Financial AI in Practice

Using AI in finance requires more than just writing code. You must build a complete system that works correctly. The system should follow the industry rules. It should be able to handle complex real-world data. It can be difficult to know where to start when building a program for credit, fraud or investments. This book gives you a clear plan to build your own financial AI programs from beginning to end.  Build a complete AI program for scoring and fraud detection.  Combine machine learning models with large language models to improve results.  Detect complex fraud using graph analytics and network detection.  Create safe and reliable AI systems using RAG techniques.  Understand the business side of AI projects and how to plan for them.  Financial AI in Practice is a guide to building complete AI systems for finance. You will work on projects for credit risk, fraud detection, investment decisions and business operations. The book shows how to build full applications that follow rules and work with real-world data. It also teaches simple steps that you can use for any AI project in finance.  After reading this book, you will have the skills to build your own financial AI systems. You will know how to work with real data, combine different models and create systems that deliver real results. This book is for data scientists, business leaders and anyone in finance who wants to build practical AI systems.