Programme at a Glance
Intake and Application
Overview
The National University of Singapore (NUS) Master of Science in Digital Financial Technology (MSc DFinTech) is offered by the NUS School of Computing.
Financial technology (abbreviated as FinTech) refers to a broad spectrum of 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 new flagship 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 programme is intended 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.
Why This Programme?
Build a solid foundation in FinTech with a programme backed by NUS School of Computing and the NUS Business School, both of which are ranked among the best schools in their subject areas*.
Optimise learning with a customisable curriculum; choose electives according to one of three tracks or based on personalised needs, and decide which capstone project option is a better fit—an academic research project conducted under the supervision of our accomplished faculty, or an internship with a FinTech company to gain practical industry experience
Prepare for a career in the fast-growing FinTech sector such as a Blockchain Developer, Financial Analyst or FinTech Product Specialist.
* QS World University Rankings by Subject 2024
Application Period
An Academic Year (AY) at NUS consists of two semesters and a special term (which occurs during the Semester 2 Vacation, and is divided into two parts of six weeks duration each):
For the MSc in DFinTech programme, there is one application period for each AY:
| Programme | Intake | Application Dates |
|---|---|---|
| MSc in DFinTech | Semester 1 (Aug Intake) | 1 Nov of year preceding the intake year to 31 Jan of the intake year |
Admission to the NUS MSc in DFinTech programme is granted on a competitive basis as places in the programme are limited. Applicants should possess the following minimum requirements:
| Academic | Bachelor's Degree in Computing, or Bachelor's Degree in a related discipline (such as Science, Technology, Engineering, and Mathematics (STEM), Finance, Economics or Business) Note: Candidates with academic qualifications other than the above may be considered on a case-by-case basis, subject to approval by the department |
| Skill/Experience | Python programming knowledge and/or learning in advanced quantitative subjects For holders of Bachelor’s Degrees in related disciplines (see above), two years of Fintech or information technology (IT) industry experience |
| English Language | Applicants whose medium of university instruction is not completely in English: Test of English as a Foreign Language (TOEFL) minimum score of 90 (Internet-based), or International English Language Testing System (IELTS) minimum Academic score of 6.0 Note: TOEFL / IELTS scores are valid for two years from the test date and should not have expired at point of application. Expired scores will not be considered for the application. |
| Other | International applicants*: Graduate Record Examinations (GRE) minimum scores of 320 (Verbal Reasoning and Quantitative Reasoning) and 3.5 (Analytical Writing), or Graduate Management Admission Test (GMAT) minimum score of 700, or Graduate Aptitude Test in Engineering (GATE) scores for graduates from Indian universities. * GRE/GMAT/GATE preferred, but not required. Candidates may be required to sit for other tests as prescribed by the School. Note: GRE scores are valid for five years from the test date and should not have expired at point of application. Expired scores will not be considered for the application. |
Candidates may visit the official Educational Testing Service (ETS) website for scheduling of TOEFL/GRE tests.
Note: Applicants are responsible for ensuring that application information and all supporting documents are truthful and correct. NUS reserves the right to verify information provided as part of an application. False or misleading information in an application (including but not limited to test scores, resumes, certificates, transcripts, etc.) is grounds for admission rejection, revocation and/or dismissal from the University.
The NUS MSc in DFinTech programme is offered on the following basis (with estimated time to complete the programme indicated below):
| Full-time | 18 months |
| Part-time | 30 months |
Note: International applicants must be accepted into an approved full-time course in Singapore to apply for a Student’s Pass. For more information, refer to the Singapore Immigration & Checkpoints Authority (ICA) website.
The NUS MSc in DFinTech is a 52-Unit coursework-based Master’s Degree programme comprising:
Core/essential courses (28 Units),
Elective courses (12 Units), and
Capstone project (12 Units).
Core/Essential Courses
Students must complete 28 Units (16 Units focused on computing and finance, and 12 Units on FinTech), comprising courses from the following list.
| Course Code | Course Title | Units |
|---|---|---|
| †FT5001 | Fintech Innovations for Consumers | 4 |
| †FT5002 | Digital Transformation at Financial Institutions | 4 |
| †FT5003 | Blockchain Innovations | 4 |
| †FT5004 | Programming for Blockchain Applications | 4 |
| †FT5005 | Machine Learning for Finance | 4 |
| †FT5009 | Contemporary Topics in Financial Data Analytics | 4 |
| †FT5010 | Algorithmic Trading Systems Design and Deployment | 4 |
| †FT5011 | Deep Learning for Finance | 4 |
| *BMD5301 | Introduction to Finance for FinTech Professionals | 4 |
| BMD5302 | Financial Modelling for FinTech Professionals | 4 |
| *IT5001 | Software Development Fundamentals | 4 |
| *IT5003 | Data Structures and Algorithms | 4 |
* Students who have completed one or more course(s) similar to BMD5301, IT5001 and/or IT5003 can submit a request to the School of Computing and (subject to the School’s approval) take the following as replacement:
> IT5004 Enterprise Systems Architecture Fundamentals,
> IT5005 Artificial Intelligence, or
> IT5006 Fundamentals of Data Analytics
† These courses can be counted towards meeting the requirement of 12 Units on FinTech.
