Smart Finance Innovations with Federated Learning and Blockchain Integration

Abstract

By combining blockchain technology with federated learning, this study introduces a novel method of smart finance. The proposed method is designed to resolve the substantial challenges associated with data privacy, security, and operational efficiency that are prevalent in conventional banking systems. Federated learning enables numerous financial institutions to develop machine learning models that enhance privacy by cooperating rather than exchanging raw data. Furthermore, blockchain technology ensures the integrity and transparency of data by creating an immutable and distributed ledger. The federated learning process is automated by smart contracts, which ensures the safety and efficiency of participant participation. The system’s efficacy in enhancing model accuracy, operational efficiency, and trustworthiness, while simultaneously ensuring robust data privacy and security, is demonstrated by experiments. This integration is a substantial development in financial technology, as it provides a secure, efficient, and intelligent platform for the evaluation and decision-making process based on financial data. The model performed 95% accuracy.