Artificial Financial Intelligence in China (Financial Mathematics and Fintech)

Preface
Acknowledgments
Contents
Chapter 1: FinTech Towards Intelligent Finance
	1.1 The Rise of AI Finance
		1.1.1 Global Trends in Artificial Intelligence Development
		1.1.2 What is Intelligent Finance?
		1.1.3 Features of Intelligent Finance
			1.1.3.1 Self-Learning Intelligent Technology
			1.1.3.2 Ecological Cooperation with Closed-Loop Data
			1.1.3.3 Technology Driven Business Innovation
	1.2 Application of Artificial Intelligence in the Financial Field
		1.2.1 Improved Efficiency of Financial Transactions
		1.2.2 Provision of Intelligent Financial Management Service
		1.2.3 Development of a Disruptive Business Model for the Insurance Industry
		1.2.4 Improved Customer Service Experience
		1.2.5 Robotic Process Automation
		1.2.6 Information Extraction and Compliance and Fraud Prevention Using Image Recognition
		1.2.7 Improved Credit Scoring and Credit Loan Services
	1.3 The Development Stages of FinTech in China
		1.3.1 Computerized Financial Services
		1.3.2 Financial Informatization
		1.3.3 Internet Finance
		1.3.4 Intelligent Finance
	1.4 The Impact of Artificial Intelligence on the Financial Industry
		1.4.1 Crowding Out Risks Introduced by Disruptive Technologies
		1.4.2 Challenges to Data Security and Personal Privacy Protection
		1.4.3 The Abuse of Facial Recognition Technology
		1.4.4 Technical Risks Caused by Algorithm Black Box and Algorithm Discrimination
		1.4.5 The Humanized Development of Artificial Intelligence
Chapter 2: Scientific and Technological Supervision of Artificial Intelligence
	2.1 The International Status of Artificial Intelligence Supervision
		2.1.1 The USA-Guide by Framework and Legislate Normatively
		2.1.2 The European Union-Rules First, Focus on the Protection of Human Rights
			2.1.2.1 The EU´s Objective in Artificial Intelligence: Assess Which Technologies Pose a Threat to Fundamental Human Rights
			2.1.2.2 Chief Concern of the European Commission: Ethical Standards
			2.1.2.3 European Commission Supervision of Artificial Intelligence: A Process of Continuous Exploration
			2.1.2.4 The EU´s Existing Laws and Regulations on the Supervision of FinTech
		2.1.3 The United Kingdom-Supervision Within the Framework of Laws and Guidelines
		2.1.4 Canada-Lead by Strategies and Guide by Principles
			2.1.4.1 Guiding Principles for Artificial Intelligence
			2.1.4.2 List of Artificial Intelligence Suppliers
			2.1.4.3 Algorithmic Impact Assessment (AIA)
			2.1.4.4 Directive on Automated Decision-Making
			2.1.4.5 Strategic Plan for Information Management and Information Technology 2017-2021
		2.1.5 Japan-Promote Development with Supervision and Focus on Employees´ Ethics
			2.1.5.1 Unique Aspects in the Application of Artificial Intelligence in Japan
			2.1.5.2 Japan´s Artificial Intelligence Society 5.0
		2.1.6 Hong Kong-Early Stages of Supervision and the Clarification of Basic Principles
		2.1.7 Singapore-Guided by Plans and Extensive Cooperation
	2.2 Development Background and Function of ``Artificial Intelligence + Financial Supervision´´
		2.2.1 Background Analysis of ``Artificial Intelligence + Financial Supervision´´
		2.2.2 The Role of ``Artificial Intelligence + Financial Supervision´´
			2.2.2.1 Provide Technical Solutions for Financial Regulatory Agencies to Reduce Regulatory Pressure and Costs
			2.2.2.2 Deal Effectively with the Risks of ``Technology + Finance´´
			2.2.2.3 Give Birth to a New Industry
	2.3 New Risks and New Challenges
		2.3.1 Increased Complexity and Scope of Risk
		2.3.2 Illegal Operation
		2.3.3 Challenges for Financial Consumer Protection
