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Hands-On Artificial Intelligence for Banking

You're reading from  Hands-On Artificial Intelligence for Banking

Product type Book
Published in Jul 2020
Publisher Packt
ISBN-13 9781788830782
Pages 240 pages
Edition 1st Edition
Languages
Authors (2):
Jeffrey Ng Jeffrey Ng
Profile icon Jeffrey Ng
Subhash Shah Subhash Shah
Profile icon Subhash Shah
View More author details

Table of Contents (14) Chapters

Preface 1. Section 1: Quick Review of AI in the Finance Industry
2. The Importance of AI in Banking 3. Section 2: Machine Learning Algorithms and Hands-on Examples
4. Time Series Analysis 5. Using Features and Reinforcement Learning to Automate Bank Financing 6. Mechanizing Capital Market Decisions 7. Predicting the Future of Investment Bankers 8. Automated Portfolio Management Using Treynor-Black Model and ResNet 9. Sensing Market Sentiment for Algorithmic Marketing at Sell Side 10. Building Personal Wealth Advisers with Bank APIs 11. Mass Customization of Client Lifetime Wealth 12. Real-World Considerations 13. Other Books You May Enjoy

Summary

In this chapter, you understood the basics of investment banking. Now, you should be able to understand the concepts of IPO and M&A. Based on the data technologies you learned about in this chapter, you should be able to model the domain requirements. With the use of the clustering model technique, you can now create high-performance artificial intelligence systems.

After this, we completed an exercise where we solved the problem of auto syndication for new issues. We also looked at an example regarding how to identify acquirers and targets.

In the next chapter, we will focus on portfolio management, asset management, and a few artificial techniques that are suitable in the domain of portfolio management.

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