AI Fraud Detection Software is a production-ready fraud detection system that analyzes transactions in real-time using an ensemble of five machine learning models: XGBoost, LightGBM, Random Forest, Logistic Regression, and Isolation Forest. The system delivers fraud probability scores, risk levels, recommended actions, and SHAP-based explanations for every prediction through an interactive dashboard and RESTful API.
Built for businesses and developers who need immediate fraud detection capabilities, this system includes a complete technology stack: FastAPI backend, React/TypeScript frontend with Tailwind CSS, PostgreSQL database, Redis caching, and Docker-based deployment. The package includes synthetic data generation scripts that create realistic transaction patterns for model training, improving coverage while protecting user information. The trained models achieve 90%+ accuracy on test data. Integration is straightforward via the included REST API with interactive documentation at /api/docs.
You receive the complete application source code, Docker configuration, training scripts, deployment guides, and a perpetual commercial license. Deploy the system on your infrastructure, customize it for your business needs, or integrate it into existing platforms. The license permits you to build and operate commercial services, including SaaS offerings, for your customers. Technical requirements include Docker Desktop, 4GB RAM minimum (8GB recommended), and basic command-line familiarity for setup.
Key capabilities: real-time transaction scoring (millisecond response times), ensemble predictions with model-level breakdown, explainable AI with top contributing factors, risk categorization (low/medium/high/critical), recommended actions (approve/review/decline/block), interactive analytics dashboard, fraud trend visualization, feature importance analysis, batch prediction support, and full API access for integration.