		2.3.4 Insufficient Attention to Warning and Preventive Measures
		2.3.5 Technical Risks and Data Risks
		2.3.6 Regulatory Arbitrage
	2.4 China´s Intelligent Financial Supervision Development Status
		2.4.1 China Banking and Insurance Regulatory Commission Practice
		2.4.2 China Securities Regulatory Commission Practice
		2.4.3 Beijing´s Practice-``Beijing Financial Risk Control Cockpit´´
		2.4.4 Guangzhou, Xi ´an and Tianjin´s Practice- ``Ant Risk Brain´´
		2.4.5 Shenzhen´s Practice-``Lingkun Financial Security Big Data Platform´´
		2.4.6 Ningbo´s Practice- ``Tianluo Diwang´´ Financial Risk Monitoring and Control System
			2.4.6.1 Risk Monitoring
			2.4.6.2 Risk Early Warning
			2.4.6.3 Risk Disposal
			2.4.6.4 Institutional Supervision
			2.4.6.5 Statistical Assessment
		2.4.7 Analysis of Existing Problems in the Development Process of ``Artificial Intelligence + Financial Supervision´´ in China
			2.4.7.1 Insufficient Planning
			2.4.7.2 Lag in Development of Rules and Standards
			2.4.7.3 Insufficient Overall Technical Ability
			2.4.7.4 Risks Inherent in the Technology
			2.4.7.5 Unbalanced Development and Application of Different Systems
	2.5 Policy Suggestions on Artificial Intelligence Research and Development and Application in Financial Supervision
		2.5.1 Understanding the Scope and Ability of ``Artificial Intelligence + Financial Supervision´´
		2.5.2 Formulating a Basic Rule System and Strengthening Standardization
		2.5.3 Building a Risk Early Warning System, and Strengthening the Ability of Financial Regulatory Institutions to Prevent and ...
		2.5.4 Monitoring the Business Behaviours of FinTech Suppliers
		2.5.5 Grasping the New Challenges of Financial Consumer Protection
		2.5.6 Enhancing International Cooperation
Chapter 3: Technical Path of Artificial Intelligence Compliance Efficiency
	3.1 Development Status of CompTech
		3.1.1 The Development Scale of CompTech
		3.1.2 Application Scenarios of CompTech
	3.2 Application of CompTech
		3.2.1 Data Processing and Analysis, Optimization of Compliance Construction
		3.2.2 Identity Verification and Management, Financial Crime Prevention
		3.2.3 Compliance Review and Evaluation, Reduction of Compliance Costs
		3.2.4 Risk Early Warning and Testing, Improved Prediction Ability
	3.3 Challenges and Risks of CompTech
		3.3.1 Limitations of the Algorithm Decision
		3.3.2 Lack of Support System
		3.3.3 Quality and Security of Data and Information
		3.3.4 The Legal Risk of Liability Confirmation
		3.3.5 Policy Suggestions for Promoting the Development of Compliance Technology
			3.3.5.1 Regulatory Big Data Platform
			3.3.5.2 Technical Management to Protect Consumer Rights and Interests
			3.3.5.3 Coordinated Development of Compliance and Supervision
			3.3.5.4 Unified Standards and Improved Supporting Guarantee Mechanism
Chapter 4: Smart Payment in China
	4.1 Application Mode of Smart Payment
		4.1.1 Front-end Application Mode
			4.1.1.1 Smart Account
			4.1.1.2 Tools for Smart Payment
			4.1.1.3 Smart Customer Service
		4.1.2 Back-end Application Mode
			4.1.2.1 Precise Service Provision
			4.1.2.2 Intelligent Regulation
	4.2 Application Scenario of Smart Payment
		4.2.1 Application Scenario of AI Payment Abroad
			4.2.1.1 Application Scenario of AI Payment Abroad in the Financial Industry
			4.2.1.2 Multi-dimensional Application Scenario of AI Payment Abroad
		4.2.2 Application Scenario of AI Payment in China
			4.2.2.1 Application Scenario of AI Payment in China´s Financial Industry
			4.2.2.2 Multi-dimensional Application Scenario of AI Payment in China
	4.3 Strengths and Deficiencies of Smart Payment
		4.3.1 Strengths of AI Payment
			4.3.1.1 Improves Payment Security
