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Hands-On Artificial Intelligence for Banking

You're reading from  Hands-On Artificial Intelligence for Banking

Product type Book
Published in Jul 2020
Publisher Packt
ISBN-13 9781788830782
Pages 240 pages
Edition 1st Edition
Languages
Authors (2):
Jeffrey Ng Jeffrey Ng
Profile icon Jeffrey Ng
Subhash Shah Subhash Shah
Profile icon Subhash Shah
View More author details
Toc

Table of Contents (14) Chapters close

Preface 1. Section 1: Quick Review of AI in the Finance Industry
2. The Importance of AI in Banking 3. Section 2: Machine Learning Algorithms and Hands-on Examples
4. Time Series Analysis 5. Using Features and Reinforcement Learning to Automate Bank Financing 6. Mechanizing Capital Market Decisions 7. Predicting the Future of Investment Bankers 8. Automated Portfolio Management Using Treynor-Black Model and ResNet 9. Sensing Market Sentiment for Algorithmic Marketing at Sell Side 10. Building Personal Wealth Advisers with Bank APIs 11. Mass Customization of Client Lifetime Wealth 12. Real-World Considerations 13. Other Books You May Enjoy

The Open Bank Project

The world's most advanced policy that allows consumers to consolidate their own data is called the Open Banking Project. It started in the UK in 2016, following the European's Directive PSD2 – the revised Payment Services Directive (https://www.ecb.europa.eu/paym/intro/mip-online/2018/html/1803_revisedpsd.en.html). This changed the competitive landscape of banks by lowering the entry barrier in terms of making use of banks' information for financial advisory reasons. This makes robo-advisors a feasible business as the financial data that banks contain is no longer segregated.

The challenge with this project is that the existing incumbent dominant banks have little incentive to open up their data. On the consumer side, the slowness in data consolidation impacts the economic values of this inter-connected network of financial data on banking services. This obeys Metcalfe's Law, which states that the value...

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