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

Network building and analysis using Neo4j

As sell-side analysts, besides finding out the primary impact of news on the company, we should also find out the secondary effect of any news. In our example, we will find out the suppliers, customers, and competitors of any news on the stocks.

We can do this using three approaches:

  • By means of direct disclosure, such as annual reports
  • By means of secondary sources (media reporting)
  • By means of industry inferences (for example, raw materials industries, such as oil industries, provide the output for transportation industries)

In this book, we use direct disclosure from the company to illustrate the point.

We are playing the role of equity researchers for the company stock, and one of our key roles is to understand the relevant parties' connections to the company. We seek to find out the related parties of the company—Duke Energy—by reading the company...