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Pass Guaranteed 2026 ACAMS CCAS: Trustable Valid Dumps Certified Cryptoasset Anti-Financial Crime Specialist Examination Pdf

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ACAMS Certified Cryptoasset Anti-Financial Crime Specialist Examination Sample Questions (Q98-Q103):

NEW QUESTION # 98
In a blockchain 51% attack, what does 51% refer to?

A. Governance tokens
B. Wallets
C. Computational power required for mining
D. Exchanges

Answer: C

Explanation:
A 51% attack refers to a situation where a single miner or group controls more than 50% of the blockchain network's computational (hashing) power. This majority control allows them to manipulate the blockchain ledger by double-spending or blocking transactions.
This term is widely recognized in blockchain security contexts and is referenced in typology papers on crypto financial crime risks, including those issued by UAE authorities and FATF.
Supporting extracts:
DFSA AML thematic reviews mention the risk of manipulation and double spending in blockchains susceptible to 51% attacks.
Typology reports on cryptoasset risks highlight computational power concentration as a core vulnerability.
"51% refers to the percentage of total mining power or computational power in the network" is the standard definition across crypto AML/CFT frameworks【31.92._TFS_Typology_Paper_Eng__4.pdf; AMLCFT_Guidance_for_FIs.pdf】.
Thus, C is correct.

NEW QUESTION # 99
In cryptoasset AML programs, "ongoing monitoring" means:

A. Freezing all suspicious accounts
B. Continuous review of transactions to detect anomalies
C. Checking customer activity only when onboarding
D. Only screening customers for sanctions once

Answer: B

Explanation:
Ongoing monitoring is the continuous analysis of customer activity to detect unusual or suspicious patterns over time.

NEW QUESTION # 100
What Is the purpose of applying learning (ML) or artificial Intelligence (Al) within a compliance framework? (Select two.)

A. To focus skilled resource on higher value activity
B. To reduce the requirement for risk assessment
C. To reduce headcount
D. To enhance efficiency

Answer: A,D

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 # 101
Which type of blockchain is jointly operated by multiple pre-approved organizations?

A. Consortium
B. Hybrid
C. Public
D. Private

Answer: A

Explanation:
Consortium blockchains are semi-private networks where governance is shared among authorized participants, offering a balance between decentralization and access control.

NEW QUESTION # 102
A customer who runs a cryptoasset automated teller machine (ATM) comes into a financial institution and deposits a larger than usual amount. When asked about the deposit, the customer answers there has been broader adoption of cryptoassets in the region where the ATM is located. Which additional information about the business would indicate high risk for money laundering? (Select Two.)

A. The region is located within a high-risk jurisdiction.
B. The cryptoasset ATM supports a variety of cryptoassets.
C. The region is neighboring with a narcotic-producing jurisdiction.
D. The cryptoasset ATM was recently licensed.
E. The volume and the number of users increase.

Answer: A,C

Explanation:
Money laundering risk increases if the business operates in or near high-risk jurisdictions (D) or regions associated with narcotics production (C), as these are common sources of illicit funds.
An increase in volume and users (A) or supporting various cryptoassets (B) alone does not necessarily increase ML risk. Recent licensing (E) may indicate regulatory compliance, potentially lowering risk.

NEW QUESTION # 103
......

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