Edge-Driven Federated Learning System for Secure and Scalable Financial Data Sharing With Privacy Protection
The results indicate that the proposed edge-driven federated learning framework can support privacy-preserving and robust cross-institutional financial risk modeling and provides an effective solution for collaborative fraud detection and anti-money laundering under data isolation, heterogeneous edge environments, and...