Product · 4 documents
The Privacy-Preserving Explainable Trust Framework (PP-ETF) achieves AUC-ROC performance within 1.4%–1.6% of centralized deep-learning models while enforcing privacy and decentralized trust guarantees.
UPI Fraud Shield is a prototype designed to monitor digital payment fraud in real time using tabular learning, graph neural networks, explainable AI, and an early-warning layer.
The Anti-Money Laundering Tracker models transaction networks using the IBM AMLSim synthetic dataset, which includes approximately 9,945 account records and 68,289 transactions.
The proposed hybrid AI system was trained and evaluated on a transaction dataset containing more than 6 million records with transaction time steps ranging from 0 to 743.
