更新时间：2021-06-18 18:34:10
封面
版权信息
About Packt
Why subscribe?
Contributors
About the authors
About the reviewers
Packt is searching for authors like you
Preface
Who this book is for
What this book covers
To get the most out of this book
Get in touch
Section 1: Quick Review of AI in the Finance Industry
The Importance of AI in Banking
What is AI?
Understanding the banking sector
Importance of accessible banking
Applications of AI in banking
Summary
Section 2: Machine Learning Algorithms and Hands-on Examples
Time Series Analysis
Understanding time series analysis
M2M communication
The basic concepts of financial banking
AI modeling techniques
Demand forecasting using time series analysis
Procuring commodities using neural networks on Keras
Using Features and Reinforcement Learning to Automate Bank Financing
Breaking down the functions of a bank
Metrics of model performance
Building a bankruptcy risk prediction model
Funding a loan using reinforcement learning
Mechanizing Capital Market Decisions
Understanding the vision of investment banking
Basic concepts of the finance domain
Finding the optimal capital structure
Providing a financial performance forecast using macroeconomic scenarios
Predicting the Future of Investment Bankers
Basics of investment banking
Understanding data technologies
Clustering models
Auto syndication for new issues
Identifying acquirers and targets
Automated Portfolio Management Using Treynor-Black Model and ResNet
Financial concepts
Understanding the Markowitz mean-variance model
Exploring the Treynor-Black model
Portfolio construction using the Treynor-Black model
Predicting the trend of a security
Sensing Market Sentiment for Algorithmic Marketing at Sell Side
Understanding sentiment analysis
Sensing market requirements using sentiment analysis
Network building and analysis using Neo4j
Building Personal Wealth Advisers with Bank APIs
Managing customer's digital data
The Open Bank Project
Performing document layout analysis
Cash flow projection using the Open Bank API
Using invoice entity recognition to track daily expenses
Mass Customization of Client Lifetime Wealth
Financial concepts of wealth instruments
Ensemble learning
Predict customer responses
Building a chatbot to service customers 24/7
Knowledge management using NLP and graphs
Real-World Considerations
Summary of techniques covered
Impact on banking professionals regulators and government
How to come up with features and acquire the domain knowledge
IT production considerations in connection with AI deployment
Where to look for more use cases
Which areas require more practical research?
Other Books You May Enjoy
Leave a review - let other readers know what you think
