Data as of Jul 25, 2026 · Based on 2,718,867 AI responses across 9,511 prompts · See how Parse measures this
DeFraudify is a complete solution for detecting anomalous financial transactions and identifying customer-level risk, using supervised machine learning for fraud prediction. The system combines unsupervised anomaly detection, clustering, and supervised models to flag potentially fraudulent activity. It includes data preprocessing, behavioral feature extraction, multiple anomaly detection techniques (KMeans, DBSCAN, Isolation Forest, LOF), optional supervised models (Random Forest, XGBoost), and a Streamlit-based dashboard for visualization and reporting.
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