AI for Real-Time Financial Fraud Prevention

Get a practical, one-sitting blueprint for using advanced AI to stop fraud as it happens. This micro course connects the dots between detection techniques and operational deployment, showing how to move from static, rules-based monitoring to adaptive, AI-driven security. You’ll see how anomaly detection, behavioural biometrics, and geolocation triggers strengthen real-time protection, and how graph analytics uncover hidden criminal networks. We’ll cover continual learning to keep models ahead of attackers, plus strategies to reduce false positives without adding friction for customers. Finish with an action plan you can apply to your organisation the same day.

You’ll learn how to:

• Spot suspicious activity instantly with anomaly detection in payments and transfers
• Combine transaction pattern analysis with behavioural biometrics for stronger authentication
• Enhance card security with AI-driven risk scoring and geolocation triggers
• Use graph analytics and network mapping to expose hidden fraud rings
• Keep fraud models adaptive with continual learning techniques

Who it’s for: Fraud prevention specialists, risk managers, compliance officers, data scientists, and product teams in financial services who need a concise, actionable guide to AI-powered fraud detection.

Course Content

1. Course Overview
2. Anomaly Detection in Payment and Transfer Systems
3. Transaction Pattern Analysis and Behavioural Biometrics
4. AI-Enhanced Card Security and Geolocation Triggers
5. Graph-Based Fraud Detection and Network Mapping
6. Continual Learning for Adaptive Fraud Models
7. Conclusion