Authors: Dr. Priti Aggarwal, Ayush Mehrotra, Dr. Vishnu Kumar Balouva, Dr. Kirandeep Kaur, and Dr. Bhavna Sharma

ISBN: 978-93-7183-022-5

DOI: https://doi.org/10.59646/810

Date of Publication: August 31, 2026

Cite this book: Priti A, Ayush M, Vishnu KB, Kirandeep K, and Bhavna S, (2026), Paradox International Publications & San International Scientific Publications, ISBN: 978-93-7183-022-5, DOI: https://doi.org/10.59646/810

Preface

The financial services industry is undergoing a profound transformation driven by the convergence of Artificial Intelligence (AI), Machine Learning (ML), big data, cloud computing, blockchain, automation, and digital platforms. Financial Technology (FinTech) has emerged as a powerful force in reshaping traditional banking, payments, lending, insurance, investment management, wealth management, and financial inclusion. Among these technologies, Artificial Intelligence has become particularly significant because of its ability to analyse vast volumes of financial data, identify patterns, automate complex processes, support decision-making, and create highly personalized financial services. This transformation has created new opportunities while simultaneously introducing important questions relating to ethics, privacy, security, transparency, regulation, and human oversight.

The textbook Artificial Intelligence in FinTech: Foundations and Financial Innovation has been developed to provide a comprehensive and accessible understanding of the principles, technologies, applications, opportunities, and challenges associated with AI-driven financial innovation. The book adopts an interdisciplinary approach by connecting concepts from Artificial Intelligence, Machine Learning, Finance, Banking, Business Analytics, Financial Technology, Risk Management, Cybersecurity, and Digital Transformation. The book begins with the foundations of AI and the FinTech ecosystem, enabling readers to understand the evolution of intelligent financial systems and the role of financial data in modern decision-making. It then explores practical applications of AI in digital banking, intelligent payments, credit assessment, lending, insurance, investment management, wealth management, and algorithmic financial services. Particular attention is given to the ways in which machine learning and predictive analytics can improve efficiency, accuracy, personalization, and risk assessment across financial institutions. A significant part of the book focuses on AI-enabled financial risk management, fraud detection, Anti-Money Laundering (AML), Know Your Customer (KYC), cybersecurity, and trustworthy AI. As financial institutions increasingly depend on algorithmic systems, understanding issues such as algorithmic bias, explainability, fairness, accountability, data privacy, and model risk has become essential. The book therefore moves beyond the technological capabilities of AI to examine the responsibilities associated with its deployment in sensitive financial environments.

The textbook also examines emerging technologies that are redefining the FinTech landscape. Generative AI, Large Language Models, Natural Language Processing, computer vision, blockchain, smart contracts, decentralized finance, embedded finance, open banking, and autonomous financial systems are discussed in relation to their potential applications and limitations. These developments demonstrate how AI is moving from being a supporting analytical tool to becoming an increasingly important component of financial innovation and strategic decision-making. Another important theme of this book is responsible and inclusive financial innovation. Technological advancement should not be considered successful merely because it improves operational efficiency. Financial innovation must also promote fairness, accessibility, transparency, consumer protection, and social value. Accordingly, the book discusses AI governance, financial regulation, regulatory technology, supervisory technology, financial inclusion, sustainable finance, ESG analytics, and the role of AI in supporting environmentally and socially responsible financial systems.

The book has been designed with both academic learning and practical application in mind. Each major topic is connected to real-world financial scenarios, case studies, practical activities, analytical exercises, and project-based learning opportunities. Students are encouraged not only to understand how AI technologies work but also to critically evaluate where, why, and under what conditions they should be applied in financial services.

The textbook is particularly useful for students and learners of Commerce, Management, Finance, Banking, Economics, FinTech, Business Analytics, Computer Applications, Information Technology, and related multidisciplinary programmes. It can also serve as a valuable reference for researchers, educators, banking professionals, FinTech practitioners, entrepreneurs, financial analysts, and managers seeking to understand the strategic implications of AI in finance.

The chapters collectively emphasize that the future of finance will not be defined by technology alone. Rather, it will depend on the ability of organizations to combine intelligent technologies with human judgment, ethical responsibility, regulatory awareness, financial expertise, and customer-centric innovation. The goal is therefore not to replace human intelligence with artificial intelligence, but to create financial ecosystems in which technology and human capabilities complement one another.

As AI continues to evolve, the boundaries of financial innovation will also continue to expand. New business models, intelligent financial products, autonomous decision systems, and data-driven services will create opportunities that are difficult to predict fully today. At the same time, emerging risks will require continuous learning, responsible governance, and adaptive regulatory frameworks. This textbook seeks to provide readers with the conceptual foundation and critical perspective necessary to participate meaningfully in this rapidly changing environment.

It is hoped that Artificial Intelligence in FinTech: Foundations and Financial Innovation will serve not only as a textbook but also as a foundation for critical inquiry, responsible innovation, practical experimentation, and future research in intelligent finance. By bringing together technological knowledge and financial understanding, the book aims to prepare learners for a financial world in which digital intelligence, innovation, trust, and human values must work together.