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ACAMS CCAS Exam Syllabus Topics:

TopicDetails
Topic 1
  • Cryptoasset and Blockchain: This domain targets Blockchain Analysts and Crypto Risk Managers. It focuses on understanding cryptoasset technologies, blockchain fundamentals, and their operational characteristics. Candidates learn about cryptoasset transaction flows, wallets, exchanges, smart contracts, and the challenges these present to financial crime prevention.
Topic 2
  • AML Foundations for Cryptoasset and Blockchain: This section of the exam measures skills of Anti-Money Laundering (AML) Officers and Crypto Compliance Specialists. It covers foundational knowledge of AML principles tailored to the cryptoasset and blockchain environment, introducing the regulatory landscape, typologies of financial crime, and the evolving risks associated with cryptoassets.
Topic 3
  • Risk Management Programs for Cryptoasset and Blockchain: This section measures expertise of Compliance Managers and Risk Officers in developing and implementing risk management frameworks specifically for the crypto sector. It includes procedures for assessing crypto-related financial crime risks, designing controls, monitoring compliance, and adapting to emerging threats within the cryptoasset ecosystem.

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ACAMS Certified Cryptoasset Anti-Financial Crime Specialist Examination Sample Questions (Q66-Q71):

NEW QUESTION # 66
Under FATF guidance, "unhosted wallets" are:

Answer: D

Explanation:
Unhosted wallets are self-custody wallets controlled directly by the user without third-party oversight, posing higher anonymity and AML risks.


NEW QUESTION # 67
Which metric is most relevant for assessing liquidity risk in a cryptoasset exchange?

Answer: A

Explanation:
Liquidity risk assessment focuses on the ability to execute trades without large price swings, which is reflected in order book depth and bid-ask spreads.


NEW QUESTION # 68
What Is the purpose of applying learning (ML) or artificial Intelligence (Al) within a compliance framework? (Select two.)

Answer: B,C

Explanation:
Machine learning (ML) and artificial intelligence (AI) are applied within compliance frameworks to enhance the efficiency of monitoring and detection processes and to allow skilled compliance resources to focus on higher-value activities such as complex investigations and strategic decision-making. ML/AI tools can process vast amounts of transaction data to identify suspicious patterns faster than manual processes.
They do not reduce the fundamental requirement for risk assessment (A) nor are they intended primarily to reduce headcount (C), but rather to optimize resource allocation.
AML and DFSA guidance emphasize leveraging technology to improve the effectiveness and efficiency of AML controls while maintaining robust risk management.


NEW QUESTION # 69
What is "layering" in the context of money laundering using cryptoassets?

Answer: A

Explanation:
Layering involves creating complex transaction chains to disguise the illicit origin of funds. In crypto, this may involve multiple wallet hops, cross-chain swaps, and the use of privacy-enhancing technologies.


NEW QUESTION # 70
Which scenario most likely indicates active involvement of a customer in scam activities?

Answer: A

Explanation:
Directly sending to a scam cluster is a strong indicator of active participation rather than passive exposure, triggering SAR obligations.


NEW QUESTION # 71
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