Opportunities and Applications of Federated Learning in the Financial Services Industry

Federated learning is an innovative machine learning technique that gained significant attention in the financial sector for its potential to address privacy concerns while maintaining the accuracy of predictive models. This technology enables financial institutions to train machine learning models in a decentralized manner from multiple devices without sharing raw data with a central server. This approach ensures data privacy and security while enabling financial institutions to make more informed decisions regarding, for example, credit risk, systemic risk, portfolio overlap, fraud detection systems, personalized investment advice, and open banking. Overall, this chapter explains how federated learning can be applied in the financial services industry and what considerations financial institutions must address to adopt federated learning.