This course equips private banking practitioners with a structured, risk-proportionate approach to Source of Wealth (SoW) due diligence. Drawing directly on the $3 billion money laundering case in Singapore and anchored in MAS/FATF expectations and ACIP best practice guidance, participants will develop the skills to build robust KYC profiles, conduct plausibility assessments, validate documents, and apply AI-assisted tools to improve the efficiency and consistency of the onboarding and ongoing review process.

Assistant Relationship Manager, Relationship Manager, Team Leader

By the end of the session, participants will be able to:

• Explain the regulatory and reputational significance of establishing legitimacy of wealth
• Analyse the $3 billion ML case to identify lapses, red flags, and system gaps
• Apply the guiding principles of SoW due diligence: Materiality, Prudence, and Relevance
• Construct a comprehensive SoW profile across employment, business ownership, investment, and gift/inheritance wealth categories
• Perform plausibility assessments using benchmarking, corroborative evidence, and document validation techniques
• Identify early warning signs and red flags in account conduct and transaction monitoring
• Apply a risk-proportionate approach to SoW due diligence based on wealth risk factors
• Leverage AI tools to assist with benchmarking, consistency checks, and SoW enrichment
• Apply learnings to realistic onboarding and ongoing review case studies

Module 1: Introduction & Discussion

• Why legitimacy of wealth matters — regulatory and reputational stakes
• Key SoW challenges: information gaps, subjectivity, turnaround times
• The $3B ML case: how perpetrators exploited system gaps, asset classes used, non-bank gatekeepers, Golden Passport risks, and lessons learnt

Module 2: SOW Due Diligence

• Guiding principles: Materiality, Prudence, Relevance
• Understanding the wealth journey: Employment, Business Ownership, Investments, Gift/Inheritance — information gathering, corroboration, and NW estimation
• Validation and plausibility: like-to-like benchmarking, red flag identification, escalation triggers
• Document validation: format checks, tampering indicators, issuer verification, accounting reasonableness
• Good practices: smell test, early warnings, account conduct monitoring
• Risk-proportionate approach: wealth risk factors, adjusted scrutiny criteria
• Roles and responsibilities: RM, AI co-pilot, KYC/Compliance, Management

Module 3: Application

• Onboarding: pre-meeting preparation, KYC template population, name screening, AI-assisted enrichment
• Ongoing review: transaction review triggers, profile updates, AI-assisted monitoring
• AI-assisted SoW DD: building and refining prompts, practical use cases, validation of outputs
• Case studies: The Tans (retirees, trust setup) and Mr P (China business owner)

Appendix - AI Prompt Strategy Reference

• Step-by-step guide with sample prompts and illustrated outputs

Assessment - MCQ

Our trainer is an experienced senior banking leader with a strong background in risk management, compliance, client onboarding, and financial crime prevention at top-tier institutions. With professional qualifications and certifications, and extensive expertise in AML/KYC, Source of Wealth due diligence, and regulatory compliance, she delivers practical, engaging, and learner-focused training programs that bridge complex regulatory concepts with real-world banking practices, helping professionals succeed across multiple markets.