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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

Providing a financial performance forecast using macroeconomic scenarios

One of the key jobs of a CFO is to provide a forecast for financial performance. So, how is AI going to change this job? We will build on what we know about finance in terms of helping with financial projections for accounting rules between items and add the predictive capability of our age to improve it.

As the CFO of the listed firm, one of our key aspects is to provide management and analyst guidance for forward-looking financials. Hypothetical data is handcrafted by the author. This seeks to emulate what the accounting system looks like.

In this section, we will look at how to forecast the financial performance of the firm.

Implementation steps

In this section, we will learn how to derive financial performance forecasts using macroeconomic scenarios. The steps are as follows:

  1. Initialize the tickers in each industry by loading them from CSV files and importing...
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