Federated Learning in Financial Services

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 computation, differential privacy, and homomorphic encryption. The third section highlights practical applications of AI and federated learning in areas such as risk management, fraud detection, credit scoring, and customer personalization, demonstrating how FL enhances security, scalability, and operational efficiency in financial systems. Financial applications where federated learning enhances security, scalability, and efficiency are also addressed. The fourth section discusses emerging trends in federated learning, including blockchain-based federated learning, zero-trust architectures, and its integration with decentralized finance (DeFi). The book concludes by examining practical implementations and regulatory considerations, ensuring compliance with data protection laws such as GDPR and CCPA.

Suvarna Sharma is an accomplished academician, researcher, and author in the field of Computer Science and Artificial Intelligence. She currently serves as an Assistant Professor at MIT World Peace University, Pune, India. She earned her Ph.D. from Maulana Azad National Institute of Technology (MANIT), Bhopal, with doctoral research focused on improving web crawler coverage using intelligent seed selection techniques. She has over a decade of experience spanning academia, research, and software development, having held academic positions at reputed institutions including Chitkara University and MANIT Bhopal, and having worked as a Software Developer at the Defence Research and Development Establishment (DRDE), Gwalior. Her research interests encompass web mining, machine learning, deep learning, blockchain technology, IoT, healthcare analytics, digital twins, federated learning, and intelligent systems. She has published extensively in leading IEEE conferences, Scopus- and Springer-indexed journals, and has contributed numerous book chapters with international publishers such as Springer, Wiley, CRC Press, and IGI Global. Dr. Sharma is the recipient of a Best Paper Award at an IEEE international conference and holds multiple patents in blockchain-based trust mechanisms and smart system designs. Actively engaged in academic service, Dr. Sharma serves as a reviewer for international conferences and journals and is a member of professional computing societies. Her work reflects a strong commitment to interdisciplinary research, innovation, and the advancement of emerging technologies through education and scholarly contribution.

Jeetendra Kumar holds Ph.D. degree in Computer Science from GLA University Mathura. Currently He has been working as an Assistant Professor in the Department of Computer Science and Application at Atal Bihari Vajpayee University, Bilaspur, Chhattisgarh, India for the last 10 years. He holds a master’s degree (M.Sc.) and a Master of Technology (M. Tech.) in Computer Science. He has published various research articles in reputed journals and conferences, including topics such as sentiment analysis, fall detection using machine learning techniques, IoT applications, automatic question generation, etc. He has also contributed book chapters on topics related to neuroscience, smartphone applications, and fog computing in healthcare. He has edited one book with CRC Press, Taylor and Francis. Dr. Kumar has completed two research projects sponsored by the State Planning Commission, C.G., and Commonwealth Media Centre for Asia (CEMCA) New Delhi and Atal Bihari Vajpayee University, Bilaspur. He is also a member of prestigious academic societies such as IEEE, the Indian Science Congress, the International Association of Engineers (IAENG), the International Computer Science and Engineering Society (ICSES), and the International Association of Academicians (IAASSE).

Rashmi Gupta holds a Ph.D. degree in Computer Applications from the NIT, Raipur. Currently, she serves as an Assistant Professor in the Department of Computer Science and Application at Atal Bihari Vajpayee University Bilaspur, Chhattisgarh. She has published more than 25 research papers, conference papers, and book chapters and has been awarded grants by AICTE to organize the ATAL Faculty Development Program and by the Science and Engineering Research Board, DST for conducting High-end Workshops and Internships. Demonstrating her commitment to mentorship, Dr. Gupta has guided over 30 PG and 20 UG students in their research-related major projects. She has edited two books with CRC Press, Taylor and Francis. With over 12 years of teaching experience, her research interests encompass Natural Language Processing, EEG signal processing, and Human activity recognition. She is also a member of prestigious academic societies such as IEEE, the Indian Science Congress, the International Association of Engineers (IAENG), the International Computer Science and Engineering Society (ICSES), and the International Association of Academicians (IAASSE).

