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Hands-On Artificial Intelligence for Banking

Hands-On Artificial Intelligence for Banking

By : Jeffrey Ng , Subhash Shah
4.3 (3)
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Hands-On Artificial Intelligence for Banking

Hands-On Artificial Intelligence for Banking

4.3 (3)
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)
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1
Section 1: Quick Review of AI in the Finance Industry
3
Section 2: Machine Learning Algorithms and Hands-on Examples

Auto syndication for new issues

If there are issues, there are investors behind them. Traditional investment banks will hire a group of professionals called the syndication desk to handle the allocation of security issues to investors who can buy these shares and bonds.

If we consider the role of the syndication desk of the investment bank, our work will be to identify the cornerstone investors of the upcoming new issues with Duke Energy, as the CFO has the funding needs in equities. To do so, we will use the institutional holding data of US stocks from SEC filing via Quandl/Sharadar, which will help us find out the investment preferences of investors who share similar interests and match those with the investors who also hold similar stocks, such as Duke Energy.

With regard to who to sell to, we will take the largest investors of US stocks as our universe of investors. The syndicated desk's job is to sell the major position of any equity issues to these investors...

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