Federated Learning in Financial Services: A Path to Secure AI (Responsible Technology and Intelligence)

As financial institutions increasingly rely on AI and ML for data-driven decision-making, concerns about data privacy, security, and regulatory compliance are growing.Federated learning (FL) emerges as a key solution, enabling collaborative AI model training across multiple organizations without sharing raw data.This book explores advancements in FL technology in the financial industry, specifically in the context of privacy-preserving AI.It also examines the significant shift from traditional centralized machine-learning approaches to decentralized learning techniques. Structured into four comprehensive sections, the book offers an in-depth examination of the subject.The first section provides an overview and introduction to FL, and reviews the increasing challenges of data privacy and regulatory constraints in the financial industry, highlighting how federated learning enables secure AI-driven financial services.The second section explores federated architectures, secure multi-party