Thematic Review of Sanctions Screening Systems (2026-03-16)

Circulars Email: HKMA E-mail Alert of 17 March 2026 (05:00 p.m. HKT)

Document Information

Title: Thematic Review of Sanctions Screening Systems (2026-03-16)

Type: Circulars

URL: https://brdr.hkma.gov.hk/eng/doc-ldg/current/20260316-1-EN

Email Received: 2026-03-17 19:49

Summary Created: 2026-03-17 13:00

English Summary (6893 chars)
Quick section switch
Management Summary
  • Purpose / Background:
    This circular shares the Hong Kong Monetary Authority's (HKMA) observations from a thematic review of Authorized Institutions' (AIs) sanctions screening systems, assessing their effectiveness in meeting statutory obligations under Hong Kong's sanctions regime and related guidance.
  • One-line conclusion (what changed / what needs to be done):
    The review found AIs' sanctions screening systems generally effective, but recommends considering independent testing and reviewing existing controls to enhance sanctions risk management.
  • Key Changes (3-8 bullets):
  • General confirmation of AI sanctions screening systems meeting expectations and operating within industry benchmarks.
  • Observation of good practices and areas for improvement in governance, system testing, list management, and AI adoption.
  • Recommendation for AIs to consider engaging independent parties for sanctions screening system testing to provide assurance on robustness.
  • Emphasis on prompt implementation of remedial actions identified through system testing.
  • Reminder of the importance of timely, complete, and accurate sanctions list updates.
  • Encouragement for AIs and SVF licensees to review existing controls and consider adopting identified best practices.
  • Key Dates / Deadlines:
    N/A (This is a summary of observations and recommendations, not a directive with specific deadlines).
  • Applicability / Impact scope:
    All Authorized Institutions (AIs) and Stored Value Facility (SVF) Licensees.
  • Recommended management actions (3-7 actionable bullets):
  • Review the HKMA's observations on sanctions screening systems and assess alignment with current practices.
  • Consider engaging independent third-party experts to conduct periodic testing of sanctions screening systems.
  • Ensure prompt remediation of any identified deficiencies or system performance issues arising from testing.
  • Regularly review and update sanctions lists from reliable sources to ensure timeliness, completeness, and accuracy.
  • Evaluate the potential adoption of technologies like Artificial Intelligence to optimize sanctions screening processes.
  • Conduct a gap analysis of existing sanctions risk controls and consider implementing recommended best practices.
Detailed Summary
  1. Document overview (nature, purpose, scope)
    This circular from the HKMA summarizes observations from a thematic review of Authorized Institutions' (AIs) sanctions screening systems. The purpose is to assess the effectiveness of these systems in meeting statutory obligations under the Hong Kong sanctions regime and related guidance, as outlined in Chapter 6 of the Guideline on Anti-Money Laundering and Counter-Financing of Terrorism. The observations are also relevant to Stored Value Facility (SVF) licensees.
  1. Main requirements (group by topic; state what must be done)
  • Governance and Oversight: AIs should demonstrate a clear understanding of their sanctions risks and obligations, including monitoring geopolitical developments and associated risks relevant to their customer base, geographic regions, products, services, and counterparties. For correspondent banking relationships, AIs must ensure visibility of customer activities. System performance data should be reported regularly to senior management.
  • System Testing and Validation: AIs are required to implement regular testing of sanctions screening systems to ensure they are explainable, effective, efficient, and commensurate with assessed risk. Testing frequency should align with risk and be approved by senior management, typically conducted at least annually, or more frequently if system updates, deficiencies, performance issues, or risk profile changes occur.
  • Sanctions List Management: AIs must ensure timely, complete, and accurate updates to their sanctions lists, subscribing to commercial databases or relying on head office provisions. Mechanisms should be in place for frequent checks to incorporate the latest designations.
  • Adoption of Artificial Intelligence: AIs are encouraged to review their existing sanctions risk controls and consider adopting practices that optimize screening processes, including the use of AI for automated false positive alert closure, provided explainable logic and risk-mitigating controls are in place.
  1. Key changes (vs previous requirements)
    This circular does not introduce new formal requirements but shares observations and recommendations based on a recent thematic review, building upon existing guidance. The key emphasis is on considering independent testing and reviewing existing controls to enhance the sanctions risk management framework.
  1. Important dates & transition
    N/A. This circular shares observations and recommendations and does not set specific deadlines for implementation.
  1. Impact and risks (operations/compliance/IT/data/reporting)
  • Operational Impact: AIs may need to adjust their testing methodologies, potentially engaging external vendors, and refine their processes for implementing remedial actions. Adoption of new technologies like AI might require IT system changes and staff training.
  • Compliance Risk: Failure to enhance sanctions screening systems based on the HKMA’s observations could lead to increased compliance risk and potential regulatory scrutiny.
  • IT/Data: Implementing AI or improving system configurations may require IT infrastructure upgrades and robust data management for testing and validation.
  1. Compliance action checklist (practical steps)
  2. Review HKMA Observations: Conduct an internal review of the observations shared in this circular.
  3. Assess Current Practices: Compare current sanctions screening system governance, testing, list management, and technology adoption against HKMA observations and industry best practices.
  4. Consider Independent Testing: Evaluate the benefits and feasibility of engaging independent third parties for sanctions screening system testing.
  5. Review Testing Frequency: Ensure the frequency of system testing is risk-based and approved by senior management.
  6. Strengthen List Management: Verify mechanisms for timely, complete, and accurate sanctions list updates.
  7. Evaluate AI Adoption: Explore the potential benefits of using AI and other technologies to enhance sanctions screening efficiency and effectiveness.
  8. Perform Gap Analysis: Conduct a comprehensive gap analysis of existing sanctions risk controls and develop an action plan for enhancement.
  9. Prepare for Reporting: Ensure system testing results are available and can be promptly provided to the HKMA upon request, demonstrating system effectiveness and efficiency.
  1. Appendices/attachments summary (if any; 1-3 sentences each; total <= 20%)
    There are no appendices or attachments referenced in the provided document content.
中文摘要 (3356 chars)
快速切換摘要區塊
管理層摘要

