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

Impact on banking professionals, regulators, and government

We have embarked on a long journey through commercial banking (Chapter 2, Time Series Analysis and Chapter 3, Using Features and Reinforcement Learning to Automate Bank Financing), investment banking (Chapter 4, Mechanizing Capital Market Decisions and Chapter 5, Predicting the Future of Investment Bankers), security sales and trading (Chapter 6, Automated Portfolio Management Using Treynor-Black Model and ResNet and Chapter 7, Sensing Market Sentiment for Algorithmic Marketing at Sell Side), and consumer banking (Chapter 8, Building Personal Wealth Advisers with Bank APIs and Chapter 9, Mass Customization of Client Lifetime Wealth) within the banking industry. This section accompanies a sample corporate client—Duke Energy—on its journey from commercial banking through to investment banking. In investment banking, we begin by introducing the investment communities who are on the buying side of the securities...