Financial Crime Has Crossed $4.4 Trillion – AI Can Level the Playing Field

The numbers are stark: Since 2023, illicit financial activity has surged by $1.3 trillion, reaching an estimated $4.4 trillion globally — a compound annual growth rate of 19.2% that far outpaces the growth of the world economy. Fraud losses alone now top half a trillion dollars, with $579.4 billion in combined bank fraud and scam losses recorded in 2025.

These are the headline findings of Nasdaq Verafin’s 2026 Global Financial Crime Report, the latest edition of a research initiative that combines proprietary financial modeling developed with Celent and Oliver Wyman, a survey of more than 500 anti-financial crime professionals, and in-depth executive interviews.

The picture that emerges is of a financial crime epidemic that continues to grow in scale and sophistication, and one that is increasingly being fought with the help of artificial intelligence (AI). By combining advanced technology with information-sharing and network-level intelligence, the report determined, financial institutions can do more than keep pace with criminals — they can get ahead.

According to Stephanie Champion, Executive Vice President and Head of Nasdaq Verafin, “the convergence of cutting-edge technology, combined with improved public-private and private-private collaboration, creates a network effect, magnifying the reach of our collective efforts and helping remove criminals from the financial system for good.”

The AI Arms Race

Criminals have moved fast. Ninety percent of financial crime professionals surveyed noted an increase in AI-driven attacks at their institution over the past two years — with more than half describing the increase as significant, at 20% or more. According to Champion, AI has fundamentally changed what adversaries are capable of: scams are more convincing, operations are more scalable, and language barriers that once limited the reach of criminal networks have been effectively eliminated.

Nowhere is this shift more visible than in fraud scams, which the report indicates are growing at more than twice the rate of bank fraud. The explanation is straightforward: criminals follow the path of least resistance.

“As financial institutions strengthen their controls at the institution level, criminals begin targeting individuals posing as trusted or legitimate counterparties,” Champion explained. “Criminals will then deceive victims into sending the payment themselves.”

Financial institutions are fighting back with the same tools. According to the report, nearly nine in ten professionals (89%) report either using AI or actively evaluating it, and 79% plan to increase AI spending over the next two years. The most tangible returns are appearing in anti-money laundering (AML) transaction monitoring, fraud detection, and investigations. More than a third of respondents report generative AI (genAI) or large language models (LLMs) in active production, with an additional 35% in proof-of-concept stages.

Yet putting AI to work at scale remains a formidable challenge — 74% of institutions cite implementation as their biggest AML hurdle, with integration and change management, rather than technology availability, proving to be the primary bottlenecks.

The Collaboration Imperative

Technology’s full potential can only be unlocked when institutions are able to see beyond their own walls. That’s precisely where collaboration becomes the force multiplier.

Detection and prevention efforts have historically been institution-centric and fragmented. Criminal networks exploit this deliberately, operating below single-institution visibility thresholds and moving funds rapidly across accounts, institutions, and jurisdictions.

“No single institution, sector, or jurisdiction can fight financial crime alone,” Champion said. “Criminal networks orchestrate sophisticated fraud and money laundering schemes with the scale and coordination of multinational corporations, sharing data, intelligence, and criminal best practices.”

The solution, Champion explained, lies in adopting technology that leverages consortium data networks, allowing institutions to detect risk at the network level rather than at the individual transaction or customer level. By observing network-wide patterns, institutions can intervene earlier and upstream, shifting fraud management from reimbursement and recovery to proactive prevention.

The report also calls for a broad coalition: social media platforms, telecom companies, and digital asset providers all need to be part of the response given that fraud and scams increasingly originate outside the financial system entirely.

The report found that 58% of respondents believe collaboration between financial institutions and public sector stakeholders would materially benefit their anti-financial crime programs. Yet significant barriers remain: 67% cite concerns over legal exposure and 53% point to a lack of regulatory guidance as the primary obstacles to bank-to-bank information sharing, even as institutions broadly recognize its value.

“The scale, speed, and sophistication of today’s financial crime perpetrators demand a response equal to the threat,” Champion said. “By combining advanced AI with collective intelligence and shared accountability, we can disrupt criminal networks earlier, prevent harm before it occurs, and protect the integrity of the global financial system.”

The 2026 Global Financial Crime Report is available here.

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