Novel Financial Applications of Machine Learning and Deep Learning: Algorithms, Product Modeling, and Applications

Preface
	Part 1: Recent Developments in FinTech
	Part 2: Financial Risk Prediction Using Machine Learning
	Part 3: Financial Time-Series Forecasting
	Part 4: Emerging Technologies in Financial Education and Healthcare
Contents
Part I: Recent Developments in FinTech
	FinTech Risk Management and Monitoring
		1 Introduction
		2 Definition of FinTech
		3 What Is FinTech Risk?
		4 Importance of Maintaining FinTech Securities
		5 Risks Behind the Rapid Development of FinTech
			5.1 Cyberattack
			5.2 Data Privacy Risk
			5.3 Data Misuse and Quality
			5.4 Technical Risks
			5.5 Operational Risk
			5.6 Credit Risk
			5.7 Market Risk
			5.8 Liquidity Risk
			5.9 Regulatory Risk
		6 FinTech Risk Management, Monitoring, and Applications
			6.1 FinTech Risks Management
				6.1.1 Identify and Categorize Fintech Risks
				6.1.2 Risks Measurement
				6.1.3 Risk Mitigation Plan Focused on Anti-Fraud Methods and Technological Model
				6.1.4 Analysis and Mitigation
				6.1.5 Monitor and Supervision the Performance of Models
			6.2 Key Regulatory Technology and Applications
				6.2.1 New Encryption Technology
				6.2.2 Blockchain Technology
				6.2.3 Machine Learning Technology
				6.2.4 Big Data Technology
			6.3 Main Applications of Regulatory Technology
				6.3.1 Smart Supervision
				6.3.2 Fraud Prediction and Prevention
				6.3.3 Data Management
				6.3.4 Transaction Monitoring
		7 Challenges of FinTech Risk Management
		8 Conclusion
		References
	Digital Transformation of Supply Chain with Supportive Culture in Blockchain Environment
		1 Introduction
		2 Literature Review
		3 Methodology of the Study
		4 Analysis and Interpretation
			4.1 Digital Transformation of Supply Chain
			4.2 Digital Transformation of Supply Chain in Supportive Culture
			4.3 Blockchain and Supply Chain Management
		5 Findings
		6 Discussion
		7 Conclusion, Theoretical Contribution, Policy Implications, and Future Work
			7.1 Conclusion
			7.2 Theoretical Contribution
			7.3 Policy Implications
			7.4 Future Work
		References
	Integration of Artificial Intelligence Technology in Management Accounting Information System: An Empirical Study
		1 Introduction
		2 Literature Review
		3 Artificial Neural Network (ANN)
		4 Proposed Model
		5 Conclusion
		References
	The Impact of Big Data on Accounting Practices: Empirical Evidence from Africa
		1 Introduction
		2 Literature Review
		3 Research Hypothesis
			3.1 Big Data and Financial Reporting Relationships
			3.2 The Impact of Big Data on Performance Management
			3.3 Big Data and Corporate Budgeting Relationships
			3.4 Big Data and Audit Evidence Relationships
			3.5 Big Data and Risk and Fraud Management Relationships
			3.6 Research Framework
		4 Research Methods and Data
			4.1 Population and Sample
			4.2 Questionnaires
			4.3 Measurement of Big Data
			4.4 Measurement of Accounting and Auditing Practices
			4.5 Methods
		5 Empirical Results and Findings
			5.1 Results of Big Data, Accounting, and Auditing Relationships
		6 Discussion on Results
			6.1 Theoretical Contribution
			6.2 Policy Implications
		7 Conclusion, Limitations, and Further Studies
		References
Part II: Financial Risk Prediction Using Machine Learning
	Using Outlier Modification Rule for Improvement of the Performance of Classification Algorithms in the Case of Financial Data
		1 Introduction
		2 Related Literature
		3 Materials and Methods
			3.1 Statistical Methods to Be Compared
			3.2 Proposed Method
		4 Results
			4.1 Simulated Data Analysis
			4.2 Credit Card Default Data (CCDD)
			4.3 Taiwan Credit Default Data
