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.
Duration 14 hours
Course Outline
AI in Financial Crime: An Introduction
- The landscape of fraud and AML in the era of digital finance
- Comparing traditional methods with AI-driven solutions
- Insights from case studies involving Mastercard, JPMorgan, and major global banks
Machine Learning for Transaction Monitoring
- Applying supervised learning to risk scoring and classification
- Using unsupervised learning techniques for anomaly detection
- Generating real-time alerts through stream processing
Graph Analytics for Network Risk Detection
- Mapping connections between entities and transactions
- Uncovering sophisticated fraud schemes using graph AI
- Practical exercises with Neo4j or equivalent tools
NLP Applications in AML
- Applying text mining to customer due diligence (CDD)
- Enhancing watchlist scanning via named entity recognition (NER)
- Automating document review and suspicious activity reports (SARs) using prompt-based methods
Model Governance and Explainability
- Creating models that are both explainable and audit-ready
- Identifying and addressing bias in fraud detection algorithms
- Implementing XAI techniques within compliance frameworks
Ethics, Regulation, and Model Risk
- Adhering to AML and KYC regulatory frameworks (such as FATF, FinCEN, and EBA)
- Addressing AI ethics in surveillance and customer monitoring
- Meeting reporting standards and ensuring regulatory auditability
Deployment Strategies and Emerging Trends
- Integrating AI models into established transaction systems
- Establishing feedback loops and mechanisms for model updates
- The role of generative AI in future fraud investigations and SAR automation
Conclusion and Path Forward
Requirements
- Familiarity with fraud risks and AML procedures
- Practical experience in data analysis or compliance reporting
- Foundational knowledge of Python or other analytics platforms
Target Audience
- Fraud risk specialists
- AML compliance teams
- Security managers
Testimonials (1)
i already have some reports that i know, i will use some of the prompts that looked at today
