2026 · Big Data · AI

Order Fraud Detection

Order Fraud Detection project overview illustration
Project overview illustration; not a product screenshot.

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