Decision Tree fraud detection for mobile money transactions with Ghana cedis support
# 🇬🇠Mobile Money Fraud Detection System
A machine learning system that detects fraudulent mobile money transactions using a Decision Tree classifier. Built with Ghana Cedis (₵) support for local relevance.
## 🎯 Key Results
- *82.2%* fraud detection rate (recall)
- *277Ă— better than random* (PR-AUC 0.36 vs 0.0013)
- Real-time transaction scoring
## 📊 Dataset
- *Source:* PaySim synthetic dataset (Kaggle)
- *Size:* 6.36M transactions
- *Fraud rate:* 0.13% (highly imbalanced)
## 🛠️ Tech Stack
- Python 3.11
- scikit-learn (Decision Tree)
- pandas, numpy
- matplotlib, seaborn
## 🚀 Quick Start
### Installation
```bash
git clone
github.com
cd fraud-detection-mobile-money
pip install -r requirements.txt