Programme Aims and Objectives
The Master of Science in FinTech and Digital Assets is a cross-disciplinary, professionally oriented programme that responds to the rapid digital transformation of financial markets and services in Hong Kong, the Greater Bay Area, the Chinese Mainland and beyond. The programme aims to cultivate graduates who can operate at the intersection of finance, technology and regulation, with emphasis on financial technologies, digital assets and data-driven financial decision-making. By integrating FinTech foundations with systematic understanding of digital-asset developments, the programme prepares students to engage with emerging forms of financial innovation and technology-enabled market structures.
More specifically, the programme aims to:
More specifically, the programme aims to:
- Equip students with a solid quantitative and data-analytic foundation in statistics, regression analysis and data mining, enabling them to understand and apply empirical methods commonly used in FinTech and digital-asset markets.
- Develop students’ understanding of digital-asset ecosystems, including stablecoins, tokenised real-world assets, decentralised finance (DeFi) protocols and smart-contract platforms, and their implications for financial intermediation, market structure and regulation.
- Provide an integrated perspective on macroeconomics and digital assets, helping students analyse how monetary policy, macro-financial conditions and regulatory developments shape the evolution of digital-asset markets.
- Cultivate the ability to apply AI, cloud computing and digital technologies to financial applications such as quantitative investment, sustainable finance and digital marketing in financial services.
- Prepare students for FinTech-related careers in banks, securities firms, asset-management institutions, technology companies, start-ups and regulatory bodies, particularly in roles involving digital-asset innovation, quantitative analysis and technology-enabled financial services.
Programme Details
Admission Code
P94
Year of Entry
2027
Intake Target
50
Mode of Study
Full-time
Credit Requirement
30
Level of Study
Master's Degree
Mode of Funding
Non-government-funded
Tuition Fee
HKD 384,000
Normal Study Period
Full-time: 1 year
Max Study Period
Full-time: 2.5 years
Class Schedule
Weekday daytime and/or evening and Saturday daytime. One Semester or Intensive teaching mode.
Mode of Processing
Applications are processed on a rolling basis. Review of applications will start before the deadline and continue until all places are filled. Early applications are therefore strongly encouraged.
Programme Leader
Prof Gavin Feng
Associate Programme Leader
Prof Jingyu He
General Enquiries
Entrance Requirements
Applicants must
- Applicants should normally hold a recognised bachelor’s degree in finance, economics, business, information systems, computer science, engineering, mathematics, statistics or a related discipline.
- Applicants with other academic backgrounds may also be considered if they can demonstrate adequate quantitative skills and strong motivation to pursue FinTech and digital-asset studies (for example, through relevant coursework, self-study or professional experience).
- Prior work experience in finance, technology or related sectors is not mandatory, but applicants with relevant professional experience in financial institutions, technology firms, regulators or start-ups will be favourably considered.
Applicants whose entrance qualification is obtained from an institution where the medium of instruction is NOT English should also fulfill the following minimum English proficiency requirement
- a score of 79 (for tests taken prior to 21 January 2026) or 4 (for tests taken from 21 January 2026 onwards) (Internet-based Test) in the Test of English as a Foreign Language (TOEFL)@#; or
- an overall band score of 6.0 in International English Language Testing System (IELTS) @#; or
- band 6 in the Chinese Mainland’s College English Test (CET6)*; or
- other equivalent qualifications.
@TOEFL and IELTS scores are considered valid for two years. Applicants are required to provide their English test results obtained within the two years preceding the start of the University's application period. 'TOEFL iBT Home Edition', ‘TOEFL MyBest Score’, ‘IELTS Indicator’, ‘IELTS One Skill Retake’ and ‘IELTS Online’ are not acceptable. All TOEFL results must be sent directly by the Educational Testing Service (ETS) using CityUHK’s institution code 3401, while IELTS results must be sent via the IELTS Results Service e-delivery to 'City University of Hong Kong - Graduate School'.
#Applicants with an IELTS overall band score of 6.0 or a TOEFL overall score of 4 will be required to pass an interview for English proficiency conducted by the concerned academic unit. Applicants with a comparable overall score of 79 or above shown on the TOEFL report may be exempt from the interview requirement. Interviews for other applicants may not be required.
*Applicants holding CET6 results may refer to the score requirement as specified for individual programmes on the admissions website.
#Applicants with an IELTS overall band score of 6.0 or a TOEFL overall score of 4 will be required to pass an interview for English proficiency conducted by the concerned academic unit. Applicants with a comparable overall score of 79 or above shown on the TOEFL report may be exempt from the interview requirement. Interviews for other applicants may not be required.
*Applicants holding CET6 results may refer to the score requirement as specified for individual programmes on the admissions website.
Course Description
Core Courses
Blockchain and Decentralized Finance
Blockchain Security
Foundations of Statistics and Probability
Machine Learning and Social Media Analytics
Quantitative Investment
Regulation and Compliance for Decentralized Finance
The Economics of Generative AI
Elective Courses
Cloud Computing Applications for FinTech
Digital Marketing
Latest Development of Digital Assets
Sustainable Finance in the Digital Age
Tokenization and Valuation of Cultural Assets
Other Programmes