目的/背景:
香港金融管理局(HKMA)就其近期對認可機構(AIs)的制裁篩查系統進行的專題審查,分享審查結果與觀察。旨在評估AIs在香港制裁制度下履行法定職責的有效性。

一句話結論(文件要你做什麼/改了什麼):
HKMA建議認可機構(AIs)和存款貨幣機構(SVF) licensees審視現有的制裁風險控制,考慮採納文件中的良好實踐,以加強制裁風險管理。

關鍵變更(3-8點):

  • AIs的制裁篩查系統普遍符合預期,運作在行業基準內,但觀察到了一些可改進之處。
  • 強調了監管機構對系統設置、性能、持續調整和測試的期望。
  • 建議AIs考慮聘請獨立第三方進行系統測試,以提供系統穩健性的保證。
  • 系統測試的頻率應與風險掛鉤,並經高級管理層批准,建議至少每年一次。
  • 強調及時、完整和準確的制裁名單更新的重要性。
  • 鼓勵採用人工智能等技術優化篩查流程,包括自動化處理誤報,並確保相關邏輯清晰透明,風險可控。
  • 要求AIs和SVF licensees審查現有風險控制,進行差距分析,並考慮採納建議以加強制裁風險管理。
  • HKMA將可要求AIs和SVF licensees提供制裁篩查系統測試結果,以證明其有效性和效率。

重要日期 / 截止日:
本文件發佈日期為 2026 年 3 月 16 日。文件中未包含具體的執行截止日期,但要求審視現有系統並考慮採納建議。

適用對象 / 影響範圍:

  • 所有認可機構 (AIs)。
  • 所有存款貨幣機構 (SVF) licensees。

管理層建議行動(3-7點,務必可執行):

  1. 審查與差距分析: 立即審查現有的制裁篩查系統的設置、性能和測試流程,與本函提出的觀察結果進行差距分析。
  2. 加強測試機制: 評估現有系統測試的頻率、獨立性和方法,考慮聘請獨立第三方進行專業評估,以增強數據的可靠性和監管的認可度。
  3. 優化名單管理: 確保制裁名單的更新機制能及時、準確地納入最新的制裁指定,特別是與香港制裁制度相關的聯合國安理會決議。
  4. 技術採用評估: 探索並評估人工智能及其他新興技術在優化制裁篩查流程(如誤報處理)的潛力,確保技術應用符合監管要求和風險管理原則。
  5. 高級管理層報告: 確保系統性能數據和測試結果能定期、有效地匯報給高級管理層,以支持決策和資源分配。
  6. 風險應對與改進: 根據測試結果和風險評估,及時實施必要的系統配置、算法調整及其他補救措施,以持續提升系統的有效性。
詳細摘要

1) 文檔概述(性質、目的、適用範圍)

  • 性質: 香港金融管理局(HKMA)發佈的通函。
  • 目的: 分享HKMA近期對認可機構(AIs)制裁篩查系統進行的專題審查結果和觀察,旨在評估AIs在香港制裁制度下的法定職責履行情況,並提供改進建議。
  • 適用範圍: 所有認可機構(AIs)和存款貨幣機構(SVF) licensees。

2) 主要要求(按主題分組,說清楚「要做什麼」)

