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Course Outline
Foundamentals of AI in Financial Crime Prevention
- Landscape of fraud and AML in the age of digital finance
- Comparing conventional methods with AI-driven solutions
- Real-world case studies from Mastercard, JPMorgan, and international banking institutions
Applying Machine Learning to Transaction Surveillance
- Using supervised learning for risk assessment and categorization
- Employing unsupervised learning to spot anomalous activities
- Generating real-time alerts and managing data streams
Graph Analytics for Identifying Network Risks
- Mapping connections between entities and financial transactions
- Uncovering intricate fraud schemes through graph AI capabilities
- Practical sessions with Neo4j or comparable graph databases
Leveraging NLP for AML Enhancements
- Applying text mining techniques to Customer Due Diligence (CDD)
- Scanning watchlists using Named Entity Recognition (NER)
- Automating document review and Suspicious Activity Reports (SARs) via prompt-based methods
Model Governance and Transparency
- Constructing models that are both explainable and subject to audit
- Identifying and addressing biases in fraud detection algorithms
- Integrating Explainable AI (XAI) techniques into compliance frameworks
Ethical Considerations, Regulations, and Model Risk
- Aligning with AML and KYC standards (e.g., FATF, FinCEN, EBA)
- Addressing AI ethics in customer surveillance and monitoring
- Meeting reporting benchmarks and ensuring regulatory auditability
Deployment Roadmaps and Emerging Trends
- Embedding AI models within current transaction infrastructure
- Establishing feedback loops and continuous model improvement cycles
- The potential of generative AI in fraud investigations and SAR automation
Recap and Future Directions
Requirements
- A solid grasp of fraud risks and AML workflows
- Prior experience in data analysis or compliance reporting
- Fundamental knowledge of Python or comparable analytics platforms
Target Audience
- Professionals specializing in fraud risk management
- Teams responsible for AML compliance
- Security management personnel
14 Hours
Testimonials (1)
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