Hong Kong Baptist University (HKBU) School of Business
MSc in Finance (FinTech and Financial Analytics)Kowloon Tong, Hong Kong
DURATION
1 up to 2 Years
LANGUAGES
English
PACE
Full time, Part time
APPLICATION DEADLINE
Request application deadline *
EARLIEST START DATE
Request earliest startdate
STUDY FORMAT
On-Campus
* Applications for the 2024-25 intake (i.e. programme commences in September 2024) have started. Review of applications will start before the deadline and continue until all places are filled. Therefore, early applications are strongly encouraged.
Key Summary
Scholarships
Explore scholarship opportunities to help fund your studies
Introduction
With the rise of disruptive technologies and the new generation of Big Data and FinTech, concepts of money, payments, identity, and security need to be looked at through a new lens -- how can finance professionals respond early and effectively to ride the wave, and take advantage of the new opportunities before it’s too late?
Through lectures, workshops, round-table discussions, case studies and expert sharing from industry practitioners, this interdisciplinary programme taught by both Finance and Management Information Systems faculty, will widen and deepen your understanding of the rapidly changing landscape and the impact of new technologies on traditional finance models. You will be empowered with knowledge in Finance, FinTech, Financial Analytics, Machine Learning, Financial Computing, Textual Analysis, Cybersecurity, Privacy, Blockchain, Cryptocurrency, Algorithmic Trading, Financial Fraud, and Regulatory Compliance. Get well-prepared for the fast-growing demand of today’s data-driven economy, and develop new insights and perspectives towards emerging technologies and harness them to take the Financial Industry to the next level.
Ideal Students
Who Should Enrol?
The Department of Finance and Decision Sciences is committed to nurturing more FinTech talent in Hong Kong.
- Looking for Change: Candidates who seek to adapt their traditional financial business to the new-age digital economy and prepare for the challenges coming out of the new data-driven economy.
- Deepening Knowledge: Candidates who seek to deepen their knowledge in the disruptive innovations and transformative forces in the finance ecosystem.
- Entering the New Era: Candidates who seek to enter the FinTech or Financial Analytics Industry.
Program Outcome
How does the programme help?
- Students are encouraged to participate in internships during their studies and we will assist with providing internship opportunities.
- The programme is interdisciplinary. Courses are taught by both Finance and Management Information Systems faculty, and industry practitioners with finance, business, and computer science backgrounds.
- Some courses are co-delivered by our faculty alongside industry practitioners to equip students with both theoretical and practical knowledge.
- Our advisory committee will not only provide advice on programme design but when possible, share their valuable first-hand experience with the students.
- Students who have a postgraduate degree in Finance or related disciplines could have up to 50% of credit transferred towards the finance-related curriculum; subject to departmental approval. Students with credit transfers will be offered a discount on the programme fee, proportional to the courses exempted.
Programme Objective
The Programme aims at empowering students with knowledge in Finance, FinTech and Financial Analytics, helping them develop the ability to solve finance-related business problems, and nurturing them to better prepare for the fast-growing demand in today’s data-driven economy.
Curriculum
Curriculum Structure
Students are required to complete eight core courses and two elective courses for graduation. In addition, students are encouraged to participate in internships during their studies, and the program will assist in providing internship opportunities.
Core Courses
Total Required Units of Core Courses - 24 Units
- FIN 7780 Financial Technology (FinTech) (3 units)
- FIN 7790 Machine Learning for Financial Data (3 units)
- FIN 7800 Corporate Finance (3 units)
- FIN 7810 Investment Management (3 units)
- FIN 7830 Financial Computing with Python and R (3 units)
- FIN 7860 International Financial Management (3 units)
- FIN 7870 Financial Derivatives and Risk Management (3 units)
- FIN 7900 Cybersecurity, Privacy and RegTech for Finance (3 units)
Elective Courses
Total Required Units of Elective Courses - 6 Units
- FIN 7820 Applied Financial Econometrics (3 units)
- FIN 7840 Blockchain and Cryptocurrency (3 units)
- FIN 7850 Algorithmic and High-Frequency Trading (3 units)
- FIN 7880 Textual Analysis in Finance and Accounting (3 units)
- FIN 7890 Compliance in Finance (3 units)
- FIN 7910 Independent Studies Integrative Project (3 units)