Artificial Intelligence and Big Data for Financial Risk Management

- Publisher:
- Taylor & Francis Ltd.
- Authors:
-
Noura Metawa
M. Kabir Hassan
Saad Metawa - ISBN:
- 9781003144410
Description:
This book presents a collection of high-quality contributions on the state-of-the-art in artificial intelligence and big data analysis as it relates to financial risk management applications. It brings together, in one place, the latest thinking on an emerging topic and includes principles, reviews, examples and research directions. The book presents numerous specific use-cases throughout, showing practical applications of the concepts discussed. It looks at technologies such as eye movement analysis, data mining or mobile apps and examines how these technologies are applied by financial institutions and how this affects both the institutions and the market. This work introduces students and aspiring practitioners to the subject of risk management in a structured manner. It is primarily aimed at researchers and students in finance and intelligent big data applications, such as intelligent information systems, smart economics and finance applications and the internet of things in a marketing environment.
Index
- Chapter 1: Grey model as a tool in dynamic portfolio selection
- Chapter 2: Predicting Financial Statement Fraud using Artificial Neural Networks
- Chapter 3: Bank Network Credit Model and Risk Management System Based on Big Data Technology
- Chapter 4: Deep Learning in Detecting Financial Statement Fraud
- Chapter 5: Predicting Stock Return Risk and Volatility Using Neural Network
- Chapter 6: Operation Analysis of Financial Sharing Center Based On Big Data Sharing Technology
- Chapter 7: Optimization algorithms for multiple-asset portfolios with machine learning techniques
- Chapter 8: Random Forest and Grey Methodology in Dynamic Portfolio Selection
- Chapter 9: The role of blockchain in financial applications
- Chapter 10: Using Computer Blockchain Technology to Analyze the Development Trend of China's Modern Financial Industry
- Chapter 11: Financial Efficiency Differentiation Based on Data Quantitative Analysis under Big Data Technology
- Chapter 12: Optimization algorithms for multiple-asset portfolios with machine learning techniques
- Chapter 13: An Overview of Neural Network in Financial Risk Management