			4.3.1.2 Improves Payment Efficiency
			4.3.1.3 Optimizes Supply and Demand Matching
		4.3.2 Deficiencies of AI Payment
			4.3.2.1 Defective Laws and Regulations
			4.3.2.2 Immature Products or Services
			4.3.2.3 Ambiguous Regulatory Position
			4.3.2.4 Insufficient Depth and Breadth of Technology Application
			4.3.2.5 Unbalanced Reserve of Talents
	4.4 Smart Payment Risks
		4.4.1 Information Security Risk
		4.4.2 Legal Risk
		4.4.3 Technical Risk
		4.4.4 Regulatory Risk
		4.4.5 Systemic Risk
	4.5 Policy Suggestions for Developing AI in Payment
		4.5.1 Complete the Legal System
		4.5.2 Stipulate Data Standard
		4.5.3 Clarify Rights and Responsibility of Regulation
		4.5.4 Optimize the Upgrade of AI Technology
		4.5.5 Strengthen Security Assessment
		4.5.6 Cultivate Inter-disciplinary Talent
		4.5.7 Implement Protection Mechanism
Chapter 5: Opportunities, Risks, and Breakdowns Brought by AI to Commercial Banks
	5.1 Commercial Banks and Scientific and Technological Development
		5.1.1 The Relationship Between Commercial Banks and Information Technology
		5.1.2 Weak Spots of Commercial Bank Business
		5.1.3 Digital Transformation of Commercial Banks
	5.2 Application of AI in Commercial Banks
		5.2.1 Motivation for Commercial Banks to Apply AI
		5.2.2 Current Situation of AI Application in Commercial Banks
			5.2.2.1 Intelligent Marketing
			5.2.2.2 Intelligent Credit
			5.2.2.3 Intelligent Customer Service
			5.2.2.4 Intelligent Investment Advisor
			5.2.2.5 Intelligent Operation
			5.2.2.6 Intelligent Risk Control
		5.2.3 The Positive Effect of AI Application in Commercial Banks
		5.2.4 Potential Risks of AI Application in Commercial Banks
			5.2.4.1 Traditional Financial Risk
			5.2.4.2 Information Technology Risk
			5.2.4.3 Data Leakage Risk
			5.2.4.4 Market Monopoly Risk
			5.2.4.5 Network Attack Risk
			5.2.4.6 Infringement Risk
			5.2.4.7 Systemic Risk
		5.2.5 Future Development Trend and Possible Obstacles
			5.2.5.1 Unbounded Service
			5.2.5.2 Prompt Response
			5.2.5.3 Personalized Service
			5.2.5.4 Secure Service
			5.2.5.5 Differentiated Service
	5.3 Promoting the Application of AI in Commercial Banks
		5.3.1 Strengthen Top-Level Design and Improve the Governance System
		5.3.2 Steady and Orderly Explorations to Build an Inclusive and Prudent Chinese ``Regulatory Sandbox´´
		5.3.3 Develop Regulatory Technology to Enhance the Ability of Risk Identification, Prevention, and Disposal
		5.3.4 Strengthen Data Governance, Balance the Efficiency of Data Use, and Personal Privacy Protection
		5.3.5 Strengthen the Training of FinTech Talents
		5.3.6 Strengthen Macro-Prudential Management and Guard against Systemic Risks
Chapter 6: Robo-advisor and Expert Advisor
	6.1 Robo-advisor
		6.1.1 Robo-advisor-An Overview
		6.1.2 Development History
		6.1.3 Advantages of Robo-advisor
		6.1.4 The Foundations of Robo-advisor Technology
			6.1.4.1 Data
			6.1.4.2 Investment Model and Algorithm
		6.1.5 Process of Robo-advisor Service
		6.1.6 Development of the Robo-advisor in China
		6.1.7 Laws, Regulations, and Supervision Relevant to the Robo-advisor in China
	6.2 Expert Advisor
		6.2.1 Programming Trading
			6.2.1.1 Concepts and Main Types
			6.2.1.2 Programming Trading Strategies
		6.2.2 Expert Advisor
			6.2.2.1 Advantages
			6.2.2.2 Challenges
		6.2.3 Supervision of Programming Trading and Expert Advisors in China
Chapter 7: Intelligent Finance Wealth Management in China
	7.1 Current Status of Online Wealth Management in China
		7.1.1 Nature of Online Wealth Management
		7.1.2 Customer Orientation of Online Wealth Management
		7.1.3 Development of China´s Online Wealth Management Market
			7.1.3.1 Pre-2008: The Dominant Role of Bank Wealth Management
