Learning objectives
- • Design real-time feature generation and low-latency inference
- • Use rules, ML, graph signals, and human review together
- • Monitor adversarial drift and label delay
System Design
Real-Time Fraud, Risk, and Abuse Systems
Cover low-latency risk scoring, graph features, rules plus ML, delayed labels, investigation queues, and adversarial adaptation.
Recommended on day 70110 minutesAdvanced
Interview prompts
- • How would you design real-time card fraud detection?
- • How do you evaluate a fraud model when labels arrive weeks later?
Prerequisites