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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

Understanding the vision of investment banking

Before we look at the basic concepts of the financial domain, we have to understand the vision of investment banking. The future of investment banking depends on how accurately the future financial performance and behaviors of companies are estimated, as well as how the key factors for the businesses are captured in the model as features. Distributing securities to investors will be automated, as will the syndication desk. The next two chapters will go through the changes that will be made on the client side in regards to their capital decisions, as well as the change on the investment bankers side regarding how to use the model to source investors so that they support the clients' capital needs (clients who raise capital via debt or equity issues are called issuers), as well as predicting the M&A needs of clients based on the financial aspects.

Performance of investment banking-based businesses

Once all these...

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