Section 2: Machine Learning Algorithms and Hands-on Examples

In this section, we will go through the applications of AI in various businesses and functions of the banking industry. The last chapter is the practical yet theoretical chapter in which I will share how I came up with the features and areas of AI applications in the field of finance. It is important for an AI engineer to develop a model with the right features, yet not get too technical in terms of programming, as it can serve as a timeless guide on how to select the appropriate features regardless of the technology.

This section comprises the following chapters:

• Chapter 2, Time Series Analysis
• Chapter 3, Using Features and Reinforcement Learning to Automate Bank Financing
• Chapter 4, Mechanizing Capital Market Decisions
• Chapter 5, Predicting the Future of Investment Bankers
• Chapter 6, Automated Portfolio Management Using Treynor-Black Model and ResNet
• Chapter 7, Sensing Market Sentiment for Algorithmic Marketing at Sell Side
• Chapter 8, Building Personal Wealth Advisors with the Bank API
• Chapter 9, Mass Customization of Client Lifetime Wealth
• Chapter 10, Real-World Considerations