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,…mehr
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
Artikelnr. des Verlages: 89536819, 979-8-8688-2052-6
First Edition
Seitenzahl: 175
Erscheinungstermin: 19. November 2025
Englisch
Abmessung: 254mm x 178mm
ISBN-13: 9798868820526
Artikelnr.: 75256965
Herstellerkennzeichnung
Libri GmbH
Europaallee 1
36244 Bad Hersfeld
gpsr@libri.de
Autorenporträt
Srinath Godavarthi has over 20 years of experience in the IT industry and has held leadership positions with global technology and consulting companies, including Amazon and Accenture. In his previous roles, Srinath led cloud strategy, architecture and digital transformation efforts for a number of federal, state, and local agencies, including Health and Human Services, Department of Veteran Affairs, and Department of Homeland Security. Srinath specializes in AI/ML technologies and has published more than a dozen white papers and blogs on various topics, including AI, ML, and healthcare. He has been a speaker at various industry conferences, including the AWS Public Sector Summit, AWS re:Invent, and the American Public Human Services Association, among others. He holds a master’s degree in Computer Science from Temple University and participate in the Chief Technology Officer Program from the University of California, Berkeley. Srinath is deeply passionate about causes that impact Veterans and kids. 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.¿¿¿
Inhaltsangabe
Chapter 1: Introduction to Generative AI.- Chapter 2: GenAI and the Financial Services Sector.- Chapter 3: GenAI Strategy: A Blueprint for Successful Adoption.- Chapter 4: Architecting and Building a GenAI Application.- Chapter 5: Risk and Compliance Managment with GenAI.- Chapter 6: Retail Banking with GenAI.- Chapter 7: Investment Banking with GenAI.- Chapter 8: Wealth and Asset Management wth GenAI.- Chapter 9: Implementation, Operations, and Maintenance of GenAI Applications.- Chapter 10: Emerging Trends, Summary, and Next Steps.
Chapter 1: Introduction to Generative AI.- Chapter 2: GenAI and the Financial Services Sector.- Chapter 3: GenAI Strategy: A Blueprint for Successful Adoption.- Chapter 4: Architecting and Building a GenAI Application.- Chapter 5: Risk and Compliance Managment with GenAI.- Chapter 6: Retail Banking with GenAI.- Chapter 7: Investment Banking with GenAI.- Chapter 8: Wealth and Asset Management wth GenAI.- Chapter 9: Implementation, Operations, and Maintenance of GenAI Applications.- Chapter 10: Emerging Trends, Summary, and Next Steps.
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