FraudSense — AI Fraud Detection

FraudSense is an end-to-end Machine Learning solution designed to secure digital payment ecosystems. It ingests financial transactions, extracts complex features in real-time, and scores fraud probability before the transaction clears.

Key Features

• Optimized XGBoost Model: Trained on highly imbalanced transactional datasets, utilizing advanced hyperparameter tuning to maximize Recall while maintaining acceptable precision.
• Real-Time Feature Engineering: Computes historical user metrics on-the-fly (e.g., transaction velocity, geographic IP distance, behavioral drifts).
• Low-Latency API: Architected to return predictions in milliseconds, enabling synchronous blocking during the checkout flow.
• Analytical Dashboard: UI for fraud analysts that provides model explainability (Explainable AI / SHAP values), facilitating manual investigation of “grey-area” cases.

Tech Stack

Data Science core built with Python (Scikit-Learn, XGBoost, Pandas), asynchronously served API, and fast in-memory caching for transaction velocity calculations.