Elective Courses
Students are strongly encouraged (but not required) to take their 12 Units of elective courses from one vertical track, as described in the following list.
Vertical 1: Computing Technologies
| Course Code | Course Title | Units |
|---|---|---|
| CS5224 | Cloud Computing | 4 |
| CS5231 | Systems Security | 4 |
| CS5321 | Network Security | 4 |
| CS5331 | Web Security | 4 |
| CS5421 | Database Applications Design and Tuning | 4 |
| CS5439 | Software Security | 4 |
| FT5008 | Contemporary Topics in Blockchain Applications | 4 |
| IS4234 | Compliance and Regulation Technology | 4 |
| IS5008 | Technology Risk and Cyber Resilience | 4 |
| IS5009 | Topics in Financial Technology Solutions | 4 |
Vertical 2: Financial Data Analytics and Intelligence
| Course Code | Course Title | Units |
|---|---|---|
| CS5242 | Neural Networks and Deep Learning | 4 |
| CS5246 | Text Processing on the Web | 4 |
| CS5339 | Theory and Algorithms for Machine Learning | 4 |
| CS5344 | Big-Data Analytics Technology | 4 |
| CS5446 | AI Planning and Decision Making | 4 |
| FT5009 | Contemporary Topics in Financial Data Analytics | 4 |
| IS5006 | Human-Centred Intelligent Systems | 4 |
| IS5126 | Hands-on with Applied Analytics | 4 |
| IS5152 | Data-Driven Decision Making | 4 |
Vertical 3: Digital Financial Transactions and Risk Management
| Course Code | Course Title | Units |
|---|---|---|
| BMF5342 | Technological Disruptions in Finance and Data Analytics | 4 |
| BMF5346 | Venture Capital and Private Equity | 4 |
| BMF5353 | Applied Investment Strategies | 4 |
| BMF5354 | Financial Regulation in a Digital Age | 4 |
| BMF5355 | Financial Institutions, Markets, Systems and Technology | 4 |
| BMF5358 | Entrepreneurship in Financial Technology | 4 |
| BT4013 | Analytics for Capital Market Trading and Investment | 4 |
| BT4016 | Risk Analytics for Financial Services | 4 |
| CS5233 | Simulation and Modelling Techniques | 4 |
| FE5103 | Equity Products and Exotics | 4 |
| FE5224 | Current Topics in Applied Risk Management | 2 |
| FE5227 | Commodities Fundamentals and Modelling | 2 |
Capstone Project
Students can choose to do either an academic research project or a FinTech internship for the two-semester capstone project.
| Course Code | Course Title | Units |
|---|---|---|
| FT5007 | FinTech Capstone Project | 12 |
Note: For more information about the courses listed above (as well as other courses offered in the current academic year), please visit NUSMODS.
To graduate from the NUS MSc in DFinTech programme, students must meet the following requirements:
| Programme and/or Specialisation | Read and pass a total of 52 Units, comprising: 28 Units of core/essential courses 12 Units of elective courses 12 Units of capstone project |
| Course and/or Qualification | Not applicable |
| Grade Point Average (GPA) | Minimum 3.0 (out of maximum 5.0)
Please see also the University’s minimum standards for Continuation and Graduation Requirements. Specific programmes may implement stricter or additional requirements. |
| Other | Not applicable |
The University reserves all rights to review fees as necessary and adjust accordingly without prior notice.
| Tuition | S$64,800.00 (excluding GST) / S$70,632.00 (including 9% GST) Note: The tuition fee stated above is for 52 Units. Students who are required to take more than 52 Units for programme completion are subject to supplementary tuition fees. |
| Application | S$109.00 (including 9% GST) Non-refundable and non-transferable Limited to one application submission per intake, for up to a maximum of five programmes/courses per application |
| Acceptance | S$5,000.00 (excluding GST) Payable upon acceptance of offer Non-refundable and non-transferable Will be credited towards tuition fees |
| Miscellaneous Student Fees | As published by Office of the University Registrar
Payable every regular semester |
Scholarships & Financial Assistance
The scholarships and financial assistance schemes presented here are examples of the kinds of funding from the University as well as third-party sponsors that might be available to eligible NUS Master's Degree (Coursework) programme students and applicants.
The information provided is subject to change, and warranties cannot be provided as to its completeness or accuracy. Students and applicants are strongly encouraged to conduct their own research, and refer to the relevant sponsors and/or websites for more detailed and up-to-date information.
NUS Master's by Coursework Enhanced Tuition Fee Rebate
NUS Master's Degree by Coursework Tuition Fee Rebate
SG Digital Scholarship (Postgraduate)
SkillsFuture Level-Up Programme
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