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

FIUs rely on formal cooperation mechanisms to exchange information lawfully and efficiently across borders. One of the most widely used mechanisms is a Memorandum of Understanding (MOU) between FIUs in different jurisdictions.

MOUs establish the terms, scope, confidentiality protections, and procedures for sharing financial intelligence. They enable FIUs to exchange information directly, quickly, and securely while respecting data protection and domestic legal requirements. This structure significantly reduces bureaucratic delays and supports effective cross-border investigations.

FATF and regional bodies are standard-setters and evaluators, not operational information-sharing hubs. The Wolfsberg Group is a private-sector association and does not facilitate FIU-to-FIU communication. MLATs are used primarily by law enforcement and judicial authorities for criminal proceedings and arrests—not for FIU intelligence exchange.

Therefore, MOUs are the correct and most appropriate mechanism for FIU cooperation.

The combination of frequent address changes and a recent change in the ultimate beneficial owner raises potential red flags that warrant immediate investigation. To mitigate risk, the insurance company should investigate these changes and temporarily decline any payment or withdrawal instructions until the review is complete and appropriate steps are agreed upon. This ensures both regulatory compliance and protection against potential misuse of the policy.

Specialized AML training must be relevant to the specific risks the corporate banking team faces, including legal/regulatory expectations and the ML/TF typologies applicable to their products and customer base.

Applicable AML laws and regulations (B):“Staff must be aware of the applicable AML/CFT laws and regulatory requirements relevant to their business area.”(CAMS 6th Edition, Chapter: AML Training and Awareness)

Money laundering typologies applicable to corporate loans (D):“Training should include typologies and red flags that are most relevant to the risks present in the specific business line, such as corporate lending.”(CAMS 6th Edition, AML Training for High-Risk Departments)

Incorrect Options:

A: Monetary instrument reporting is more relevant to retail/branch banking.

C: Regulatory exam best practices are for compliance teams, not business-line relationship managers.

Virtual Asset Service Providers (VASPs) are considered higher-risk customers under FATF guidance due to their exposure to anonymity, speed of transactions, and cross-border activity. When onboarding a VASP, a financial institution must conduct a thorough risk assessment to determine whether the relationship aligns with its financial crime risk appetite.

Understanding the percentage of higher-risk clients served by the VASP is critical, as it indicates the level of exposure to illicit activity and the robustness of the VASP’s own risk management practices. A high concentration of higher-risk customers may significantly increase money laundering and terrorist financing risk.

Identifying which registered institutions act on behalf of the VASP, such as wallet providers or exchange operators, is also essential. Reliance on third parties introduces additional risk and requires assessment of those entities’ regulatory status and AML controls.

Finally, knowing who the VASP’s clients are, including the proportion of foreign versus domestic customers, is a core component of geographic and customer risk analysis. Cross-border exposure often elevates risk due to differing regulatory standards.

Data privacy practices and the use of central bank digital currencies, while relevant operational considerations, are not primary determinants of AML risk appetite decisions.

A risk-based approach involves conducting a comprehensive risk assessment, applying controls that match the identified risk levels, and creating detailed customer risk profiles to focus monitoring and resources where they are most needed to mitigate financial crime risks effectively.

In a mutual evaluation, a country must demonstrate to the FATF that it has an effective framework to protect its financial system from abuse. This process assesses both technical compliance with FATF Recommendations and the effectiveness of the country's AML/CFT measures.

Public-private partnerships help develop a culture of compliance across sectors and improve the quality and quantity of data through information sharing, enhancing the collective ability to detect and prevent financial crime.

AI and machine learning in adverse media screening can reduce human error through consistent analysis, automate the detection of new versus previously reviewed information, and process multiple languages and scripts, enabling broader and more accurate coverage than human review alone.