Fraud Detection System
In-house transaction fraud detection and risk-management platform.
Problem
Detect suspicious transactions in near real time without adding meaningful latency to the payment path or blocking legitimate customers.
Architecture
A rules and scoring pipeline that consumes transaction events from a stream, evaluates risk signals, and emits decisions that the payment services enforce. Historical features are computed offline and served online.
Technical challenges
Balancing false positives against missed fraud, evaluating rules within tight latency budgets, and evolving rules safely in production.
Solution
An event-driven scoring service with versioned rule sets, shadow evaluation for new rules before enforcement, and clear observability into why a transaction was flagged.
Scale
Evaluates high-throughput transaction streams in near real time.
Lessons learned
Shadow-testing rules before enforcement made it safe to iterate quickly. Explainability mattered as much as accuracy for operational trust.
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