			7.1.3.2 2008 to 2013: Emphasis on Investment Diversification, and Emergence of Online Wealth Management
			7.1.3.3 2013-2016: The Rise of Internet Wealth Management Products
			7.1.3.4 2016 Onwards: Development of AI and of Intelligent Wealth Management Services
	7.2 Driving Factors of the Development of China´s Intelligent Wealth Management Market
		7.2.1 Political Factors
		7.2.2 Economic Factors
			7.2.2.1 Increased Demand for Intelligent Wealth Management Services
			7.2.2.2 Role of the New Middle class
			7.2.2.3 Increased Customer Choice
			7.2.2.4 Limitations of Traditional Wealth Management
		7.2.3 Social Factors
		7.2.4 Technical Factors
	7.3 Problems of the Intelligent Wealth Management Market in China
		7.3.1 Demand Side Problems
			7.3.1.1 Total Quantity
			7.3.1.2 Structure
		7.3.2 Weaknesses of Traditional Wealth Management Services
			7.3.2.1 Insufficient Service Supply
			7.3.2.2 Poor Accuracy
			7.3.2.3 Value Orientation
			7.3.2.4 Inaccurate Information from Users
	7.4 Intelligent Wealth Management Service
		7.4.1 Development Mode
		7.4.2 Core Factors of Intelligent Wealth Management Service
			7.4.2.1 Accurate User Profile
			7.4.2.2 Financial Professional Competence
			7.4.2.3 User Intention Insight
			7.4.2.4 Intelligent Interaction Capability
			7.4.2.5 Information Service Capability
		7.4.3 Application of AI in Intelligent Data Analysis
		7.4.4 Intelligence Grading of Intelligent Wealth Management Service System
			7.4.4.1 Interactive Experience
			7.4.4.2 Intelligent Matching
			7.4.4.3 Investor Education
			7.4.4.4 Level of Different Types of Enterprise Business intelligence Value
			7.4.4.5 Strategic Significance of Intelligent Wealth Management Service Ecosystem
Chapter 8: Intelligent Finance in China´s Financial Market
	8.1 Overview of China´s Securities Industry
		8.1.1 Current Status of the Development of Securities Companies
			8.1.1.1 Overview
			8.1.1.2 Profit Model
		8.1.2 Problems in the Development of China´s Securities Industry
			8.1.2.1 Direct Public Participation with Insufficient Scientific Analysis
			8.1.2.2 Challenges for Retail Business of Securities Companies
			8.1.2.3 Dependence on Brokerage
			8.1.2.4 Technological Obstacles to Optimized and Personalized Asset Management
		8.1.3 Application of AI in the Securities Industry
			8.1.3.1 Customer Classification
			8.1.3.2 Intelligent Customer Service
	8.2 Intelligent Finance in China´s Bond Market
		8.2.1 Current Situation of China´s Bond Market
			8.2.1.1 Overview
			8.2.1.2 Primary Market Operation
			8.2.1.3 Secondary Market Operation
			8.2.1.4 Defaults in the Bond Market
		8.2.2 Problems in the Development of China´s Bond Market
			8.2.2.1 Market Segmentation
			8.2.2.2 Inflated Rating, Lagged Adjustment, and Insufficient Risk Warning
			8.2.2.3 Low Transparency
		8.2.3 Role of AI in the Bond Market
			8.2.3.1 Facilitates Integration of Market Information Resources, Enhances Bond Market Supervision
			8.2.3.2 Facilitates Upgrading of Credit Risk Control System
			8.2.3.3 Improves Transparency of the Bond Market
	8.3 Intelligent Finance of China´s Insurance Industry
		8.3.1 Overview of China´s Insurance Industry
			8.3.1.1 Steady Increase in Size
			8.3.1.2 Ample Room for Growth
		8.3.2 Problems in the Development of China´s Insurance Industry
			8.3.2.1 Weak Public Insurance Awareness
			8.3.2.2 Severe Competitiveness in Homogeneous Products
			8.3.2.3 High Costs
			8.3.2.4 Complicated Procedures
			8.3.2.5 Backwardness of the Insurance Service Model
		8.3.3 Application of AI in Insurance
			8.3.3.1 Application Prospects
			8.3.3.2 Application Scope
			8.3.3.3 Application Cases
Bibliography