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Artificial intelligence (AI) is transforming both sides of the financial crime equation. Financial institutions are adopting AI to enhance screening, due diligence, and transaction monitoring, yet criminals are equally quick to weaponise the same technology – scaling their operations, increasing sophistication, and widening the space between offence and defence. The World Economic Forum has already identified AI-enhanced cybercrime and fraud as one of the top five fastest-rising global risks, underscoring just how quickly criminal groups are leveraging AI to expand their reach and automate attacks at scale.
AI is accelerating both sides of the financial crime equation
Although AI empowers financial institutions to protect customers more effectively, attackers evolve just as fast, making financial crime prevention a perpetual cycle of escalation. As one respondent to the Napier AI / AML Index 2025-2026 described, the sector will continue to experience peaks and troughs in criminal activity as attackers push ahead and risk teams respond in turn.
This dynamic is playing out across a threat landscape that is becoming more complex. I recently spoke at an ACAMS UK Chapter event, where we discussed criminal use cases included the use of generative AI to create deepfake synthetic identities and to automate phishing and social engineering, both of which are increasingly common predicate behaviours linked to money laundering.
These tools dramatically reduce the barriers to entry for bad actors, enabling criminal networks to industrialise their operations and scale targeting at a pace traditional defences struggle to match.
What the UK’s criminal activity profile tells us
The UK’s own criminal activity profile reinforces the urgency. The United Kingdom lost more to money laundering in 2024 than 2023, even after financial institutions increasing their compliance spend by 15%. The deterioration in markets like the UK underlines that the fight is far from over and the need for explainable, compliance first AI has never been greater. That dependence creates a critical intervention point for institutions, provided they can detect the traces these networks leave behind. However, the complexity and fragmentation of these criminal operations mean that human analysts and legacy systems often miss the subtle behavioural signals that reveal cross-network coordination.
Responsible AI: the differentiator that will define future success
This is where AI can close the gap. AI-powered monitoring systems can analyse volumes of data at a speed and granularity far beyond what is possible manually, enabling the discovery of behavioural patterns that point to illicit flows. These might include the coordinated movement of funds through groups of accounts, the structured dispersal of payments intended to avoid thresholds, or the rapid purchase and resale of high-value goods and assets used for laundering. AI gives institutions the ability to identify patterns, raise alerts, and uncover hidden networks far faster than human analysis alone.
Yet, while AI is an essential tool, it cannot operate in isolation. Meaningful impact requires pairing AI with strong governance, human-in-the-loop oversight, and robust regulatory alignment. This perspective aligns with the broader industry sentiment: AI must be explainable, auditable, and responsibly deployed. As regulators such as the FCA encourage innovation through initiatives like the AI Sandbox and AI Lab, they simultaneously reinforce expectations around model risk management, fairness, and the mitigation of unintended consequences. Innovation is necessary, but governance is non-negotiable.
Data versus data: the new frontline of financial crime
The strongest message from law enforcement at ACAMS distilled the challenge into one blunt reality: we are fighting data with data. Criminals are scaling through data and AI, and financial institutions must respond in kind, adopting technologies that allow them not just to keep pace, but to move ahead of attackers. The cat-and-mouse dynamic may never disappear entirely, but it is possible for the defenders to set the tempo, provided they have access to the tools, intelligence, and governance structures that enable effective action.
AI is reshaping the fight against financial crime. It increases detection speed, enhances accuracy, and reveals networks that once remained hidden. But as AI accelerates on both sides, the institutions that succeed will be those that innovate responsibly – deploying AI that is powerful enough to confront modern threats, yet explainable and compliant enough to withstand scrutiny. The opportunity is significant, and the responsibility is even greater.
To explore deeper insights into global AML effectiveness, emerging criminal typologies, and how markets compare on AI readiness, read the Napier AI / AML Index 2025–2026.
