Master of Science in Digital Financial Technology (MSc in DFinTech)
Financial technology (abbreviated as FinTech) refers to a broad spectrum of the technologies and innovations that are being used to improve and automate the delivery of financial services. The FinTech industry has grown explosively in the last decade, with the advances being made in cloud computing, data analytics and artificial intelligence (AI). To meet surging demand for high quality FinTech talent in Singapore and globally, this graduate programme in FinTech is designed to help students build a strong foundation in computing and finance, and features a range of elective courses organised along three tracks: Computing Technologies, Financial Data Analytics and Intelligence, and Digital Financial Transactions and Risk Management.
The Master of Science in Digital Financial Technology (MSc DFinTech) is designed primarily to help prepare graduates for challenging but rewarding careers as AI software developers, data scientists, FinTech security specialists, financial quantitative analysts and other similar professions in financial institutions or FinTech firms.
In addition, to help build a strong foundation in computing and finance, this programme offers elective courses that cover deep computing and finance expertise to help prepare graduates for future career challenges in the FinTech sector.
Structure of Programme
The MSc DFinTech is a master’s degree by coursework programme. Students are required to pass the requirement of 40 Units (equivalent to 10 courses), together with an additional 12 Units of bridging courses, meeting the following 52 Units programme requirements:
| 28 Units Core/Essential Computing Courses | 16 Units used to strengthen computing and finance foundations of MSc DFinTech students |
|---|---|
| 12 Units used to strengthen FinTech foundations of MSc DFinTech students | |
| 12 Units Elective Courses | 12 Units chosen from courses offered by the School of Computing or Business School |
| Capstone Project | 12 Units (spanning across 2 semesters) |
28 Units of Core/Essential Courses
FT5001 to FT5011 are new courses designed to instill core FinTech competencies covering Artificial Intelligence, Blockchain, and Data Analytics. Among the 28 Units essential courses, BMD5301 and BMD5302 cover the basics of finance and are offered by the NUS Business School. IT5001 and IT5003 cover the basics of computing. The objective is to ensure all students graduate with solid training in both computing and finance foundation.
12 Units of Elective Courses
Elective courses offered by the School of Computing cover areas such as computing systems, cybersecurity, AI, data analytics, and enterprise IT. Students can also take electives in risk management and investment from the NUS Business School. The elective courses are listed in Annex A.
This two-semester Capstone Project is designed to aid students to be equipped with in-depth skills and knowledge in a focused area through experiential learning. Students can choose either an academic research project under the supervision of world-class scholars at NUS, or a FinTech internship that will allow graduating students to obtain industry work experience.
Note: Students have an option to replace the capstone project with 12 Units of prescribed list of elective courses.
Courses Offered under this Programme
The details of the Core/Essential courses are listed in Core Courses.
The details of the Elective courses are listed in Annex A – Elective Courses.
Duration of Programme
The normal candidature periods for full-time and part-time students are 1.5 and 2.5 years respectively. The maximum candidature is 3 years for all students.
Workload
The maximum and minimum workload for part-time candidates per semester are 12 and 4 Units respectively. Candidates who are on full-time candidature can have a maximum and minimum workload of 20 and 12 Units respectively per semester.
Course Plan
The normal candidature periods for full-time and part-time programmes are 3 and 5 semesters respectively. We recommend the following course plans for full-time and part-time programmes:
Course Plan 1 (Full-Time) | Semester 1 (16 Units) | Semester 2 (12 Units) | Semester 3 3 courses (12 Units) |
|---|---|---|---|
| Capstone Project (12 Units) (spans over Semester 2 and 3) | |||
Course Plan 2 (Full-Time) | Semester 1 (20 Units) | Semester 2 (12 Units) | Semester 3 2 courses (8 Units) |
| Capstone Project (12 Units) (spans over Semester 2 and 3) | |||
Course Plan 3 (Full-Time) | Semester 1 (16 Units) | Semester 2 (16 Units) | Semester 3 2 courses (8 Units) |
| Capstone Project (12 Units) (spans over Semester 2 and 3) | |||
The default plan recommended for full-time students is Course Plan 1. Students can choose 1 extra elective in either Semester 1 or 2 and take lesser courses in Semester 3.
Full-time students have flexibility to plan their courses as long as they do not exceed the full-time workload of 20 (maximum) and 12 (minimum) Units respectively per semester. The Industry Capstone Project includes a full-time internship attachment of at least 4 months which is likely to take place between May to Oct.
Part-time students are allowed to enroll a minimum of 4 Units or take up to 12 Units (maximum) per semester, and are expected to complete the programme within the normal candidature period of 2.5 years. Students may have the flexibility to plan their courses as long as they do not exceed the maximum workload. When planning for their workload, students should take into consideration their academic research project workload.
| Sample Course Plan 1 (Part-Time) |
Semester 1 3 courses (12 Units) |
Semester 2 2 courses (8 Units) |
Semester 3 2 courses (8 Units) |
Semester 4
3 courses (12 Units) |
|---|---|---|---|---|
| Capstone Project (12 Units) (spans over Semester 2 and 3) |
||||
| Sample Course Plan 2 (Part-Time) |
Semester 1 2 courses (8 Units) |
Semester 2 2 courses (8 Units) |
Semester 3 2 courses (8 Units) |
Semester 4 2 courses (8 Units) |
Semester 5 2 courses (8 Units) |
|---|---|---|---|---|---|
| Capstone Project (12 Units) (spans over Semester 4 and 5) |
|||||
Continuation/Graduation Requirements
The MSc DFinTech programme uses the Grade Point Average (GPA) as a criterion for continuation and graduation. Students may refer to the information on the University’s continuation requirements and duration of the programme.
In order to graduate from the MSc DFinTech programme, students are required to fulfil the programme requirements, as well as achieve a minimum final GPA of 3.0.
Students are allowed a maximum of two level 4000 courses, with the remaining courses at level 5000 or above.
To apply, please click here.
