世界银行-第一代洗钱和资助恐怖主义风险评估的经验教训（英）-2023-76页_3mb

Key Findings & Recommendations from the World Bank Report on National Money Laundering/Terrorist Financing Risk Assessments

1. Global State of Risk-Based Approach

• Major Deficiencies: 44% of jurisdictions lack deep understanding of money laundering (ML) and terrorist financing (TF) risks, directly affecting their effectiveness ratings (IO1).
• Policy Implementation: 47% of countries lack risk-based policies despite technical compliance in other areas.
• Data Challenges: 66% of jurisdictions face data and statistical issues, hindering accurate risk assessments.

2. Best Practices for High-Quality NRAs

• Leadership & Collaboration: Appoint a strong leader, empower assessors, and foster inter-agency and public-private collaboration.
• Holistic Approach: Avoid myopia by balancing qualitative/quantitative data, address systemic risks, and engage academia.
• Data-Driven Insights: Invest in data collection, statistics, and specialized tools (e.g., the World Bank’s Proceeds of Crime Data Collection Tool).
• Feedback Integration: Conduct anonymous perception surveys, incorporate external reviews, and leverage post-NRA stakeholder feedback.

3. Transition to Risk-Based Approach

• Actionable Outcomes: Turn risk assessment results into practical policies, strategies, and resource allocation.
• Cultural Shift: Establish permanent risk-based units within financial intelligence units (FIUs) or competent authorities.
• Communication Efficiency: Share results via sector-specific briefs instead of lengthy reports to enhance clarity and impact.

4. Future Directions

• Targeted Technical Assistance: Focus on high-priority areas like legal persons (LPs), virtual assets (VASPs), and data-based research.
• International Collaboration: Support academic studies, data sharing, and guidance on exemptions/simplifications (Recommendation 33).
• Resources & Capacity Building: Continuously invest in human capital and data infrastructure for sustained risk assessment effectiveness.

Conclusion:
The global implementation of the risk-based approach remains uneven. Addressing capacity constraints, enhancing data availability, and fostering a robust institutional culture are critical to improving ML/TF risk management and aligning with FATF standards.