Getting ahead of the AI game in financial crime prevention

The game of financial crime never stops changing, as bad actors find more ingenious, tech-driven ways to defraud financial institutions and their customers. With scams increasing by 35% worldwide in 2026, ¹ criminals aren’t just stepping up their ability to execute fraudulent transactions; they are also getting better at targeting identities and opening accounts.

Assisted by AI, financial crime is moving upstream and exploiting weaknesses in its institutional opponents long before it initiates suspicious transactions. For financial institutions themselves, that means moving beyond a transaction-centric approach to fraud and anti-money laundering (AML), rethinking where risk begins and determining how to get ahead of it, fast.

How is AI changing financial crime tactics?

Fraud behaves much like a balloon: If you squeeze it in one place, you push it toward another. So, as the largest banks tighten their controls against, say, impersonation scams, fraudsters simply and swiftly switch to a different fraud scenario or often target other institutions with lesser controls.

But there are other trends at play. Advancements in AI are lowering the barriers to creating convincing scams, synthetic identities and fraudulent documentation. As a result, banks must now make their most consequential risk decisions earlier in the money lifecycle: – not at the moment transactions occur, but when accounts are opened, devices registered, credentials recovered or customer profiles changed.

Why are transaction-based fraud controls no longer enough?

Fraud, then, no longer begins when money moves, but when trust is compromised. Today though, many financial crime controls only kick in after a customer has been authenticated and permitted to use bank accounts and services.

The industry has become exceptionally good at detecting bad transactions. But this reactive approach is playing into the hands of fraudsters. Now the question isn’t whether a transaction is legitimate, it’s whether the institution can trust the individual initiating it.

Consequently, the next big challenge for banks is not to prevent fraudulent transactions, but to stop bad actors from gaining access to transactions in the first place.

How does AI make financial crime faster and cheaper?

Meanwhile, AI continues to make fraudsters a more powerful adversary than ever to financial institutions. AI may not yet be creating entirely new forms of financial crime, but it certainly makes existing schemes faster and cheaper to perpetrate.

With generative AI in particular, it’s easier to create believable utility bills and other account-opening documents from simple prompts, eliminating the need for manual document alteration. Deepfake videos, however, although effective at impersonating individuals, are still too costly to create at scale.

How can agentic AI strengthen financial crime prevention?

Two can play the AI game, and banks are harnessing the positive powers of purpose-built AI agents to bolster their financial crime prevention frameworks. Agentic AI isn’t replacing traditional transaction-monitoring rules and models; the architecture of the future will combine behavioral monitoring with established platforms, human oversight and rule overlays that respond quickly to new patterns.

Again, it’s the sheer scalability of AI that makes it efficient at both perpetrating and fighting fraud. With human intervention when necessary, agentic systems can generate new rules and bring together vast volumes of information far more quickly than manual analysis. This helps AML investigators prepare consistent suspicious activity reports (SARs) in minutes rather than hours.

Why is continuous trust assessment important in banking?

As fraudsters continue to operate upstream of transactions, AI’s enormous capacity to work at speed and scale will facilitate the shift from periodic identity verification to continuous trust assessment. This in turn will enable banks to focus more heavily on stronger identity validation, adaptive authentication, device intelligence, behavioral analytics and risk-based customer controls.

Financial crime will only grow more sophisticated, but with their own advanced fraud prevention tools, banks can get ahead of the game. In days to come, competitive advantage will belong to institutions that can continuously establish, validate and maintain customer trust across every interaction, not just every transaction.

¹The Sumsuber, Scam Attempts Rise 35% as Mobile Devices Dominate Fraud, October 2026