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

Understanding the vision of investment banking

Before we look at the basic concepts of the financial domain, we have to understand the vision of investment banking. The future of investment banking depends on how accurately the future financial performance and behaviors of companies are estimated, as well as how the key factors for the businesses are captured in the model as features. Distributing securities to investors will be automated, as will the syndication desk. The next two chapters will go through the changes that will be made on the client side in regards to their capital decisions, as well as the change on the investment bankers side regarding how to use the model to source investors so that they support the clients' capital needs (clients who raise capital via debt or equity issues are called issuers), as well as predicting the M&A needs of clients based on the financial aspects.

Performance of investment banking-based businesses

Once all these...