1. Deciphering Crowdfunding1.1. The Crowdfunding Phenomenon: an Overview
1.1.1. The European Market
1.1.2. The US market
1.1.3. The Asia-Pacific Market
1.2. Crowdfunding State-of-the-Art
1.2.1. Investment Models
1.2.2. Non-investment Models
1.3. New Research Trends: The language of Crowdfunding
1.4. References
2. Addressing Information Asymmetries in Online Peer-to-Peer Lending
2.1. Introduction
2.2. Online Peer-to-Peer Lending Platforms
2.3. Information Asymmetries and Peer to Peer Lending Platforms
2.4. Conclusions and Future Directions for Research
2.5. References
3. Machine learning and AI for risk management
3.1. Introduction
3.2. Machine Learning and AI Techniques for Risk Management
3.3. Machine Learning and AI Applications for Risk Management
3.3.1. Application to Credit Risk
3.3.2. Application to Market Risk
3.3.3. Application to Operational Risk
3.3.4. Application to RegTech
3.4. The Challenges and Future of Machine Learning and AI for Risk Management
3.5. References
4. What Fintech Can Learn from High-Frequency Trading: Economic Consequences, Open Issues and Future of Corporate Disclosure
4.1. Introduction
4.2. High Frequency Trading: Definition and Data
4.2.1. Methodology
4.2.2. Descriptive Statistics
4.3. Results
4.3.1. Thematic Analysis
4.3.2. Impact of HFT
4.3.2.1. Effects on Market Quality
4.3.2.2. HFT's Trading Strategies and Speed
4.3.2.3. Market Structure, Co-location and Regulation after the Flash Crash
4.3.3. HFT Reaction to Corporate Disclosure
4.4. Conclusion and Future Research Directions
4.5. References
5. InsurTech
5.1. Introduction
5.2. How Does Insurance Work?
5.3. The Big Data Paradigm
5.3.1. Telematics
5.3.2. Wearables
5.3.3. Smart Homes and the Internet of Things (IoT)
5.3.4. Big Data: Trustworthiness and Privacy Concerns
5.4. Artificial Intelligence
5.4.1. Machine Learning and AI in the Underwriting Process
5.4.2. AI in Claims Management Process
5.4.3. AI in Customer Interaction
5.5. Distributed Ledger Technologies
5.5.1. Improving Current Processes Using DLTs
5.5.2. P2P Insurance
5.6. Conclusion
5.7. References
6. Understanding RegTech for Digital Regulatory Compliance
6.1. Introduction
6.2. Business Drivers of RegTech
6.3. RegTech in Focus: Digital Regulatory Reporting
6.3.1. Phase 1 Digital Regulatory Alerts
6.3.2. Phase 2 Making Regulations Digital
6.3.3. Phase 3 Performing Digital Regulatory Reporting
6.3.4. Phase 4 Creating Meta-Data Models for Semantic Interoperability
6.4. Discussion and Implications
6.5. Conclusion
7. Payment Service Directive II and its Implications
7.1. Introduction
7.2. Background
7.3. EU Initiated Review of the Effectiveness of PSD I
7.3.1. Main Findings of Impact Study
7.4. Payment Services Directive II
7.4.1. Scope of the Directive and the Removal of Exclusions
7.4.2. Authorisation of Payment Institutions
7.4.3. Innovation
7.4.4. Confirmation of Availability of Funds
7.4.5. Enhancing Competition
7.4.6. Customer Protection
7.4.7. Security
7.4.8. Complaints Handling
7.5. European Banking Authority (EBA) Work on PSD II
7.6. Strong Customer Authentication (SCA)
7.6.1. Exemptions for SCA
7.7. Commentary
7.8. References
8. From Transactions to Interactions: Social Considerations for Digital Money
8.1. Introduction
8.2. Affordances of Digital Money
8.3. Opportunities for Interaction
8.3.1. Negotiating Payment
8.3.2. Effects of Intermediation
8.3.3. Collaborative Value Creation
8.4. Social Impacts of Digital Transactions
8.4.1. Sensitive Data Generation and Sharing
8.4.2. Choice Proliferation
8.4.3. Untangling Money and Payment System
8.5. Conclusion
8.6. References
9. Token-based Business Models
9.1. Introduction
9.2. Native Digital Assets
9.3. Crypto Tokens
9.4. Token-based Business Models
9.5. Driving Forces behind the Token-based Business Models
9.6. Crypto Tokens to enhance the Sharing Economy
9.7. References
10. Blockchain beyond Cryptocurrencies
10.1. Introduction
10.2. What is Blockchain?
10.3. Payments and Remittance
10.4. Credit and Lending
10.5. Trading and Settlements
10.6. Compliance
10.7. Conclusion and Avenues for Future Research
10.8. References
