Artificial Intelligence and Big Data for Financial Risk Management: Intelligent Applications (Banking, Money and International Finance)

✍ Scribed by Noura Metawa (editor), M. Kabir Hassan (editor), Saad Metawa (editor)

• Publisher: Routledge
• Year: 2022
• Tongue: English
• Leaves: 249
• Edition: 1
• Category: Library

✦ Synopsis

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.

✦ Table of Contents

Cover
Half Title
Series Page
Title Page
Copyright Page
Table of Contents
List of figures
List of tables
List of contributors
1 Grey Model as a Tool in Dynamic Portfolio Selection: Simple Applications
2 Predicting Financial Statement Fraud Using Artificial Neural Networks
3 Bank Network Credit Model and Risk Management System Based on Big Data Technology
4 Deep Learning in Detecting Financial Statement Fraud: An Application of Deep Neural Network (DNN)
5 Predicting Stock Return Risk and Volatility Using Neural Network: The Case of the Egyptian Stock Exchange
6 Operation Analysis of Financial Sharing Center Based on Big Data Sharing Technology: Taking SF Express as an Example
7 Optimization Algorithms for Multiple-Asset Portfolios with Machine Learning Techniques: Theoretical Foundations of Optimum and Coherent Economic Capital Structures
8 Random Forest and Grey Methodology in Dynamic Portfolio Selection
9 The Role of Blockchain in Financial Applications: Architecture, Benefit, and Challenges
10 Using Computer Blockchain Technology to Analyze the Development Trend of China’s Modern Financial Industry
11 Financial Efficiency Differentiation Based on Data Quantitative Analysis under Big Data Technology
12 Optimization Algorithms for Multiple-Asset Portfolios with Machine Learning Techniques: Practical Applications with Forecasting of Optimum and Coherent Economic Capital Structures
13 An Overview of Neural Network in Financial Risk Management
Index