2026年最新の実際のCAMS7日本語問題集最新ACAMS練習テスト問題集ゲット [Q76-Q90]

グローバル組織は、複数の管轄区域にわたるリスクを効果的に管理するために、グループ ポリシーが各国の特定の AML および制裁規制に準拠していることを確認する必要があります。

Jurisdictions with high corruption, limited regulatory oversight, and weak AML enforcement present elevated money laundering risks. Criminal organizations often exploit such environments to conceal illicit funds. Geographic risk assessments should consider sanctions exposure, corruption indices, terrorism concerns, and international AML compliance evaluations.

Technology plays a critical role in strengthening AML/CFT programs by improving efficiency, consistency, and scalability. Regulators encourage the responsible use of technology while maintaining governance and oversight.
One major benefit is processing large volumes of data efficiently, helping institutions eliminate investigative backlogs and manage increasing transaction volumes. Technology also automates repetitive tasks, reducing human error and improving data accuracy, allowing compliance professionals to focus on higher-value investigative work.
Technology does not eliminate privacy concerns, and front-end search tools alone are not sufficient to drive effectiveness. Human oversight remains essential for decision-making, investigations, and regulatory reporting.

Dormant accounts becoming suddenly active may indicate account compromise, mule activity, or money laundering. Investigators should review historical activity, customer information, login patterns, and transaction details to determine whether the activity is legitimate or requires escalation and reporting.

Policies, controls, and procedures must be proportionate to the size and nature of the firm, approved by senior management, and regularly reviewed to ensure they remain effective in preventing and mitigating financial crime risk while aligning with regulatory expectations.

The finance industry is inherently vulnerable to money laundering risks due to the nature, scale, and complexity of its operations. FATF and global regulators consistently identify several structural characteristics that increase exposure to illicit financial activity.
One major vulnerability is the availability of complex financial products and services, such as derivatives, correspondent banking, and structured investments. These products can be misused to disguise the origin of funds through layering and complex transaction chains.
Another key risk arises from engagement with high-risk jurisdictions. Financial institutions often operate across borders, including in countries with weak AML controls or limited regulatory oversight, increasing exposure to money laundering and terrorist financing risks.
Additionally, high transaction volumes present a significant challenge. The sheer scale and speed of transactions make it difficult to detect suspicious activity, particularly when illicit transactions are deliberately structured to blend in with legitimate activity.
In contrast, heightened regulatory obligations and investments in technology are risk-mitigating factors, not vulnerabilities. They are designed to reduce exposure to financial crime rather than increase it.

Real estate transactions are vulnerable to ML/TF risks, particularly when there is limited transparency or unusual payment methods:
Cross-border purchases (A):”Purchases by foreign buyers, especially from high-risk jurisdictions, are a red flag for money laundering in the real estate sector.”(CAMS 6th Edition, Real Estate Money Laundering Risks; FATF, Money Laundering and Terrorist Financing through the Real Estate Sector, 2007) Non-financed purchases (D):”Non-financed (all-cash) purchases can indicate the introduction of illicit funds into the financial system, bypassing the controls of mortgage lenders.”(CAMS 6th Edition, Real Estate ML
/TF Risks)
Incorrect Options:
B: Purchasing in the name of a natural person is standard and not inherently risky.
C: Paying the true market price does not raise ML/TF risk.
References:
CAMS 6th Edition, Chapter: ML/TF Risks in Real Estate
FATF, Money Laundering and Terrorist Financing through the Real Estate Sector (2007)

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.

A: “Effective training includes practical examples and use cases tailored to the business.” B: “Firms must keep accurate records of all AML/CFT training, including completion logs.” D: “Staff should be aware of the consequences of non-compliance with AML/CFT obligations.”(CAMS 6th Edition, AML/CFT Training and Awareness) Incorrect:
C: Training should be tailored and role-specific.
E: Third-party trainers are not required for effective training.
References:
CAMS 6th Edition, Training and Awareness Programs

The susceptibility of a company or jurisdiction to ML/TF abuse is significantly increased by:
Permissibility of bearer shares (B):”Bearer shares make it easy to hide ownership and control, presenting a major risk for misuse by criminals.” Rules governing the disclosure of beneficial ownership by the jurisdiction (C):”Weak requirements or loopholes in beneficial ownership disclosure are frequently exploited to conceal criminal involvement in corporate structures.”

パーペチュアルKYC（pKYC）は、静的な変化や行動異常といったデータトリガーをリアルタイムで監視し、固定の更新スケジュールではなく顧客固有のデータに基づいて優先順位付けを行います。この動的なアプローチは、顧客のリスクプロファイルの変化に迅速に対応することで、リスク管理を強化します。