Course Outline
Introduction to Artificial Intelligence (AI) in Financial Crime Prevention for Government
- Overview of Fraud and Anti-Money Laundering (AML) in the Digital Finance Era
- Comparison of Traditional Methods with AI-Based Approaches
- Case Studies from Mastercard, JPMorgan, and Global Financial Institutions
Machine Learning for Transaction Monitoring for Government
- Supervised Learning Techniques for Risk Scoring and Classification
- Unsupervised Learning Methods for Anomaly Detection
- Real-Time Alert Generation and Stream Processing
Graph Analytics and Network Risk Detection for Government
- Modeling Relationships Between Entities and Transactions
- Detecting Complex Fraud Schemes Using Graph AI
- Hands-On Experience with Neo4j or Similar Tools
Natural Language Processing (NLP) for AML for Government
- Text Mining in Customer Due Diligence (CDD)
- Watchlist Scanning Using Named Entity Recognition (NER)
- Prompt-Based Document Review and Suspicious Activity Reports (SARs)
Model Governance and Explainability for Government
- Building Explainable and Auditable Models
- Bias Detection and Mitigation in Fraud Detection Algorithms
- Application of Explainable AI (XAI) Techniques in Compliance Settings
Ethics, Regulation, and Model Risk for Government
- Compliance with AML and Know Your Customer (KYC) Frameworks (e.g., FATF, FinCEN, EBA)
- Ethical Considerations in Surveillance and Customer Monitoring
- Reporting Standards and Regulatory Auditability
Deployment Strategies and Future Trends for Government
- Integrating AI Models into Existing Transaction Systems
- Feedback Loops and Model Updating Mechanisms
- Future of Generative AI in Fraud Investigation and SAR Automation
Summary and Next Steps for Government
Requirements
- Knowledge of fraud risk and Anti-Money Laundering (AML) procedures for government operations
- Experience in data analysis or compliance reporting
- Basic understanding of Python or analytics platforms
Audience
- Fraud risk professionals for government agencies
- AML compliance teams for government entities
- Security managers for government departments
Testimonials (3)
The background / theory of LLMs, the exercise
Joanne Wong - IPG HK Limited
Course - Applied AI for Financial Statement Analysis & Reporting
it has opened my mind to new tool that can help me in creating automation
Alessandra Parpajola - Advanced Bionics AG
Course - Machine Learning & AI for Finance Professionals
I very much appreciated the way the trainer presented everything. I understood everything even if Finance is not my area, he made sure that every participant was on the same page, while keeping up with the time left. The exercises were placed at good intervals. Communication with the participants was always there. The material was perfect, not too much, not too little. He elaborated very well on a bit more complicated subjects so that it can be understood by everyone.