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Course Outline
Introduction to AI in Financial Crime
- The landscape of fraud and AML in the era of digital finance
- Comparing traditional methods with AI-driven solutions
- Real-world case studies from Mastercard, JPMorgan, and major global banks
Machine Learning for Transaction Monitoring
- Applying supervised learning for risk scoring and classification
- Utilising unsupervised learning to detect anomalies
- Generating real-time alerts and processing data streams
Graph Analytics and Network Risk Detection
- Modelling connections between entities and transactions
- Identifying intricate fraud schemes through graph AI
- Hands-on exercises using Neo4j or comparable tools
Natural Language Processing for AML
- Applying text mining in Customer Due Diligence (CDD)
- Scanning watchlists via Named Entity Recognition (NER)
- Conducting document reviews and generating Suspicious Activity Reports (SARs) using prompt-based methods
Model Governance and Explainability
- Constructing models that are both explainable and auditable
- Detecting and mitigating bias in fraud detection algorithms
- Incorporating XAI techniques into compliance frameworks
Ethics, Regulation, and Model Risk
- Ensuring alignment with AML and KYC frameworks (such as FATF, FinCEN, EBA)
- Ethical considerations in AI-driven surveillance and customer monitoring
- Meeting reporting standards and ensuring regulatory auditability
Deployment Strategies and Future Trends
- Integrating AI models into existing transaction systems
- Implementing feedback loops and model update mechanisms
- The role of Generative AI in the future of fraud investigation and SAR automation
Summary and Next Steps
Requirements
- A solid understanding of fraud risks and AML procedures
- Practical experience in data analysis or compliance reporting
- Fundamental knowledge of Python or analytics platforms
Target Audience
- Fraud risk specialists
- AML compliance teams
- 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
