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)
Section 1: Quick Review of AI in the Finance Industry
Section 2: Machine Learning Algorithms and Hands-on Examples

To get the most out of this book

Before you get started, I assume that you are running Ubuntu 16.04LTS Desktop or above and have done your Python 101 course. Knowledge of how to install the relevant software packages is assumed and will not be covered in this book.

Three database engines (SQLite, MongoDB, and Neo4j) are used in this book. Please make sure that you have them installed.

Regarding data sources, we will get data from ( and a paid subscription to Quandl (Sharadar Core US Equities Bundle ( for chapters 4 and 5, and Sharadar Fund Prices ( for chapters 6 and 7), Twitter's Premium Search ( for chapter 7, and the Open Bank Project ( for chapter 8.