In the new era of fintech, stock exchanges around the globe are actively exploring ways to perform system upgrades and service enhancements. However, most of the existing fintech applications are deployed in the industries of banking, internet finance and digital currencies rather than the securities industry, in which only very few could come up with feasible plans based on specific securities business models.
It is generally believed that blockchain and artificial intelligence (AI) technologies such as intelligent investment advisor (robo-advisor) would be the most applicable in the exchange market.
This report focuses on blockchain and AI applications in the securities industry and explores how these new technologies could be integrated in the areas of investment, trading, clearing and settlement, as well as regulation, with a view to find specific feasible applications of fintech in the capital market.
This report introduces examples of blockchain technology deployed in trading and clearing and settlement businesses, asset rehypothecation business and private equity market as well as the use of AI technology in intelligent/roboinvestment research and advisory services. Each example compares the pros and cons of the new technology and the traditional business model, and the difficulties and challenges arising from the use of blockchain and AI technologies.
There’s also discussion about the principles and tools in the establishment of the regulatory framework for the development of fintech. To a certain extent, the use of fintech may not help reduce the inherent risks in the financial system but rather, may magnify or expose new forms of financial risk. Therefore, regulators should consider how to enable the application of fintech innovations in the securities industry under an appropriate regulatory framework.
This report also discusses the consistency principle in financial regulation. The consistency principle means that financial businesses of the same nature should be subject to the same regulation. Financial services, be they offered in a virtual or real environment, should be governed by the same legal framework. This will ensure fair competition and prevent regulatory arbitrage.
The report discusses the feasibility of using big data, deep learning and knowledge-graph to establish effective regulatory technology systems. It is essential for regulators to build an effective regulatory technology, using big data and AI analysis to strengthen their ability to do macro-analysis of financial institutions and track systematic risks, in order to better monitor and prevent systemic financial risks.