CAMS ACAMS Certified Anti-Money Laundering Specialist (CAMS7 the 7th edition) Free Practice Exam Questions (2026 Updated)

Large individual cash transactions pose the highest money laundering risk for money services businesses. Cash is difficult to trace and, when handled in significant amounts, can be used to introduce illicit funds into the financial system with minimal transparency.

Many jurisdictions lack robust sanctions frameworks, requiring international cooperation and education to improve compliance.

Option B (Correct):Educational initiatives such as AML/sanctions training and workshops help raise awareness and build capacity.

Option D (Correct):Bilateral cooperation allows knowledge-sharing and technical assistance between regulatory authorities.

Why Other Options Are Incorrect:

Option A (Incorrect):Trade restrictions may pressure non-compliant nations, but they do not directly improve sanctions awareness.

Option C (Incorrect):Enforcing fines without prior education or assistance is ineffective and may create diplomatic tensions.

Best Practices for Sanctions Awareness & Compliance:

Develop international AML/sanctions training programs for emerging markets.

Encourage diplomatic engagement to strengthen legal frameworks.

Leverage FATF’s Mutual Evaluation process to assess progress.

According to FATF Recommendations, reporting entities are strictly prohibited from disclosing to clients or third parties that a suspicious activity report (SAR) has been filed or that an investigation is ongoing. This prohibition, known as "tipping off," is designed to preserve the integrity of investigations and prevent suspects from taking evasive actions.

Scenario-based systems use algorithms to detect suspicious behaviors, such as transactions occurring at unusual times, those exceeding specified thresholds, or those taking place in locations inconsistent with a customer's typical activity. These anomalies help identify potential financial crime risks.

Artificial intelligence (AI) enhances transaction monitoring by complementing or improving upon traditional rules-based systems. Regulators recognize that AI can strengthen AML programs when deployed with appropriate governance and oversight.

One key benefit is the ability to identify changes in customer behavior over time. AI models analyze historical and real-time data to detect deviations from expected patterns, allowing institutions to reassess customer risk more dynamically and accurately.

AI can also generate predictive customer risk scores, helping institutions prioritize alerts and focus investigative resources on higher-risk customers and activities. This improves efficiency and effectiveness while supporting a risk-based approach.

AI is designed to reduce false positives, not increase them, and bias must be carefully managed during training through governance and data controls.

Hawala operatives rely on informal networks outside the regulated banking system, allowing funds to move across borders without the usual AML controls.

Because hawala transactions are settled on trust rather than recorded through formal channels, it’s often impossible to trace who originated or ultimately received the funds.

The Bank Secrecy Act (BSA) is the foundational Anti-Money Laundering (AML) and Counter-Terrorist Financing (CFT) law in the United States. Enacted in 1970, the BSA requires financial institutions to establish and maintain effective AML programs designed to detect and prevent money laundering and terrorist financing.

Under the BSA and its implementing regulations, financial institutions must implement key controls such as Customer Identification Programs (CIP), customer due diligence (CDD), enhanced due diligence (EDD) for higher-risk customers, transaction monitoring, record-keeping, and the filing of Suspicious Activity Reports (SARs) and Currency Transaction Reports (CTRs) with FinCEN.

While the USA PATRIOT Act expanded AML obligations—particularly in relation to terrorist financing—it amended and strengthened the BSA rather than replacing it. The Money Laundering Control Act criminalized money laundering activities but does not establish the operational compliance framework. MiCA is an EU regulation and does not apply in the U.S.

Therefore, the BSA remains the cornerstone of U.S. AML/CFT compliance requirements.

Countries that are members of the Egmont Group can securely exchange information between their Financial Intelligence Units (FIUs) to support money laundering and terrorist financing investigations, even when the activity involves multiple jurisdictions.

A core requirement of applying a risk-based approach (RBA) in customer due diligence for legal entity clients is the identification and verification of beneficial ownership. FATF standards require financial institutions to take reasonable measures to identify and verify the identity of the natural persons who ultimately own or control a legal entity.

Understanding beneficial ownership is critical because complex corporate structures can be misused to conceal illicit ownership, launder money, or evade sanctions. The depth of verification required depends on the assessed risk level of the customer, with higher-risk entities requiring enhanced due diligence.

Information such as market competition or profitability is not relevant to AML/CFT risk assessment. While open-source information may support due diligence, relying solely on internet or social media sources is insufficient and inconsistent with regulatory expectations.

Therefore, verifying beneficial ownership is the most essential and regulator-mandated CDD measure under a risk-based approach.

Virtual Asset Service Providers (VASPs) are considered higher-risk customers due to their exposure to anonymity, speed, and cross-border transactions. FATF guidance highlights several red flags indicative of potential money laundering activity.

The use of shell companies to move funds into and out of a VASP is a strong indicator of attempts to conceal beneficial ownership and obscure transaction flows. Similarly, frequent use of mixers and tumblers is a well-recognized technique used to break transaction trails and hinder blockchain tracing.

Receiving funds from jurisdictions with weak AML frameworks significantly increases geographic risk, particularly when combined with other red flags.

By contrast, peer-to-peer infrastructure use and market volatility are inherent features of the virtual asset ecosystem and do not, on their own, indicate money laundering.

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.

Open-source intelligence (OSINT) is widely used in AML/CFT investigations to support customer due diligence, adverse media screening, and financial crime analysis. However, because OSINT sources vary widely in quality and reliability, regulators and investigative best practices emphasize verification and corroboration.

The most effective way to ensure the reliability of open-source information is cross-checking information across multiple independent sources. Corroboration helps confirm accuracy, reduce the risk of misinformation, and identify inconsistencies or bias. This approach is especially important when using online media, public records, blogs, or social media content.

Excluding entire categories of sources—such as the dark web or social media—may result in missed intelligence and does not ensure reliability. Similarly, relying only on international news agencies limits coverage and may overlook relevant local or niche reporting.

Therefore, triangulation through multiple sources is the most effective and regulator-aligned method for validating OSINT.

Understanding the source and origin of assets (C):According to the CAMS 6th Edition (Chapter: Customer Due Diligence and Enhanced Due Diligence) and the EU 4th & 5th AML Directives, regulated entities are required to take adequate measures to understand the source of funds and the origin of assets of their customers, especially when there are higher risk factors such as large transactions or PEPs.“Firms must identify the source and origin of assets to ensure they are not the proceeds of crime or corruption, particularly for higher-risk customers.”(CAMS 6th Edition, CDD/EDD Requirements; EU Directive 2015/849, Article 20)

Performing negative news checks of prospective customers (D):Adverse media screening is an essential part of the onboarding process for identifying potential risks related to money laundering, terrorist financing, or reputational harm.“Negative news or adverse media checks form a vital component of the due diligence process, helping organizations detect links to criminal or suspicious activities.”(CAMS 6th Edition, CDD/EDD Requirements)

Incorrect Options:

A: Onboarding interviews may be part of EDD, but are not a standard or required AML control.

B: PEPs are not to be automatically rejected; instead, enhanced due diligence should be applied.

E: Producing financial stability reports is not an AML control, but may be relevant for credit or investment assessment.