How FinCEN’s new AML/CFT proposal leverages AI for better compliance

FinCEN

In a move to modernize AML/CFT frameworks, the U.S. Department of the Treasury’s FinCEN has unveiled a proposal under the Anti-Money Laundering Act of 2020.

According to Napier AI, this proposal mandates that AML/CFT programs must adopt a risk-based approach to be deemed compliant, marking a significant departure from traditional ‘check-the-box’ methods.

For the first time, FinCEN’s proposal explicitly requires financial institutions to develop and implement AML/CFT programs that are both effective and reasonably designed, with specific components to ensure compliance. These programs must incorporate a mandatory risk assessment process, aligning closely with government-wide AML/CFT priorities to tailor risk-based approaches appropriately.

In terms of technology and innovation, the proposal puts a strong emphasis on the adoption of Artificial Intelligence (AI) to enhance these compliance programs. AI can drastically improve the accuracy and efficiency of risk assessments by automating routine tasks and minimizing human error, which is critical in maintaining the integrity of financial systems.

Napier AI, a key player in financial compliance technology, supports the move towards a more dynamic and responsive regulatory environment. The company advocates for the integration of AI through its Perpetual Client Risk Assessment (PCRA) technology, which provides continuous, real-time insights into customer risk profiles. This approach helps in rapidly identifying and reacting to potential threats, thereby enhancing the effectiveness of AML/CFT programs.

Furthermore, Napier AI stresses the importance of explainability in AI applications, ensuring that AI-generated decisions are both transparent and comprehensible to human operators. This transparency is essential not only for compliance but also for fostering trust between financial institutions and regulatory bodies.

Additionally, the proposal encourages institutions to consider broader AML/CFT priorities by incorporating specific financial crime typologies developed in collaboration with agencies like the UK’s Financial Conduct Authority (FCA). This targeted approach helps in reducing inefficiencies such as the high volume of false positives in transaction monitoring systems.

Napier AI also underscores the significance of continuous risk assessment and the value of public-private data sharing in refining Suspicious Activity Reports (SARs), which can significantly improve the effectiveness of AML/CFT measures.

As regulatory landscapes evolve, the integration of innovative technologies and real-time data analysis stands to offer not only compliance advantages but also operational efficiencies, potentially turning regulatory adherence into a competitive edge for proactive institutions.

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