  • 制裁風險管理與治理:
  • AIs須清晰理解其在香港及其他司法管轄區的制裁風險及義務。
  • 需密切監察地緣政治發展及相關制裁風險,並考慮客戶、地理區域、產品服務和交易對手的性質。
  • 從事代理銀行業務的AIs須特別注意風險敞口及客戶活動的可視性。
  • 定期向高級管理層匯報系統績效數據,以制定行動及資源分配。
  • 系統測試與驗證:
  • AIs須實施例行性系統測試,以證明其制裁控制的解釋性、有效性和效率,並與評估風險相稱。
  • HKMA建議AIs考慮聘請獨立第三方進行系統測試,以提供系統穩健性的保證。
  • 測試的獨立性和專業性至關重要,無論內部或外部執行。
  • 測試結果應能加強系統維護、優化、報告和質量保證,並基於風險敞口評估變更的適當性。
  • 應及時對測試建議的補救措施(特別是系統配置和算法)採取行動。
  • 測試後績效數據須及時報告給高級管理層。
  • 測試頻率須與風險相符,並經高級管理層批准,建議至少每年一次,並在系統重大更新、發現缺陷或風險概況改變時增加頻率。
  • 制裁名單管理:
  • AIs須確保制裁名單的更新及時、完整和準確。
  • 機制須確保最新指定信息能被及時納入內部數據庫。
  • 技術採用:
  • 鼓勵AIs和SVF licensees審視現有制裁風險控制,進行差距分析。
  • 考慮採納文中提出的良好實踐,以加強制裁風險管理框架。
  • 考慮採用人工智能等技術優化篩查流程,包括自動化處理誤報,確保邏輯清晰透明,並具備風險緩釋控制。

3) 關鍵變更(對比既有要求/舊政策)
本文件總結了HKMA對AIs制裁篩查系統的專題審查結果,並未引入全新的強制性監管要求,而是基於現有法規(如《反洗錢及反恐怖融資指引》第6章)提出觀察和建議。其主要價值在於:

  • 明確實踐期望: 文件詳細闡述了HKMA對制裁篩查系統在治理、測試、名單管理和技術採用方面的具體期望和良好實踐。
  • 強調獨立測試: 強烈建議AIs考慮聘請獨立第三方進行系統測試,這可能比以往更強調外部驗證的必要性。
  • 推動技術應用: 鼓勵並肯定AIs採用人工智能等新技術優化篩查流程,為技術創新設定了監管導向。
  • 提供審查視角: 通過分享實際審查結果,幫助AIs了解自身在行業中的表現,以及HKMA關注的重點領域。

4) 重要日期與過渡安排(含實施/生效/截止)

  • 發佈日期: 2026 年 3 月 16 日。
  • 過渡安排: 文件未明確列出具體的執行截止日期,但要求AIs和SVF licensees「審查」和「考慮採納」,暗示這是一項持續性的改進任務。

5) 對機構的影響與風險(營運/合規/IT/資料/報告)

  • 合規風險: 未能及時採納建議可能導致系統有效性不足,進而面臨違反制裁規定的合規風險。
  • 營運影響: 引入獨立測試、優化流程、採用新技術可能需要額外資源(人力、財力、時間)。
  • IT影響: 評估和實施技術方案(如AI)需要IT部門的配合,可能涉及系統升級或整合。
  • 報告要求: 可能需要調整現有的內部報告機制,以更有效地匯報系統績效和測試結果給高級管理層。
  • 資料管理: 確保制裁名單的準確性和及時性,以及測試數據的完整性,對資料管理提出更高要求。

6) 合規動作清單(checklist)

  • [ ] 審查現有制裁篩查系統的治理結構和風險理解。
  • [ ] 評估客戶、地理區域、產品服務和交易對手相關的制裁風險。
  • [ ] 確保向高級管理層的定期報告機制有效。
  • [ ] 檢視現有的系統測試政策和程序。
  • [ ] 評估聘請獨立第三方進行系統測試的可行性和效益。
  • [ ] 驗證系統測試的獨立性和測試方的專業性。
  • [ ] 確保測試結果能有效用於系統維護、優化和風險管理。
  • [ ] 建立及時處理測試建議補救措施的流程。
  • [ ] 評估制裁名單的更新機制,確保時效性、完整性和準確性。
  • [ ] 進行制裁風險控制的差距分析。
  • [ ] 探索並評估人工智能等技術在制裁篩查中的應用潛力。
  • [ ] 準備在HKMA要求時提供制裁篩查系統測試結果。

7) 附件/附錄摘要(如有;每項 1-3 句;總量 <= 20%)
本文件並未包含獨立的附件或附錄。其內容直接體現於通函的正文中。