			4.4 PAK Credit Default Data
		5 Discussion
		6 Conclusion
		References
	Default Risk Prediction Based on Support Vector Machine and Logit Support Vector Machine
		1 Introduction
		2 Literature Review
		3 Methodology
			3.1 Datasets
			3.2 Forecast Algorithms
			3.3 Performance Measures
		4 Results
			4.1 Description of the Data
			4.2 Prediction of Credit Risk
			4.3 Comparative Analysis of Prediction Models
		5 Discussion
		6 Conclusion
		References
	Predicting Corporate Failure Using Ensemble Extreme Learning Machine
		1 Introduction
		2 Research Methodology
			2.1 Extreme Learning Machine
			2.2 Ensemble Techniques
				2.2.1 Multiple Classifiers Technique
				2.2.2 Bagging
				2.2.3 Boosting
				2.2.4 Random Subspace
		3 Experimental Design
			3.1 Data
			3.2 Variables
			3.3 Evaluation Metrics
		4 Results
			4.1 Further Validation
		5 Conclusion
		Appendices
			Appendix 1
			Appendix 2
		References
	Assessing and Predicting Small Enterprises´ Credit Ratings: A Multicriteria Approach
		1 Introduction
		2 Methodology
			2.1 Establishment of a Credit Rating System
			2.2 Solution to Credit Scoring
			2.3 Dividing Credit Ratings of Loan Customers
		3 Empirical Analysis
			3.1 Sample Selection and Data Sources
			3.2 Credit Rating of Small Wholesale and Retail Enterprises
		4 Conclusion
		References
Part III: Financial Time-Series Forecasting
	An Ensemble LGBM (Light Gradient Boosting Machine) Approach for Crude Oil Price Prediction
		1 Introduction
		2 Literature Review
		3 Research Methodology
			3.1 Dataset
			3.2 Description of the Algorithms Used in Analysis
			3.3 Performance Measures
		4 Results and Discussion
		5 Conclusion and Future Work
		References
	Model Development for Predicting the Crude Oil Price: Comparative Evaluation of Ensemble and Machine Learning Methods
		1 Introduction
		2 Related Literature
		3 Methodology
			3.1 Dataset
			3.2 Description of the Algorithms
			3.3 Performance Measures
		4 Results and Discussion
		5 Conclusion and Future Work
		References
Part IV: Emerging Technologies in Financial Education and Healthcare
	Discovering the Role of M-Learning Among Finance Students: The Future of Online Education
		1 Introduction
		2 Literature Review on Mobile Technologies in Teaching
		3 The Impact of M-Learning on Finance Students
		4 Available Mobile Applications for Online Platforms
		5 Online Platforms for University Students
		6 The Effect of Implementing M-Learning in Education
		7 A Projection of the Available Digital Online Contents in the Future
		8 The Development in Education by Virtue of M-Learning
		9 The Affordability and Availability for Pursuing Studies as a Finance Student
		10 Conclusion
		References
	Exploring the Role of Mobile Technologies in Higher Education: The Impact of Online Teaching on Traditional Learning
		1 Introduction
		2 Literature Review on Mobile Technologies in Teaching
		3 The Influence of Mobile Technologies in Teaching
		4 Mobile Technologies Available via an Online Platform
		5 Popular Applications in Higher Education
		6 Higher Education from Online to Offline Setting
		7 The Impacts of Mobile Technologies on University Students
		8 The Impacts of Variation in Assessment in Higher Education
		9 Traditional, Online, or Blended Learning?
		10 Financial Profitability and Complexity Among Learners
			10.1 Financial Profitability
			10.2 Financial Complexity
		11 Conclusion
		References
	Knowledge Mining from Health Data: Application of Feature Selection Approaches
		1 Introduction
		2 Related Works
		3 Material and Methods
			3.1 Datasets
			3.2 Feature Selection Approaches
		4 Results and Discussion
		5 Conclusion
		References