Hands-On Artificial Intelligence for Banking

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

Jeffrey Ng , Subhash Shah , CFA 지음

Packt(GCO Science) 2020년 07월 10일 출간

작품소개

책소개

▶What You Will Learn
- 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

▶Key Features
- 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

▶Who This Book Is For
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.

목차

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

책 속으로

▶What this book covers
- Chapter 1, The Importance of AI in Banking, explains what AI is and discusses its applications in banking. This chapter also provides a detailed introduction to banking as a sector, the complexity of banking processes, and diversification in banking functions.

- Chapter 2, Time Series Analysis, covers time series analysis. This chapter explains time series analysis in detail with examples and explains how the Machine-to-Machine (M2M) concept can be helpful in the implementation of time series analysis.

- Chapter 3, Using Features and Reinforcement Learning to Automate Bank Financing, covers reinforcement learning. It also covers different AI modeling techniques using examples, as well as the business functions of the bank in the context of examples.

- Chapter 4, Mechanizing Capital Market Decisions, discusses the basic financial and capital market concepts. We will look at how AI can help us optimize the best capital structure by running risk models and generating sales forecasts using macro-economic data. The chapter also covers important machine learning modeling techniques such as learning optimization and linear regression.

- Chapter 5, Predicting the Future of Investment Bankers, introduces AI techniques followed by auto-syndication for new issues. We will see how capital can be obtained from interested investors. In the latter section of the chapter, we will cover the case of identifying acquirers and targets―a process that requires science to pick the ones that need banking services.

- Chapter 6, Automated Portfolio Management Using Treynor-Black Model and ResNet, focuses on the dynamics of investors. The chapter discusses portfolio management techniques and explains how to combine them with AI to automate decision-making when buying assets.

- Chapter 7, Sensing Market Sentiment for Algorithmic Marketing at Sell Side, focuses on the sell side of the financial market. The chapter provides details about securities firms and investment banks. This chapter also discusses sentiment analysis and covers an example of building a network using Neo4j.

- Chapter 8, Building Personal Wealth Advisers with Bank APIs, focuses on consumer banking. The chapter explains the requirements of managing the digital data of customers. The chapter also explains how to access open bank APIs and explains document layout analysis.

- Chapter 9, Mass Customization of Client Lifetime Wealth, explains how to combine data from the survey for personal data analysis. The chapter also discusses Neo4j, which is a graph database. In this chapter, we will build a chatbot to serve customers 24/7. We will also look at an example entailing the prediction of customer responses using natural language processing, Neo4j, and cipher languages to manipulate data from the Neo4j database.

- Chapter 10, Real World Considerations, serves as a summary of the AI modeling techniques covered in the previous chapters. The chapter also shows where to look for further knowledge of the domain.

출판사 서평

▶ Preface
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.

작가정보

저자(글) Jeffrey Ng

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.

저자(글) 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.

저자(글) CFA