引导式测验 · 中等 等级

人工智能反洗钱测验

回顾人工智能如何支持反洗钱工作中的交易监控、客户风险评估、图形分析和人工审核。

相关引导路径人工智能反洗钱
问题 1 的 8

What operational issue can rule-based transaction-monitoring systems create?

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  1. What operational issue can rule-based transaction-monitoring systems create?
    • They can produce false-positive alerts that require investigator review
    • They establish criminal intent from a transaction amount alone
    • They eliminate all review of customer activity
    • They automatically prove whether funds are illicit
  2. What does “structuring” mean under U.S. Bank Secrecy Act guidance?
    • Splitting one account into multiple dashboards for convenience
    • Breaking up transactions for the purpose of evading reporting or recordkeeping requirements
    • Moving a transaction between currencies for an exchange rate
    • Combining several payments for routine bookkeeping
  3. 为什么图神经网络在 AML 中特别有用？
    • 他们将交易文本翻译成其他语言
    • 它们降低了存储交易数据的成本
    • 他们将账户和转账建模为网络，揭示了协调活动的隐藏环
    • 他们自动加密所有客户通信
  4. What is customer due diligence (CDD) information used for in risk-based AML monitoring?
    • Automatically proving that a customer committed a crime
    • Replacing all transaction monitoring
    • Setting a universal threshold for every institution
    • Developing a customer risk profile and assessing activity in context
  5. 为什么标记训练数据对监督 AML 模型来说是一个挑战？
    • 与正常交易相比，确认的洗钱案件很少见
    • 银行拒绝使用任何历史数据
    • 标签每天都会自动更改
    • 监管机构禁止存储任何交易记录
  6. Why should an AML alert include an interpretable rationale for an investigator?
    • It makes the alert a final legal finding
    • It helps the investigator review the activity and document why it may be suspicious
    • It removes the need to examine transaction context
    • It guarantees that every alert is true
  7. What can entity resolution do in an AML data pipeline?
    • Determine a customer’s guilt without an investigation
    • Change the legal reporting threshold
    • Link records that may refer to the same person or organization across datasets
    • Replace transaction records with generated text
  8. How should an investigator interpret an AI-generated transaction risk score?
    • As proof of money laundering
    • As an automatic SAR filing decision
    • As a replacement for the institution’s AML program
    • As a prioritization signal that requires review of supporting activity and context