As an indication of the importance of FinTech to Hong Kong’s prospects, the first award made to the Business School under the Research Grants Council’s Theme-based Research Scheme (TRS) is for research in this field. The project will examine the impacts of FinTech on individual investors, financial institutions and the industry to establish a roadmap for transforming the city into a global FinTech hub.
FinTech is reshaping the world economy at an unprecedented pace. Artificial intelligence, blockchain and encryption technologies have transformed the financial industry, challenging decades-old traditional business models in banking, investment, payment, regulation and compliance.
However, it is difficult to imagine Hong Kong maintaining its competitive edge if the city’s finance sector only seeks to replicate practices followed elsewhere, but fails to develop a strategy most suited to its own economy.
The Business School’s TRS project
The Research Grants Council’s funding awards for the TRS aim to focus the research efforts of academic institutions on themes of strategic importance to the long-term development of Hong Kong.
Through their large-scale Theme-based Research Project on FinTech, Professor TAM Kar-yan, Dean of the HKUST Business School, and his multidisciplinary team are seeking a deeper understanding of the interplay between technology and financial services in Hong Kong, and will conduct specific research into blockchain technology, machine learning applications, cybersecurity and risk assessment.
Research team and management structure
Due to the interdisciplinary nature of FinTech, the project is led by experts in accounting, economics, finance, computer science, information systems, and statistics from HKUST, the Chinese University of Hong Kong, City University of Hong Kong and the University of Hong Kong.
Professor Tam heads the Executive Committee which, together with the Academic Advisory Group and the Project Advisory Group, will oversee the teams tackling the eight research tasks that cover blockchain, cybersecurity, risk preference, robo-advising, artificial intelligence (AI)/machine learning, systemic risk, policy on financial innovation, and manpower development.
The Academic Advisory Group consists of leading academics who will advise on research methodology and discuss findings. The Project Advisory Group is made up of representatives from regulators and the industry, who will advise on and help disseminate the findings. The Executive Committee’s brief covers the day-to-day operations of the project.
Project Tasks
The team responsible for Task 1 will investigate whether the benefits claimed for blockchain, or distributed ledger technology, are real. These benefits include the reduction of transaction fees, intrinsic trustworthiness, and decentralization.
Task 2 seeks to find out whether compulsory cybersecurity protection schemes for financial institutions are effective. Via an inherent risk assessment and a maturity risk assessment, the team will compare expected and actual resilience levels, and devise a roadmap for improvement.
The Chartered Financial Analysts’ standard risk profiling process involves five steps: define goals; fill out a risk profile questionnaire; score the answers; determine asset allocation; and, finally, implement. The team tackling Task 3 is studying investor profiling for robo-advising - in particular, whether the scoring of a questionnaire is an adequate basis for the automated process.
Task 4 is also concerned with the same AI-and-machine-learning-driven service, but will consider how robo-advising affects the trading behavior of individual investors.
The effectiveness of AI techniques in the multimodal content analysis of public disclosures is the title of Task 5. The team will try to determine whether digital technologies can spot and analyze “signals” buried in unstructured data, such as news reports, and whether these signals are useful in assessing and predicting the performance of a firm.
The Task 6 team is charged with developing a real-time systemic risk monitoring system for Hong Kong, using advanced high-frequency and high-dimensional analytics techniques. This will be completed in three stages: first, identifying suitable digitalized financial data; second, statistical modeling based on this data; and, finally, creating an online system for monitoring systemic risk.
Determining how financial innovation can be sustained in Hong Kong is the challenge set for the team tackling Task 7. To arrive at policy recommendations, the team will address analytical models of FinTech services, using empirical modeling, case studies and survey studies.
Finally, the Task 8 team will use structured interviews, surveys and manpower growth projections to derive a list of competencies of FinTech professionals, and then gain an understanding of the talent “supply side” through an analysis of the education programs available.
Research for this four-year project has already begun. “The project has set two ultimate goals: first, to establish Hong Kong as an intellectual powerhouse of FinTech and second, to assess the city’s ability to facilitate financial innovations and to develop policy recommendations to sustain FinTech development,” Professor Tam says.
“The second goal will also cover the regulatory environment, innovation pipeline, cooperation between incumbents and startups, and recruiting and nurturing FinTech talent,” he adds.