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  • Learn the basics of banking with the help of Python
  • Automate commercial bank pricing with reinforcement learning
  • Perform technical analysis using convolutional layers on Keras
  • Use natural language processing (NLP) to listen to market sentiment and visualize it using graph databases
  • Deploy a robot advisor to manage your personal finance via Openbank
  • Unlock the history and future drivers of AI adoption in banking via coding examples
  • Learn how to obtain financial data from commerical, open and internal sources

Remodeling your outlook on banking begins with educating yourself about the latest and most effective approach; which in this case is artificial intelligence. Hands-On Artificial Intelligence for Banking is a step-oriented guide that will help you carve a bright future in the banking domain.

This book will help you to apply AI to make your banking services smoother, more cost efficient and accessible to the client. The book will focus on both the client and server side uses of AI. You’ll begin by understanding the importance of AI and the revolution it has bought about in the banking industry. Next, you’ll explore how to use time series analysis and reinforcement learning to automate client procurements and banking and finance decisions. When you’ve worked through this section, you can gear up to learn about mechanizing capital market decisions, using automated portfolio management systems and predicting the future of investment banking. Building personal wealth advisors and mass customization of client lifetime wealth are some of the other concepts that you will explore. Approaching the end of the book, you’ll cover some real-world AI considerations in the field of banking.

By the end of this book, you will be equipped with the skills to navigate the finance domain by leveraging the power of AI.

  • Understand how to obtain financial data via Quandl or internal systems
  • Automate commercial banking using artificial intelligence and Python programs
  • Implement various artificial intelligence models to make personal banking easy
Page Count 417
Course Length 12 hours 30 minutes
ISBN 9781788830782
Date Of Publication 18 Dec 2020



Mr Jeffrey Ng, CFA, works at Ping An OneConnect, Hong Kong, as the Head of Bank of Banks whose mandate is to advance the use of AI in banking and financial ecosystem. Prior to this, he headed the Data Lab of BNP Paribas Asia-Pacific that built A.I. & Data Analytics solution for businesses and was the Vice-Chairman of the French Chamber of Commerce’s FinTech Committee in Hong Kong. In 2010, being one of the pioneers to apply client analytics in Investment banking, he built the Analytics team for the bank. He had AI projects in retail and commercial banks with PwC Consulting and GE Money. He graduated from Hong Kong Polytechnic University in Computing and Management and holds a MBA in Finance from the Chinese University of Hong Kong.

Subhash Shah

Subhash Shah is an experienced solution architect. With 14 years of experience in software development, he works as an independent technical consultant now. He is an advocate of open source development and its utilization in solving critical business problems. His interests include Microservices architecture, Enterprise solutions, Machine Learning, Integrations and Databases. He is an admirer of quality code and test-driven development (TDD). His technical skills include translating business requirements into scalable architecture and designing sustainable solutions. He is a co-author of Hands-On High Performance with Spring 5, Hands-On AI for Banking and MySQL 8 Administrator’s Guide. He has also been a technical reviewer for other books.