2026 · Big Data · AI
Order Fraud Detection
Real-time fraud detection for suspicious orders before fulfillment
Tech Stack
PythonApache SparkCeleryOracle DBMongoDBOpenTelemetry
Overview
Order Fraud Detection is a large-scale data pipeline designed to identify fraudulent transactions across high-volume order streams in real time. The system processes order events using Apache Spark and Celery workers, applying rule-based scoring and behavioral pattern analysis to flag suspicious orders before fulfillment. OpenTelemetry provides full observability across the pipeline. Built for a warehouse and logistics operation handling nationwide distribution, it supports fraud review before orders reach fulfillment.
Goals
- 01Detect and flag fraudulent orders in real time before they reach fulfillment
- 02Process high-volume transaction streams with timely detection
- 03Reduce financial loss from order manipulation and identity fraud
- 04Provide an auditable fraud event log for compliance and review teams

