Research Seminar Series – Talk 2

Date: 31 August 2021 (TUE)
Time: 4:00pm – 6:00pm (GMT +8, HK Time)
Conducted via Zoom

Professor Douglas Arner

Professor Douglas Arner

Kerry Holdings Professor in Law, Faculty of Law, HKU
Associate Director of HKU-SCF FinTech Academy

Covid-19, Digital Finance, Financial Inclusion and the UN Sustainable Development Goals

Abstract:
In a recent paper, we argue financial technology (FinTech) is the key driver for financial inclusion, which in turn underlies sustainable balanced development, as embodied in the UN Sustainable Development Goals (SDGs). The full potential of FinTech to support the SDGs may be realized with a progressive approach to the development of underlying infrastructure to support digital financial transformation. Our research suggests that the best way to think about such a strategy is to focus on four primary pillars. The first pillar requires the building of digital identity, simplified account opening and e-KYC systems, supported by the second pillar of open interoperable electronic payments systems. The third pillar involves using the infrastructure of the first and second pillars to underpin electronic provision of government services and payments. The fourth pillar – design of digital financial markets and systems – supports broader access to finance and investment. Implementing the four pillars is a major journey for any economy, but one which has tremendous potential to transform not only finance but economies and societies, through FinTech, financial inclusion and sustainable balanced development. This project will monitor the implementation and impact of this strategy.

Professor S.M. Yiu

Professor S.M. Yiu

Professor at Department of Computer Science, Faculty of Engineering, HKU

Deputy director of HKU-SCF FinTech Academy

A Visualization Assisted Abnormal Trading Detection System for Multi-crypto Currencies

Abstract:
Up to now, there are thousands of cryptocurrencies exist in the market, including bitcoin, Ether. But cryptocurrencies impose a critical threat to existing monetary systems due to its anonymity in nature, for examples, money laundry and making profits by disseminating rumors. In this project, we aim at designing and implementing a system to assist the analysis of detecting abnormal transactions in crypto-currencies. This system has two objectives. The first one is to allow investigators to visualize the problematic transaction clusters in a user-friendly manner. There is no existing free tools that allow a user to identify these problematic transaction clusters easily. The second objective is to allow investigators (e.g. investigators from law-enforcement units and/or commercial financial institutes) to receive warnings from our systems. That is, we hope to automatically identify some abnormal transaction clusters and provide warnings to the investigators. Technically, our system integrates data collection, data analysis, and data visualization to provide stakeholders (including exchanges and investors) with effective information about crypto-currencies so as to help them make rational decisions (in addition to the crime case investigation of law enforcement units).