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Course Outline
AI in Financial Crime: An Introduction
- The landscape of fraud and AML in the era of digital finance
- Comparing conventional methods with AI-driven solutions
- Real-world examples from Mastercard, JPMorgan, and major global banks
Machine Learning for Transaction Monitoring
- Using supervised learning for risk scoring and classification
- Applying unsupervised learning to identify anomalies
- Generating real-time alerts and processing data streams
Graph Analytics and Network Risk Identification
- Modeling connections between entities and transaction flows
- Identifying complex fraud schemes through graph AI
- Practical sessions using Neo4j or comparable technologies
NLP for Anti-Money Laundering
- Text mining techniques for customer due diligence (CDD)
- Scan watchlists using named entity recognition (NER)
- Prompt-based document analysis and handling suspicious activity reports (SARs)
Model Governance and Interpretability
- Creating models that are explainable and subject to audit
- Identifying and mitigating bias in fraud detection algorithms
- Applying XAI methods within compliance frameworks
Ethics, Regulatory Frameworks, and Model Risk
- Adhering to AML and KYC standards (such as FATF, FinCEN, and EBA)
- Ethical considerations in surveillance and customer monitoring via AI
- Meeting reporting standards and ensuring regulatory audit trails
Deployment Strategies and Emerging Trends
- Embedding AI models into current transaction processing systems
- Establishing feedback loops and mechanisms for model updates
- The role of generative AI in fraud investigations and SAR automation
Recap and Future Directions
Requirements
- Familiarity with fraud risk concepts and AML procedures
- Prior experience in data analysis or compliance reporting
- Foundational knowledge of Python or common analytics platforms
Target Audience
- Fraud risk specialists
- AML compliance officers and teams
- Information 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
