Over £2 trillion is laundered through the global financial system every year, fuelling everything from trafficking and terrorist activity to grand corruption and environmental crime. The scale of the challenge can seem insurmountable, but at Themis, we believe that the intelligent application of technology, particularly AI, may finally shift the balance. Not just by speeding up detection or easing compliance burdens, but by fundamentally changing how we fight financial crime.
It’s no surprise, then, that AI is a central topic of conversation across our business, from product to policy, from engineering to compliance; but AI isn’t just an exciting technology story - for CFOs, it’s a financial one. From cost control to capital allocation, AI is quickly becoming a key lever for value. And across both public and private sectors, the case for strategic investment is growing stronger by the day.
In the UK, the government has committed up to £2 billion by 2030 to support AI development, funding research, infrastructure, and oversight. Projects like the Isambard-AI supercomputer, set to become one of Europe’s most powerful, reflect a national effort to scale AI capacity responsibly and competitively. Globally, similar efforts are underway. The US, EU, China and Gulf economies are pouring billions into national strategies to build not only AI capability but the regulation, data infrastructure, and digital talent pipelines to support it.
Private capital is moving fast too. According to CB Insights, in 2023, global AI startups raised approximately $50 billion in venture funding, often at really strong multiples. But perhaps more telling is how AI is being applied within established businesses, especially those operating in complex, regulated environments. A recent study by Basware found that finance teams using AI are achieving average returns of £1.36 for every £1 invested. Deloitte reports that 93% of firms implementing AI-led automation have already realised measurable cost savings. Even in traditionally risk-averse sectors like banking, AI is being embedded into fraud detection, customer onboarding and risk scoring, with projected operational savings running into the hundreds of millions over the next five years.
At Themis, we’ve seen the same pattern across our client base. Many are using AI to reduce manual processing burdens, streamline reviews, and accelerate investigations, all without increasing headcount. This is the heart of what AI can offer financially: the ability to do more with less; and the gains aren’t just in cost-cutting.
Smart deployment of AI often creates revenue multipliers too. A recent McKinsey study estimated that generative AI could unlock between $200 billion and $340 billion in annual value for the financial services sector alone by improving decision-making, enhancing customer journeys, and accelerating turnaround times.
There are concrete examples of this happening now. Citi and Ant International recently piloted an AI-powered FX hedging tool that helped one major airline reduce hedging costs by 30%: an improvement that translated directly to the bottom line. Fidelity Investments has used AI in procurement to reduce contract processing times by 50% and cut spend by 20%, delivering meaningful cost efficiency in a legacy-heavy environment.
In anti-financial crime, the returns are just as tangible. According to vendors like Tookitaki, ThetaRay, and Hawk AI, some banks using AI-enhanced AML platforms have cut false positives by between 70% and 90%, while reducing compliance costs by up to 60%. These results vary by implementation, but the direction is clear: smarter, faster systems that reduce manual triage and improve investigative accuracy.
Of course, not all deployments succeed, and this is where discipline matters. Poorly scoped or overly generic tools can struggle to deliver value, especially if adopted without clear use cases. IBM research suggests that as many as 30% of enterprise AI pilots fail to scale, often due to integration or governance challenges. But when focused on high-cost, high-friction areas, such as document-heavy compliance processes or large-volume transaction monitoring, the upside is significant. AI can help teams move faster, reduce error, and cut through backlogs, all while enabling human specialists to focus on high-level decisions rather than data prep.
From a financial perspective, the real attraction of AI isn’t just optimisation—it’s resilience. Markets, regulations, and risk environments are changing at speed. Systems that learn, adapt, and scale in real time will be more cost-effective over the long term than static, manual, or fragmented setups. The return on investment isn’t only measured in headcount or speed, but in better controls, fewer failures, and stronger long-term positioning.
At Themis, we’ve seen growing interest from organisations looking to address precisely these issues, especially within their financial crime and compliance functions. Our own recent survey of industry leaders shows that while AI adoption is still uneven, the direction is clear: the next few years will see rapid acceleration in practical, risk-focused AI deployments. The challenge for leadership now is not whether to invest, but how to do so wisely.
For CFOs, this means applying the same standards we always have: evidence-based planning, measurable results, and strategic alignment. The difference is that AI now meets those standards more often than it used to and in more parts of the business. When the numbers add up, caution becomes inaction; and when the cost of standing still is rising, the prudent move is to act.
Artificial intelligence (AI) presents opportunities for transformational solutions to many of the world’s most pressing challenges. The threat of financial crime, which provides the lifeblood for the illicit economy in which organised crime, terror groups, and other serious criminal actors operate, is no exception. Download our insightful report today.
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