Anti-Money Laundering (AML),
Fraud Management & Cybercrime,
Fraud Risk Management
ACAMS Highlights Need for Enhanced Data, Architecture, and AI in Investigative Practices
An emerging trust crisis in the financial system, largely exacerbated by artificial intelligence and deepfake technologies, poses significant challenges for investigators targeting fraud and other financial crimes. According to the Association of Certified Anti-Money Laundering Specialists (ACAMS) Global AFC Threats Report 2026, criminals are increasingly leveraging advanced AI tools to execute sophisticated fraudulent schemes.
The report underlines a continuing trend where the malicious use of generative AI has been identified as the foremost risk in combating financial crime, marking the third consecutive year for this finding. An overwhelming 75% of compliance professionals surveyed indicated that AI presents a high or very high risk. Additionally, AI is facilitating the growth of “fraud as a service” platforms, allowing less experienced criminals to orchestrate elaborate scams with relative ease.
As the threats evolve, anti-financial crime teams are adjusting their resource allocations. Notably, 84% of those surveyed emphasized a heightened focus on combating scams directly targeting individuals. AI-driven identity fraud emerged as a primary concern, as traditional methods of verification struggle against the reliability of advanced deepfakes and holograms.
Justine Walker, executive vice president of thought leadership at ACAMS, remarked, “Baseline expectations have shifted dramatically; what was acceptable two years ago will not suffice in the near future.” The organization conducted a survey with 1,400 compliance professionals, predominantly from the financial sector, to assess these changing dynamics.
While organizations are piloting various AI tools—56% report currently implementing AI-driven solutions—they face significant internal challenges. Legacy IT systems and outdated data practices are identified as high risks to the efficacy of anti-financial crime programs, as non-unified datasets lead to biases and increased false positives, straining already limited compliance resources.
The financial industry is also contending with a fragmented regulatory landscape and rising geopolitical tensions fueled by fluctuating tariffs and sanctions. A substantial 72% of respondents anticipate major changes to AI regulations in the coming year, while 70% foresee alterations in cryptocurrency regulations, indicating a complex and rapidly evolving environment.
In light of these challenges, businesses are exploring new avenues for fraud detection. Approaches such as behavioral pattern analysis, device intelligence, and multi-layered verification strategies are becoming imperative. However, institutions must grapple with a fast-evolving underground banking system that has embraced digital technologies quicker than defenses have adapted.
Walker highlights that the historical hawala networks are becoming increasingly sophisticated, exacerbating the struggle for institutions unprepared to combat these digital threats. The call for a cohesive response to the evolving regulatory landscape has never been more urgent, as criminals exploit existing vulnerabilities in compliance frameworks.
For Chief Information Officers (CIOs), developing a robust anti-financial crime strategy is anchored in modernizing data architectures and ensuring system integration and AI readiness. As organizations strive for resilience amid disruption, deploying intelligent systems that can adapt to emerging threats is crucial for safeguarding against future financial crimes.