Transaction Stream Monitoring and Fraud Detection Backend

Fraud costs financial platforms money and trust, and it happens in the milliseconds between a transaction arriving and being approved. This project builds the backend that watches that window: a real-time transaction monitoring and fraud detection service for a finance platform. The intern implements the service in Express and Node.js on PostgreSQL, designing ACID-compliant transaction processing so no payment is half-recorded even under failure, and applying concurrency control so simultaneous operations on the same account cannot corrupt balances. Detection logic evaluates incoming transactions against suspicious patterns, with advanced SQL including joins and carefully chosen indexes keeping those checks fast; Redis caches high-frequency queries so hot paths avoid repeated database round trips. JWT-secured endpoints, role-based access, and audit trails ensure every action is authenticated and every decision leaves a reviewable record. The project teaches the disciplines that distinguish financial backends from ordinary APIs, including correctness under concurrency, auditability, and performance at the query level, and completing it gives the intern concrete evidence they can engineer systems where mistakes have monetary consequences.