Transforming Financial Services with Generative AI: From Strategy and Design to Practical Applications

Generative AI (GenAI) is revolutionizing the financial services sector (FSS), offering new ways to enhance efficiency, improve customer experiences, and streamline operations. This book is your comprehensive guide to understanding and implementing GenAI within FSS. Grounded in real-world use cases, this book moves from fundamentals to boardroom-ready execution. You'll start with the core concepts behind AI, machine learning, and GenAI, then pivot into the challenges of FSS: intense regulatory scrutiny, evolving fraud threats, operational complexity, and rising expectations for personalized, always-on service. You'll learn a practical blueprint for GenAI adoption, including strategy, governance, risk controls, data readiness, and culture--through the lens of executives tasked with delivering measurable value responsibly. From there, you'll get hands-on experience building GenAI systems: prompt design, evaluation, Retrieval-Augmented Generation (RAG), fine-tuning, and agentic workflows. You'll see how these capabilities power mission-critical functions across the enterprise: Finally, you'll operationalize all of it with modern FMOps/LLMOps practices--security, privacy, performance, cost management, monitoring, and continuous improvement--so pilots become production systems that scale. The closing chapter distills emerging trends, from autonomous agents to domain-specialized models, and lays out next steps so your organization can adopt GenAI with confidence, compliance, and a clear return on investment. Whether you're a CIO crafting a roadmap, a product leader shipping AI features, a data scientist building RAG pipelines, or a risk and compliance executive seeking control and clarity, this book is your end-to-end guide to deploying GenAI that is safe, explainable, and enterprise-grade. What You Will Learn

Develop a strategic blueprint for GenAI adoption, including implementation methodologies, risk mitigation, and best practices for financial institutions Master the core components of building GenAI applications, from prompt engineering and model evaluation to RAG and Agentic AI

Discover how GenAI transforms risk and compliance management, including applications in Anti-Money Laundering (AML), trade surveillance, and regulatory reporting

Explore practical GenAI use cases across retail banking, investment banking, and wealth management, and learn about successful operational deployment

Who This Book Is For Data scientists, AI professionals, and financial services experts interested in leveraging generative AI within the financial sector.

Author: Srinath Godavarthi,Ravi Nagvekar
Publisher: Apress
Published: 01/03/2026
Pages: 325
Binding Type: Paperback
Weight: 1.35lbs
Size: 10.00h x 7.00w x 0.73d
ISBN: 9798868820526

About the Author

Srinath Godavarthi has over 20 years of experience in the IT industry serving both public sector and commercial customers. He held leadership positions with global technology and consulting companies including Amazon and Accenture. In his previous roles, Srinath led digital transformation for a number of customers across multiple industry verticals including Financial Services, Healthcare and Telecommunications. Srinath is an accomplished author, specializes in GenAI, AI/ML technologies and published over a dozen white papers and blogs. He has been a speaker at various industry conferences including Generative AI summits, AWS Public sector summit, AWS re: Invent, American public Human Services association among others. He holds a Master's degree in Computer Science from Temple University and a Chief Technology Officer program from the University of California, Berkeley. Srinath is deeply passionate about causes that impact Veterans and kids. In his spare time, he volunteers to help Veterans and enables the next generation by teaching AI/ML technologies to high school students and assisting them with research projects.

Dr Ravi Nagvekar is a seasoned technology professional with more than 20 years of experience in the IT and finance domains, having worked with some of the world's leading financial institutions, including JP Morgan Chase, ABN Amro, ICICI Bank, HDFC Bank, and Bank of Baroda. His extensive expertise spans across multiple areas, such as generative AI, machine learning, data engineering, and cloud solutions. Currently, Ravi is part of Amazon Web Services (AWS), where he supports some of the largest financial clients in the Americas, focusing on generative AI and machine learning implementations. Prior to his role at AWS, he led the Analytics and Machine Learning Platform Engineering team at JP Morgan Chase, driving innovation and enabling advanced analytics capabilities for the bank's strategic initiatives. Ravi has presented at numerous AWS Summits, Latin American summits, and client events, sharing his insights on AI/ML and generative AI, and is recognized for his thought leadership in the field. He is also the inventor of a patented cloud-agnostic data mesh, demonstrating his ability to create cutting-edge solutions that address complex data challenges. Academically, Ravi holds a aster's degree in Technology Management from the University of Arizona and a master's degree in Computer Management from the University of Pune. He also completed a Postgraduate Diploma from the Columbia Technical Institute. Currently, Ravi is pursuing a Doctorate, with his research focusing on the impact of generative AI on the financial industry. With a passion for continuous learning, Ravi stays at the forefront of emerging technologies, constantly exploring new developments in AI and cloud computing. In his spare time, he enjoys spending quality time with his family and exploring new places around the world.

Mandy Kinne is a Technical Editor, who has been an integral part of our team. Mandy has a passion for language and technology. She loves connecting with people from diverse backgrounds and working with people across cultures, which taught her the power of sharing knowledge through words and illustrations. Mandy has been working with AI and its precursors, in some form, since 1994, when she was employed by the Center for Machine Translation at Carnegie Mellon University. Mandy has been a technical writer in a variety of industries--health insurance, telecom and computer networking and hardware--and before becoming a freelancer, she worked at a fintech company. She holds BAs in Rhetoric and French from Carnegie Mellon University and is active in the Write the Docs technical writing community. Mandy volunteers with the NOVA Roller Derby, serves as the Communications Chair for her fiber art guild, and is always knitting or spinning something.