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

Procuring commodities using neural networks on Keras

In this section, we will take a look at another more complex example. As before, we will define the problem statement and then define steps to solve the problem.

In this example, we want to forecast the procurement of commodities based on historical data. The commodity that we are going to use is natural gas. In the case of natural gas, we do not have any control over its pricing because it is a hugely globalized commodity. However, we can still set up the internal procurement strategy when the pricing of the natural gas hits a certain range. The profitability ratio target will constrain the maximum pricing we can pay for the raw material to be profitable for the owners of the firm. We will track the profitability ratio, which is the ratio of cost of natural gas to sales.

Let's understand this pricing constraint with an example. In this example, we assume that for each dollar spent where the unit cost...