Brian-Mbuya/mpesa-fraud-detection

The project is a standard application of the Isolation Forest algorithm to a specific domain (M-Pesa). With only 2 stars and 1 fork after nearly 100 days, it lacks community traction and functional depth. It serves as a personal project or educational tutorial rather than a production-grade security tool. The use of synthetic data highlights the primary barrier in this niche—access to real, sensitive financial transaction logs—which this project does not overcome. Defensibility is minimal as any data scientist can replicate this logic using standard scikit-learn documentation in a few hours. In a real-world scenario, this would be displaced by internal proprietary models at major fintechs like Safaricom or specialized fraud platforms like Feedzai or Featurespace, which utilize more advanced techniques (Graph Neural Networks, streaming analytics) and real-world data labels.