[P] Open Source Fraud Detection System handling 0.17% class imbalance with Random Forest

Hey everyone, I just finished refactoring my Credit Card Fraud Detection system. I wanted to move away from messy notebooks and build a production-grade Python application.

Key features:

• Handles imbalanced data (PaySim dataset) using class weighting.
• Modular design (Ingestion, Feature Engineering, and Evaluation are decoupled).
• Full integration tests (pytest ) and audit logging.
• Achieves ~0.99 AUC.

It’s also a good reference if you’re trying to structure your ML projects professionally.

Repo: github.com/arpahls/cfd Feedback is more than welcome!