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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
Building Personal Wealth Advisers with Bank APIs

In the previous chapter, we analyzed the behavior of a sell-side of the exchange. We also learned about sentiment analysis and gained in-depth knowledge of the subject by learning how to analyze market needs using sentiment analysis. We then learned a bit about Neo4j, which is a NoSQL database technique. We then used Neo4j to build and store a network of entities involved in security trading.

In this chapter, we will focus on consumer banking and understand the needs of managing customer's digital data. Then, we will learn how to access the Open Bank Project, an open source platform for open banking. After that, we'll look at an example of wrapping AI models around bank APIs. Finally, we will learn about document layout analysis.

We will cover the following topics in this chapter:

  • Managing customer's digital data
  • The Open...
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