ACAMS CAMS - Certified Anti-Money Laundering Specialist (CAMS7 the 7th edition)

Artificial intelligence and machine learning technologies support the risk-based approach (RBA) to AML compliance by enhancing an institution’s ability to identify, assess, and prioritize financial crime risks. Regulatory guidance emphasizes that these technologies should augment—not replace—human judgment.

One key benefit is advanced customer risk assessment. AI and ML can synthesize large volumes of customer data, including background information, transaction behavior, and external risk indicators, allowing institutions to develop more accurate and dynamic risk profiles.

AI and ML also enable the identification of complex networks among seemingly unrelated clients. Through network analytics and pattern recognition, these tools can uncover hidden relationships used in layering and structuring activities.

Additionally, AI-driven systems excel at detecting complex money laundering patterns within transaction data that may not trigger traditional rule-based alerts, improving effectiveness and efficiency.

Automatically generating SARs or adapting thresholds without human oversight is inconsistent with regulatory expectations. Human review and governance remain essential components of AML compliance.

Appointing individuals to serve in official capacities poses a higher money laundering risk because it can be used to obscure the true beneficial ownership and control of the company, making it easier to conceal illicit activities or the identity of those directing the business.

FATF standards require financial institutions to adopt a risk-based approach (RBA) that is informed by national and sectoral risk assessments. These assessments identify key threats, vulnerabilities, and typologies within a jurisdiction or industry and provide essential context for institutional risk management.

Financial institutions must reference and align their internal AML/CFT risk assessments with the findings of NRAs and sectoral assessments. This means demonstrating awareness of identified risks and showing how these risks are mitigated through policies, controls, and procedures.

However, institutions are not required to copy or mechanically apply the exact methodologies, weightings, or conclusions of these assessments. Each institution must tailor its risk assessment to its own business model, customer base, products, services, and geographic exposure.

Board oversight is required, but NRAs do not dictate how internal assessments must be written or approved. The key regulatory expectation is alignment, awareness, and effective risk management—not rigid adoption.

A primary objective of public sector groups in combating money laundering is to establish and enforce legal and regulatory frameworks that enable the detection, prevention, and punishment of money laundering and related financial crimes, ensuring the integrity of the financial system.

The real estate sector is recognized by FATF as vulnerable to money laundering due to the high value of transactions and the ability to integrate illicit funds into legitimate assets.

Key red flags include the use of commercial properties in ways inconsistent with the declared business purpose, which may indicate the property is being used to park or disguise illicit funds rather than generate legitimate income.

The use of complex loans or credit financing arrangements can be employed to obscure the true source of funds and create artificial legitimacy. Similarly, corporate vehicles and complex ownership structures are frequently used to conceal beneficial ownership.

Unexplained cash payments are among the most common and serious indicators of money laundering in real estate transactions, particularly when inconsistent with the buyer’s profile or local market practices.

The mere use of mortgages or agricultural land does not inherently indicate money laundering risk.

Cross-border purchases increase complexity and risk due to differing regulations and potential anonymity.

Non-financed purchases, especially in cash, can facilitate money laundering by avoiding traditional financial scrutiny.

An effective AML/CFT compliance program must include several core elements outlined in FATF recommendations and national regulations. One of these essential elements is an independent and skilled audit function.

The purpose of independent audit is to test and validate the effectiveness of AML controls, identify weaknesses, and ensure compliance with regulatory requirements. Audits must be conducted by qualified personnel who are independent from the day-to-day AML operations to maintain objectivity.

While enterprise risk management frameworks and advanced technologies such as AI can enhance AML programs, they are not mandatory foundational elements. Regulators focus on governance, oversight, and accountability rather than technology sophistication.

An independent audit function ensures continuous improvement and provides assurance to senior management and regulators that the AML program is operating effectively.

Global organizations must ensure their policies and procedures comply with local laws and regulations in each country where they operate, even when maintaining group-wide consistency. Relying solely on international or U.S. standards does not ensure compliance with all local requirements, which may be more stringent or specific.

“A global group-wide program should ensure adherence to local AML and sanctions laws and regulations in every jurisdiction in which it operates. Local adaptation of policies is essential to address jurisdiction-specific risks and legal requirements.”

(CAMS 6th Edition, International AML/CFT Standards; FATF Recommendations 18, 35; EU & US Sanctions Regulations)