Thank you for sending your enquiry! One of our team members will contact you shortly.
Thank you for sending your booking! One of our team members will contact you shortly.
Course Outline
AI Fundamentals in Financial Crime Prevention
- Examining fraud and AML challenges in the modern digital finance landscape
- Comparing conventional methods with AI-driven strategies
- Reviewing case studies from Mastercard, JPMorgan, and other major global banks
Applying Machine Learning to Transaction Surveillance
- Employing supervised learning for risk assessment and classification
- Utilizing unsupervised learning to identify anomalies
- Implementing real-time alert creation and stream data processing
Graph Analytics for Identifying Network Risks
- Representing connections between entities and their transactions
- Identifying intricate fraud patterns through graph AI applications
- Practical sessions using Neo4j or comparable tools
NLP Applications in AML Processes
- Extracting insights from text in customer due diligence (CDD)
- Performing watchlist scans via named entity recognition (NER)
- Conducting document reviews and suspicious activity reports (SARs) using prompt-based techniques
Model Governance and Interpretability
- Creating models that are transparent and subject to audit
- Identifying and reducing bias within fraud detection algorithms
- Integrating XAI methods into compliance workflows
Ethics, Regulatory Frameworks, and Model Risk
- Aligning with AML and KYC regulations (such as FATF, FinCEN, and EBA guidelines)
- Addressing AI ethical considerations in monitoring and surveillance
- Meeting reporting standards and ensuring regulatory audit readiness
Implementation Strategies and Emerging Trends
- Embedding AI models into current transaction processing systems
- Establishing feedback loops and mechanisms for model refinement
- Exploring the role of generative AI in fraud inquiries and SAR automation
Recap and Recommended Path Forward
Requirements
- Foundational knowledge of fraud risks and AML protocols
- Prior experience in data analysis or compliance reporting
- Basic working knowledge of Python or standard analytics platforms
Target Audience
- Specialists in fraud risk management
- Teams focused on AML compliance
- Security management professionals
14 Hours
Testimonials (1)
i already have some reports that i know, i will use some of the prompts that looked at today
