Generative AI for Financial Services: Challenges, anti-patterns, and best practicesКНИГИ » ПРОГРАММИНГ
Название: Generative AI for Financial Services: Challenges, anti-patterns, and best practices Автор: Vikesh Pandey, Arnav Khare Издательство: BPB Publications Год: 2025 Страниц: 316 Язык: английский Формат: epub (true) Размер: 10.1 MB
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.
This book is a perfect starting point for anyone looking to gain expertise in Generative AI while learning how it can be applied to financial services. It goes quite in detail on the nuances of financial services and the risks. Challenges and opportunities it brings along and how generative AI can be used to increase efficiency in various business processes at financial institutions.
It takes a practical approach to showcase how generative AI can be implemented to solve different use-cases in financial services while providing detailed insights into common generative AI use-cases while providing reference architectures and also hands-on solutions. The code samples given in the book are all Python based, so we expect the readers to have a basic level of understanding of Python programming language.
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.
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
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