between financial institutions and the criminals they seek to thwart. 

A recent industry survey by RedCompass Labs, a provider of financial crime detection solutions, has unveiled a stark reality: banks are struggling to keep pace with increasingly sophisticated financial criminals, particularly in the realm of cybercrime.

The study, which surveyed 300 senior payments professionals at US banks, paints a concerning picture: banks estimate they are lagging an average of 8.2 months behind criminals in adopting and leveraging new technologies for financial crime detection and prevention.

The AI double-edged sword

This lag in stopping attacks against financial institutions has a plethora of reasons, but a main factor drawn from the report was AI-augmenting attacks of various methods.

This technological gap is not uniform across the banking sector, however. Smaller banks estimate criminals are just 2-3 months ahead, while some larger institutions fear the gap could be as wide as 23 months. Despite this lag, 75% of banks surveyed expressed confidence they can eventually close this gap.

However, experts warn this optimism may be misplaced given current detection rates.

More than half (57%) of banks believe AI will make financial crime detection more difficult, with 16% fearing it could render detection nearly impossible.

The growth of AI has enabled more sophisticated cybercrime, allowing criminals to create increasingly convincing scams and automate their operations at scale. 

However, AI is not just a tool for criminals. Larger banks, in particular, see potential in AI for fighting financial crime. Among these institutions, 54% expect AI to simplify detection, and 36% believe it could potentially eliminate financial crime altogether.

This optimism suggests that with proper implementation, AI could become a powerful ally in the fight against financial criminals. Despite the urgent need for rapid adaptation, banks report significant challenges in swiftly updating their systems to address emerging threats. A majority (59%) say it takes 4-6 months to update fraud models after identifying new financial crime red flags. Internal governance (27%), complexity (26%), and change management processes (24%) were cited as key obstacles to more frequent model updates.

Finance’s future security

To begin successfully mitigating the risks of fraud, the report says banks need "curious, autonomous AI agents that know what they are looking for and never tire or get distracted." 

This points to a future where AI is not just a tool for detection, but an active participant in the fight against financial cybercrime.

Moreover, there's a growing recognition of the need to support smaller financial institutions in this technological arms race. Todd Conklin, the US Treasury Department's Chief AI Officer and Deputy Assistant Secretary for the Office of Cybersecurity and Critical Infrastructure Protection, noted a "significant reduction" in fraud at some of the country's largest financial institutions thanks to AI. 

As criminals continue to innovate and exploit new technologies, it's clear that banks must redouble their efforts to keep pace. The future of financial security may well depend on how quickly and effectively banks can harness the power of AI and other emerging technologies to stay one step ahead of increasingly sophisticated cyber criminals.

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