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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

The basic concepts of financial banking

Before we move full steam aheadinto anotherexample,we will first craft out our data, AI, and business techniques and knowledge. If you are familiar with all of these concepts, feel free to skip this section.

Financial knowledge is a good place to start to understand how our decisions in forecasting business activities impact financial decision-making in non-financial firms. Additionally, when predicting future activities using a machine learning model, we also learn how the finance industry can prepare for this future volume of business. What financing does to help with core business activities in non-financial firms is covered in the following section.

The functions of financial markets – spot and future pricing

Financial markets, such as exchanges, play the role of markets for products to be exchanged. For example, consider commodities such as natural gas—we can either buy it directly from sellers...

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