Data & Analytics
Design a Fraud Detection System (Real-time stream processing)
A low-latency stream-processing system scoring every transaction against behavioral and rule-based models before it completes.
Open and Simulate this Architecture in InfraDraftCore Architectural Components
Real-Time Event Stream Ingestion
Every transaction enters the pipeline the moment it's initiated.
Feature Store
Serves real-time and historical user/transaction features to the scoring model.
Rule Engine
Deterministic, explainable checks that run alongside the ML model.
ML Scoring Service
Real-time inference producing a fraud probability per transaction.
Decision/Action Service
Turns a score into block/flag/allow within the transaction's latency budget.
Case Management & Manual Review Queue
Routes ambiguous cases to human analysts.
Model Feedback Loop
Feeds confirmed outcomes back into retraining data.