Valentina E. Balas is a Full Professor in the Department of Automatics and Applied Software at the Faculty of Engineering, “Aurel Vlaicu” University of Arad, Romania. She holds a PhD Cum Laude, in Applied Electronics and Telecommunications from Polytechnic University of Timisoara. Dr. Balas is author of more than 350 research papers in refereed journals and International Conferences. Her research interests are in Intelligent Systems, Fuzzy Control, Soft Computing, Smart Sensors, Information Fusion, Modeling and Simulation. She is the Editor-in Chief to International Journal of Advanced Intelligence Paradigms (IJAIP) and to International Journal of Computational Systems Engineering (IJCSysE), member in Editorial Board member of several national and international journals and is evaluator expert for national, international projects and PhD Thesis. Dr. Balas is the director of Intelligent Systems Research Centre in Aurel Vlaicu University of Arad and Director of the Department of International Relations, Programs and Projects in the same university. She served as General Chair of the International Workshop Soft Computing and Applications (SOFA) in nine editions organized in the interval 2005-2020 and held in Romania and Hungary. Dr. Balas participated in many international conferences as Organizer, Honorary Chair, Session Chair, member in Steering, Advisory or International Program Committees and Keynote Speaker. Recently she was working in a national project with EU funding support: BioCell-NanoART Novel Bio-inspired Cellular Nano-Architectures - For Digital Integrated Circuits, 3M Euro from National Authority for Scientific Research and Innovation. She is a member of European Society for Fuzzy Logic and Technology (EUSFLAT), member of Society for Industrial and Applied Mathematics (SIAM) and a Senior Member IEEE, member in Technical Committee – Fuzzy Systems (IEEE Computational Intelligence Society), chair of the Task Force 14 in Technical Committee – Emergent Technologies (IEEE CIS), member in Technical Committee – Soft Computing (IEEE SMCS). Dr. Balas was past Vice-president (responsible with Awards) of IFSA - International Fuzzy Systems Association Council (2013-2015), is a Joint Secretary of the Governing Council of Forum for Interdisciplinary Mathematics (FIM), - A Multidisciplinary Academic Body, India and recipient of the "Tudor Tanasescu" Prize from the Romanian Academy for contributions in the field of soft computing methods (2019).

Gaurav Dhiman is a highly accomplished academician and researcher with an impressive track record of excellence in computer science. He holds PostDoctoral from Federal University of Ceara (Brazil), Ph.D. in Computer Engineering from Thapar Institute of Engineering & Technology, Patiala, and has also completed his Master Degree of Computer Applications from the same institute. Currently, he is serving as an Assistant Professor in the School of Sciences and Emerging Technologies, Jagat Guru Nanak Dev Punjab State Open University, Patiala. His research has been recognized at the highest level, as he has been named one of the world's top researchers by Clarivate Analytics as world’s Top 1% highly cited researcher. He also listed of world's Top 2% scientists prepared by Elsevier and Stanford University, USA. He is the senior member of IEEE. He has also received accolades for his outstanding reviewer work from Knowledge-Based Systems (Elsevier). He has authored over 300 peer-reviewed research papers, all of which are indexed in SCI-SCIE, and 15 international books. He is currently serving as a guest editor for more than forty special issues in various peer-reviewed journals. He is an Editor-in-Chief of the ICCK Transactions on Machine Intelligence and ICCK Transactions on Large Language Models. He is an Associate Editor of IEEE Transactions on Industrial Informatics, IEEE Transactions on Consumer Electronics, IEEE Transactions on Computational Social Systems, IET Software (Wiley), Expert Systems (Wiley), IEEE Systems, Man, and Cybernetics Magazine, Spatial Information Research (Springer), and many more. He is also an Academic Editor of Computational and Mathematical Methods in Medicine (Hindawi), Scientific Programming (Hindawi), Mobile Information Systems (Hindawi), and Review Editor of Frontiers in Energy Research - Fuel Cells, Frontiers in High-Performance Computing - Parallel and Distributed Software, Frontiers in Artificial Intelligence - Pattern Recognition, and more. His research interests span a wide range of topics including Generative Artificial Intelligence, Large Language Modles, Internet of Things, Machine-learning, Deep-learning, Single-, Multi-, Many-objective optimization (Bio-inspired, Evolutionary, and Quantum), Soft computing (Type-1 and Type-2 fuzzy sets), Power systems, and Change detection using remotely sensed high-resolution satellite data. He has published his research in various reputed journals, including IEEE, Elsevier, Springer, Wiley, Taylor and Francis, among others.