Book Image

Hands-On Artificial Intelligence for Banking

By : Jeffrey Ng, Subhash Shah
Book Image

Hands-On Artificial Intelligence for Banking

By: Jeffrey Ng, Subhash Shah

Overview of this book

Remodeling your outlook on banking begins with keeping up to date with the latest and most effective approaches, such as artificial intelligence (AI). Hands-On Artificial Intelligence for Banking is a practical guide that will help you advance in your career in the banking domain. The book will demonstrate AI implementation to make your banking services smoother, more cost-efficient, and accessible to clients, focusing on both the client- and server-side uses of AI. You’ll begin by understanding the importance of artificial intelligence, while also gaining insights into the recent AI revolution in the banking industry. Next, you’ll get hands-on machine learning experience, exploring how to use time series analysis and reinforcement learning to automate client procurements and banking and finance decisions. After this, you’ll progress to learning about mechanizing capital market decisions, using automated portfolio management systems and predicting the future of investment banking. In addition to this, you’ll explore concepts such as building personal wealth advisors and mass customization of client lifetime wealth. Finally, you’ll get to grips with some real-world AI considerations in the field of banking. By the end of this book, you’ll be equipped with the skills you need to navigate the finance domain by leveraging the power of AI.
Table of Contents (14 chapters)
1
Section 1: Quick Review of AI in the Finance Industry
3
Section 2: Machine Learning Algorithms and Hands-on Examples
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...