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

Demand forecasting using time series analysis

In this section, we will take a look at the first example of forecasting the demand for electricity consumption, and predict the energy expenses using time series analysis. We will start with a brief problem statement and define steps to solve the problem. This will give you a better understanding of how to find solutions to problems using time series analysis.

Today, electricity or energy is a very basic necessity for all of us. We use electricity and pay bills. Now, as a customer, we want to analyze electricity consumption and predict future consumption and predict energy expenses. This is the problem that we will solve in this section.

Time series analysis is the optimal approach for solving problems similar to the one defined in the preceding problem statement. Machine learning models need large datasets to be fed before the actual solution is derived. These large datasets are used by machine learning models to...