Generative AI for Financial Services

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.

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

Vikesh Pandey is a Principal Generative AI/ML Specialist Solution Architect and the EMEA Generative AI Lead for financial services at AWS, where he helps the largest financial institutions in EMEA transform their business using Generative AI/ML technologies. He carries extensive experience designing large scale Generative AI&ML platforms and solutions for financial organizations, which cater to 100s of teams and 1000s of users and end consumers. Vikesh is also the maintainer of the most popular machine learning repository of AWS, which provides 100s of example implementations for GenAI and ML use-cases. Vikesh is an established public speaker, speaking at top tier AWS conferences and independently organized technology conferences and meet-ups, attended by tens of thousands of developers and executives. Vikesh is an active blogger writing technology blogs on AWS Official blogs and also on Medium.

Arnav Khare is a Principal Solutions Architect and leads the Generative AI prototyping team at AWS, working with the largest global financial institutions. His primary focus is helping Financial Services Institutions build Generative AI and Machine Learning applications in the cloud. Arnav holds an MSc in Artificial Intelligence from Edinburgh University and has 20 years of industry experience ranging from small startups he founded to large investment banks apart from AWS. Outside of work, Arnav loves spending time with his two daughters, finding new independent coffee shops, reading, and traveling.