Blockchain-Enabled Secure Supply Chain Finance Using Federated Learning and Smart Contract-Based Trust Verification

Abstract

Federated learning based on blockchain-powered smart contracts transforms supply chain finance, with decentralized risk analysis, data privacy, and automatic transaction approval. The presented framework offers the operations of five strategic steps including data preprocessing, federated model training, risk forecasting, smart contract deployment, and system integration. In Federated Averaging (FedAvg), supply chain actors train models with their local information not being disclosed globally and use it to tweak global models, which in turn are trained by them. Blockchain provides verifiability which is not tamperable resulting into fraud and financial transparency. The classification of risks based on the patterns of the transactions and the operational parameters applies safe decision making in the decentralized networks. The platform enhances compliance, efficiency, and trust and provides an affordable system of autonomous financial validation at scale. The metrics like Transaction Throughput, Latency, Auditability Score, Trust Score demonstrate the performance of the framework in the real-life environment of the supply chain finance.