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Course Outline
Introduction to AI in Financial Crime Prevention
- Landscape of fraud and AML in the era of digital finance
- Contrasting traditional methods with AI-driven solutions
- Real-world case studies from Mastercard, JPMorgan, and other global banking entities
Machine Learning for Transaction Surveillance
- Applying supervised learning for risk scoring and categorization
- Employing unsupervised learning to identify anomalies
- Generating real-time alerts through stream processing
Graph Analytics and Network Risk Identification
- Mapping connections between entities and their transactions
- Identifying intricate fraud schemes via graph AI
- Practical exercises using Neo4j or comparable platforms
Natural Language Processing in AML
- Conducting text mining for Customer Due Diligence (CDD)
- Performing watchlist scans using Named Entity Recognition (NER)
- Reviewing documents and drafting Suspicious Activity Reports (SARs) using prompt-based techniques
Model Governance and Interpretability
- Constructing models that are both explainable and subject to audit
- Identifying and mitigating bias within fraud detection algorithms
- Applying XAI techniques within compliance frameworks
Ethics, Regulation, and Model Risk Management
- Ensuring adherence to AML and KYC frameworks (such as FATF, FinCEN, EBA)
- Navigating AI ethics in customer surveillance and monitoring
- Meeting reporting standards and maintaining regulatory auditability
Deployment Strategies and Emerging Trends
- Embedding AI models into current transaction systems
- Establishing feedback loops and mechanisms for model updates
- The role of generative AI in future fraud investigations and SAR automation
Conclusion and Future Directions
Requirements
- A solid grasp of fraud risks and AML procedures
- Practical experience in data analysis or compliance reporting
- Foundational knowledge of Python or standard analytics platforms
Target Audience
- Professionals specializing in fraud risk management
- Teams responsible for AML compliance
- Security managers
14 Hours
Testimonials (1)
i already have some reports that i know, i will use some of the prompts that looked at today
