We have received more than 30 applications from financial and research institutions. We have now put out five calls for applied research proposals: in econometrics and data science, back-testing methodologies, quantum computing for the financial sector, and explainable AI. Last year, MAS and the industry also began collaborating with MIT Media Lab to do serious FinTech R&D. MAS, industry professionals, and MIT researchers have come together towards developing prototypes that look into applications of AI and distributed ledger technology in the financial sector. They include use cases in smart contracts, trade finance, and central bank digital currencies. And earlier this year, the Intellectual Property Office of Singapore established a FinTech Fast Track initiative for patents. 7/9  BIS central bankers' speeches  Under the Fast Track, FinTech patents can be granted in as quickly as six months, compared to the industry convention which can be up to two years. Once patented in Singapore, applicants can leverage on our global patent highways to expedite the registration of their patents in more than 30 overseas markets. Platforms for Innovation The final piece in FinTech ecosystem - platforms for innovation. Innovation does not occur in isolation. We need platforms to connect people and ideas; problems and solutions; and foster collaboration. One such platform we are excited about is AFIN – the ASEAN Financial Innovation Network. Let’s begin with the problem statement. There are about 1.7 billion adults globally who are unbanked.
If we don’t address these concerns, we will not have the consensus that is necessary to achieve the many benefits of technology. What do we need to get right in data governance? Data must be protected – we must safeguard privacy, confidentiality, and security. Data must be used in a responsible, transparent, and ethical manner. We must be able to explain the results of data driven algorithms. We cannot hide behind the black box. Humans, not machines, are accountable for decisions driven by AI or data analytics. We must ensure that outcomes of data or AI driven processes are ethical, free of bias, and socially acceptable. Only then, can we create an ecosystem where data flows seamlessly in a trusted manner. MAS has been actively working with the industry to develop principles to guide the responsible use of data in financial services. We are pleased to release today a set of principles to promote Fairness, Ethics, Accountability & Transparency, or FEAT, in the use of AI and data analytics. I’m told this is the first of its kind in the world – where the regulator and industry have come together to set guidance on the responsible use of AI and data analytics. And I am sure this is a living document that will be continually updated as we learn more. Next, on the international front: we need more data connectivity, and less data localisation. This is a serious risk. Data localisation measures are on the rise around the world.