國立虎尾科技大學 |

Generative AI for financial services = challenges, anti-patterns, and best practices /

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Generative AI for financial services / Vikesh Pandey, Arnav Khare.
Reminder of title:	challenges, anti-patterns, and best practices /
Author:	Pandey, Vikesh.
other author:	Khare, Arnav,
Description:	1 online resource (318 pages)
Subject:	COMPUTERS / Data Science / Machine Learning. -
Online resource:	https://portal.igpublish.com/iglibrary/search/BPB0000706.html
ISBN:	9789365891843

Generative AI for financial services = challenges, anti-patterns, and best practices /
Pandey, Vikesh.

Generative AI for financial services challenges, anti-patterns, and best practices /[electronic resource] ：Vikesh Pandey, Arnav Khare. - 1 online resource (318 pages)

Includes bibliographical references and index.

Generative AI for financial services : challenges, anti-patterns, and best practices -- About the Authors -- About the Reviewers -- Acknowledgements -- Preface -- Code Bundle and Coloured Images -- Table of Contents -- 1. Introduction to Generative AI -- 2. Types of Foundation Models -- 3. Generative AI Implementation Approaches -- 4. Generative AI Use-cases in Financial Services -- 5. Generative AI Challenges for Financial Services -- 6. Generative AI Anti-Patterns for Financial Services -- 7. Architectural Considerations in Generative AI -- 8. Use-case: Improving Customer Experience with Generative AI -- 9. Use-case: Contact Center Insights with Generative AI -- 10. Use-case: Fine-tuning for Financial Services -- 11. Use case: Automating ESG Analysis Using Agents -- 12. Choosing the Right Implementation Approach -- 13. Increasing Trustworthiness in Generative AI -- 14. Building Foundation Model Operations Practices -- Index.

Access restricted to authorized users and institutions.

Generative AI for Financial Services is a book targeted at any AI practitioner who wants to understand how generative AI works on a fundamental level and extend that learning to risks, challenges, and opportunities in regulated industries like financial services. This book explores generative AI and its applications in financial services. It starts by explaining key concepts, differences from traditional AI, and the generative AI lifecycle. Readers learn about foundation models, transfer learning, and implementation strategies, including fine-tuning and training models. Practical use cases like improving customer experiences, automating ESG analysis, and optimizing contact centers are covered. The book also addresses challenges like model bias, ethics, and compliance while focusing on building trustworthy AI with fairness and accountability. Finally, it highlights MLOps and FMOps for efficient AI model deployment and management in production environments. By the end of this book, you will be well-equipped to navigate the exciting world of generative AI and confidently apply its transformative potential within the financial services landscape. KEY FEATURES Evolve from a generative AI enthusiast to an advanced practitioner in generative AI. Learn effective ways of building generative AI solutions for financial services. Become familiar with the upcoming trends in generative AI space. WHAT YOU WILL LEARN Learn about popular use-cases, challenges, risks in financial services, and how to overcome those. Learn how to launch and scale generative AI applications in regulated environments like financial services, expanding from tens to thousands of use cases. Understand the operational aspects of AI, including MLOps and FMOps. Address challenges and ethical considerations in AI implementation. WHO THIS BOOK IS FOR This book is suitable for generative AI engineers, prompt engineers, ML engineers, data scientists, AI/ML, and technical leaders in financial services.

Mode of access: World Wide Web.

ISBN: 9789365891843Subjects--Topical Terms:

1483854
COMPUTERS / Data Science / Machine Learning.
Index Terms--Genre/Form:

554714
Electronic books.

LC Class. No.: QA76.9.A25

Dewey Class. No.: 006.3

Generative AI for financial services = challenges, anti-patterns, and best practices /
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505 0 # $a Generative AI for financial services : challenges, anti-patterns, and best practices -- About the Authors -- About the Reviewers -- Acknowledgements -- Preface -- Code Bundle and Coloured Images -- Table of Contents -- 1. Introduction to Generative AI -- 2. Types of Foundation Models -- 3. Generative AI Implementation Approaches -- 4. Generative AI Use-cases in Financial Services -- 5. Generative AI Challenges for Financial Services -- 6. Generative AI Anti-Patterns for Financial Services -- 7. Architectural Considerations in Generative AI -- 8. Use-case: Improving Customer Experience with Generative AI -- 9. Use-case: Contact Center Insights with Generative AI -- 10. Use-case: Fine-tuning for Financial Services -- 11. Use case: Automating ESG Analysis Using Agents -- 12. Choosing the Right Implementation Approach -- 13. Increasing Trustworthiness in Generative AI -- 14. Building Foundation Model Operations Practices -- Index.
506 # $a Access restricted to authorized users and institutions.
520 3 $a Generative AI for Financial Services is a book targeted at any AI practitioner who wants to understand how generative AI works on a fundamental level and extend that learning to risks, challenges, and opportunities in regulated industries like financial services. This book explores generative AI and its applications in financial services. It starts by explaining key concepts, differences from traditional AI, and the generative AI lifecycle. Readers learn about foundation models, transfer learning, and implementation strategies, including fine-tuning and training models. Practical use cases like improving customer experiences, automating ESG analysis, and optimizing contact centers are covered. The book also addresses challenges like model bias, ethics, and compliance while focusing on building trustworthy AI with fairness and accountability. Finally, it highlights MLOps and FMOps for efficient AI model deployment and management in production environments. By the end of this book, you will be well-equipped to navigate the exciting world of generative AI and confidently apply its transformative potential within the financial services landscape. KEY FEATURES Evolve from a generative AI enthusiast to an advanced practitioner in generative AI. Learn effective ways of building generative AI solutions for financial services. Become familiar with the upcoming trends in generative AI space. WHAT YOU WILL LEARN Learn about popular use-cases, challenges, risks in financial services, and how to overcome those. Learn how to launch and scale generative AI applications in regulated environments like financial services, expanding from tens to thousands of use cases. Understand the operational aspects of AI, including MLOps and FMOps. Address challenges and ethical considerations in AI implementation. WHO THIS BOOK IS FOR This book is suitable for generative AI engineers, prompt engineers, ML engineers, data scientists, AI/ML, and technical leaders in financial services.
538 $a Mode of access: World Wide Web.
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700 1 # $a Khare, Arnav, $e author $3 1483966
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