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Hands-On Artificial Intelligence for Banking, published by Packt

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Hands-On Artificial Intelligence for Banking

Hands-On Artificial Intelligence for Banking

This is the code repository for Hands-On Artificial Intelligence for Banking, published by Packt.

A practical guide to building intelligent financial applications using machine learning techniques

What is this book about?

Hands-On Artificial Intelligence for Banking is a must-have guide for AI developers and machine learning experts looking to build intelligent finance-based applications. This guide will give its readers a complete overview of the global banking business with the help of interesting use-cases, and their implementation using popular Python libraries.

This book covers the following exciting features:

  • Automate commercial bank pricing with reinforcement learning
  • Perform technical analysis using convolutional layers in Keras
  • Use natural language processing (NLP) for predicting market responses and visualizing them using graph databases
  • Deploy a robot advisor to manage your personal finances via Open Bank API
  • Sense market needs using sentiment analysis for algorithmic marketing
  • Explore AI adoption in banking using practical examples
  • Understand how to obtain financial data from commercial, open, and internal sources

If you feel this book is for you, get your copy today!

https://www.packtpub.com/

Instructions and Navigations

All of the code is organized into folders.

The code will look like the following:

#list of key intent, product and attribute
product_list = ['deposit','loan']
attribute_list = ['pricing','balance']
intent_list = ['check']
print('loading nlp model')
nlp = spacy.load('en_core_web_md')

Following is what you need for this book: This is one of the most useful artificial intelligence books for machine learning engineers, data engineers, and data scientists working in the finance industry who are looking to implement AI in their business applications. The book will also help entrepreneurs, venture capitalists, investment bankers, and wealth managers who want to understand the importance of AI in finance and banking and how it can help them solve different problems related to these domains. Prior experience in the financial markets or banking domain, and working knowledge of the Python programming language are a must.

With the following software and hardware list you can run all code files present in the book (Chapter 2 - 9).

Software and Hardware List

Chapter Software required OS required
1 - 10 Python 3.5+, PyTorch 1.x, GPU (preferred) Ubuntu
5 - 9 SQLite 3.11 Ubuntu
8 MongoDB Community Edition 1.2.6.10 Ubuntu
7 and 9 Neo4j Community Version Ubuntu

We also provide a PDF file that has color images of the screenshots/diagrams used in this book. Click here to download it.

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Get to Know the Author

Jeffrey Ng, CFA, works at Ping An OneConnect Bank (Hong Kong) Limited as Head of FinTech Solutions. His mandate is to advance the use of AI in banking and financial ecosystems. Prior to this, he headed up the data lab of BNP Paribas Asia Pacific, which constructed an AI and data analytics solution for business, and was the vice-chair of the French Chamber of Commerce's FinTech Committee in Hong Kong. In 2010, as one of the pioneers in applying client analytics to investment banking, he built the analytics team for the bank. He has undertaken 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 an MBA in finance from the Chinese University of Hong Kong.

Subhash Shah works as head of technology at AIMDek Technologies Pvt. Ltd. He is an experienced solutions architect with over 12 years of experience. He holds a degree in information technology. He is an advocate of open source development and its utilization in solving critical business problems at a reduced cost. His interests include microservices, data analysis, machine learning, AI, and databases. He is an admirer of quality code and test-driven development (TDD). His technical skills include, but are by no means limited to, translating business requirements into scalable architecture, designing sustainable solutions, and project delivery. He is a coauthor of MySQL 8 Administrator's Guide and Hands-On High Performance with Spring 5.

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Hands-On Artificial Intelligence for Banking, published by Packt

License:MIT License


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