Free Practice Questions for ACAMS CAMS Exam

A, C, D:

“Trust and asset management services can facilitate the concealment of the source of funds (A), provide a layer of anonymity to transactions (C), and obscure the true legal and beneficial owners (D). These are well-established ML/TF risks in the private wealth sector.”(CAMS 6th Edition, ML/TF Risks in Trust and Asset Management)

B and E are normal aspects of asset management and are not in themselves ML/TF risks unless combined with other suspicious behaviors.

In the context ofgambling and gaming sectors, a well-known money laundering typology is the use of platforms tointroduce illicit funds and withdraw them as "winnings". When a customerdeposits large cash amounts and quickly withdraws themwithout engaging in actual gambling, it indicates"placement and layering"techniques.

This behavior is indicative of attempts todisguise the origin of illicit funds, converting them into legitimate-looking financial flows. It is considered a classic red flag in AML programs related to casinos and online gaming.

A risk-based approach prioritizes allocating more resources to higher-risk areas and regularly reassessing risks to ensure resource allocation remains aligned with evolving threats and vulnerabilities. This maximizes the effectiveness of the AFC program.

The United Nations Security Council (UNSC) is authorized under the UN Charter to imposebinding sanctions measureson member states. These sanctions may target countries, entities, or individuals and can include arms embargoes, travel bans, asset freezes, and restrictions on trade or financial services.

Statement Ais correct:

Circumventing or evading UNSC sanctionsmay constitute a criminal offenseif the jurisdiction has incorporated UN obligations into domestic law. While the UNSC does not directly impose criminal penalties,member states must implement these measures locally, andmany jurisdictions have lawsthat make such violations criminal acts.

Statement Bis incorrect:

The UNSC is empowered toimpose broad restrictions, includingtrade bans beyond arms, such as on luxury goods, fuel, or specific commodities. Therefore, the idea that it cannot prohibit exports beyond arms is inaccurate.

Statement Cis correct:

Member countries of the United Nations are expected to implement and enforce UNSC sanctions, in accordance with their obligations under the UN Charter (specifically Chapter VII). Countries are responsible for transposing these sanctions into their national legal frameworks.

Statement Dis incorrect:

Although member countries are required to enforce sanctions,not all countries automatically consider breaches a criminal offense. Whether a violation is criminal depends on how each country enacts UN sanctions domestically.

An effective name screening process is a critical component of sanctions and AML compliance. Regulators expect financial institutions to implement strong governance, risk-based design, and ongoing validation.

Clearly defining the screening scope, frequency, and alert adjudication procedures in policies ensures consistency, transparency, and accountability across the organization.

Conducting a risk assessment allows institutions to make informed, proportionate decisions on which data attributes to screen (e.g., names, aliases, addresses), how frequently to screen, and which databases to use. This aligns with the risk-based approach.

Regular testing and validation ensure that screening systems continue to perform as intended, detect true matches, and minimize false positives or missed hits.

Selecting the most popular database or assigning a single individual for control ownership does not ensure effectiveness and may introduce governance risk.

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.

Modern KYC solutions help reduce identity theft, provide reliable customer authentication to build trust, and shorten authentication times, enhancing both security and efficiency in customer onboarding and ongoing due diligence processes.