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Anti-Money Laundering: Emerging Risks and Regulatory Shifts

This article first appeared in the February 2026 issue of Financier Worldwide magazine. The entire publication is available at: https://www.financierworldwide.com/indepth-feature-anti-money-laundering-2026 (Subscription required)

“Q. What are the most pressing anti-money laundering (AML) risks currently facing the US? To what extent are you seeing the emergence of threats such as synthetic identities, AI driven fraud and other technology enabled laundering methods?

A. Some of the most pressing anti-money laundering (AML) risks we are seeing relate to changing national security priorities, including foreign terrorist organisations, export controls violations and sanctions. Those risks have always been important, but they have become significantly more complex for financial institutions (FIs) to manage in the current environment. At the same time, there is increased focus on knowing your customer, fraud and money laundering, particularly as it relates to synthetic identity theft and deepfakes. Fraud and cyber security breaches were always ‘specified unlawful activities’ for money laundering purposes, but they were often operationalised separately, which created silos and gaps. What we are seeing now is a shift toward thinking about these risks more holistically, as institutions recognise how closely connected they are in practice and operations.”

Q. How do emerging typologies of money laundering increasingly intersect with fraud schemes?

A. They have always intersected legally. Fraud generates the unlawful proceeds; as soon as those proceeds are moved, that activity constitutes money laundering under the criminal statutes. Cyber security weakness is central to how this plays out in practice. It is the predominant way fraud is carried out today – online, remotely and without face-to-face interaction. Weak cyber security creates the environment that provides anonymity and enables bad actors to obtain funds and move them through the financial system.

Q. How are lawmakers and regulators in the US navigating the tension between AML obligations and data privacy laws, especially in relation to customer due diligence and information sharing?

A. In the US, FIs do not face data privacy restrictions when sharing information with the government for certain regulatory purposes. For example, filing suspicious activity reports or currency transaction reports does not trigger any privacy restrictions. AML obligations at the federal level have remained largely intact. State regulatory agencies have taken on an even more active role in supervision and enforcement, particularly in areas such as payments and money transmission licensing, which can create challenges with coordination and information sharing for the institutions. The US also has relatively broad statutory safe harbour provisions that permit information sharing among FIs in cases involving suspected money laundering or terrorist financing. Those mechanisms allow institutions to share customer information without violating data privacy laws and are broader than what exists in many other jurisdictions.

Q. What are the biggest operational challenges companies in the US face in maintaining AML compliance – particularly around data management, transaction monitoring and reporting? How are technology solutions helping to streamline these processes?

A. We think the biggest challenge is governance. It comes down to very basic questions. How strong is data quality and the ability to detect poor data? Are the models performing as intended? Can institutions prove that through testing and validation? Execution is another major issue. There are many impressive tech tools on the market, but once institutions try to operationalise them at scale, weaknesses in governance often become apparent. When technology is implemented the right way, it can be very effective. It can drive efficiency, improve how institutions identify customer, transaction and relationship risk, and lower costs over time. But large institutions are often dealing with dozens of legacy systems that are difficult to integrate, while smaller institutions may not have the budget or technical expertise needed to implement complex solutions. The longer-term vision is better visibility across risk areas, including money laundering, sanctions, fraud and other domains.

Q. How are companies approaching the integration of new AML technologies – such as artificial intelligence (AI) driven monitoring, automated know your customer, or blockchain analytics? What barriers are they encountering in terms of cost, interoperability or regulatory acceptance?

A. Companies are often integrating new AML technologies into complex legacy environments where systems developed or acquired over time do not easily integrate. That makes interoperability a significant challenge, particularly for organisations that have grown through acquisitions. A key lesson has been that integration cannot be technology-led. Successful efforts start with governance, organisational alignment and clearly defined processes. Then, the selected technology supports those decisions. When institutions allow a vendor or a tool to dictate process or data requirements, integration efforts tend to break down. There are also practical limitations in the technology itself. Customer onboarding data, transaction information and areas such as digital assets often require different analytics tools, which means institutions frequently rely on multiple tools to cover gaps. That complexity reflects the reality that no single technology solution is designed to do everything that an FI needs today.

Q. How should companies assess the effectiveness of their AML programmes? What approaches or tools are proving most valuable in driving continuous improvement?

A. Assessing AML effectiveness is inherently difficult because you are often trying to prove a negative. AML regulations are required to be reasonable, not perfect. Firms are expected to strike a balance between effective risk management and customer experience, recognising that some issues will inevitably be missed and that overly burdensome controls can create their own problems. Where we are seeing the most progress is with the use of data and analytics, to evaluate which controls and rules are truly effective. This is helping firms move away from static, annual risk assessments that can quickly become outdated, and toward more continuous, data-driven diagnostics. As customer onboarding and transactions become more digital, institutions have better data to analyse patterns of behaviour rather than relying solely on hard thresholds. That shift toward behavioural analysis and faster feedback loops is proving critical as threats grow more sophisticated and evolve more quickly.

Q. As financial crime continues to evolve, what do you see as the most critical shifts that will shape the future of AML regulation, enforcement and compliance over the years ahead?

A. AML regulation and supervision shifts in response to global events, emerging threats and national security concerns. As federal priorities shift, we are seeing increased state-level activity. Technology will also play a central role in the future of AML. Regulators and agencies are increasingly using data analytics and AI-driven tools to identify risk within FIs, which allows them to focus examinations more precisely on areas of genuine concern. They expect FIs to design their programmes to use data to more accurately target risk. Firms will have to design their compliance programmes to focus on data quality to allow for behavioural analytics and more dynamic risk identification. At the same time, AML remains an inherently global discipline. Changes in geopolitical dynamics and international relationships can influence risk assessments, enforcement coordination and information sharing across borders. As a result, FIs will need to remain adaptable as the global threat landscape evolves.”

Permission to use this reprint has been granted by the publisher.