Generative AI for Financial Services: Challenges, anti-patterns, and best practices (English Edition)

Description

DescriptionGenerative 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 forThis book is suitable for generative AI engineers, prompt engineers, ML engineers, data scientists, AI/ML, and technical leaders in financial services.Table of Contents1. Introduction to Generative AI2. Types of Foundation Models3. Generative AI Implementation Approaches4. Generative AI Use-cases in Financial Services5. Generative AI Challenges for Financial Services6. Generative AI Anti-Patterns for Financial Services7. Architectural Considerations in Generative AI8. Use-case: Improving Customer Experience with Generative AI9. Use-case: Contact Center Insights with Generative AI10. Use-case: Fine-tuning for Financial Services11. Use case: Automating ESG Analysis Using Agents12. Choosing the Right Implementation Approach13. Increasing Trustworthiness in Generative AI14. Building Foundation Model Operations Practices