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PERSONAL PROGRAMME GUIDE · UNOFFICIAL

Graduate education at NTU

MSc in
Financial Technology.

A quantitative foundation for a changing financial world.

Patrick Pun · Founding Programme Director

Official programme website Explore the curriculum
This is a personal, simplified guide, not an official admissions website. The official NTU programme pages take precedence for curriculum, fees, entry requirements, course availability and regulations. Overview checked in September 2026.

Two directions, a shared foundation

Choose your perspective.

The programme combines data science, artificial intelligence and information technology with financial applications.

01 / IPA

Intelligent Process Automation

A technical pathway for students interested in quantitative methods, machine learning and automation in finance.

Data scienceAI & automationQuantitative methods
02 / DFS

Digital Financial Services

A pathway exploring financial services, digital technologies and innovation in the financial ecosystem.

Digital financeFinancial innovationTechnology & business

The curriculum at a glance

One common core.
Two specialisation paths.

The 30-AU programme comprises a 12-AU compulsory core, 12 AU of electives from the chosen specialisation, and 6 AU of other electives. Select a block below to explore the current course pool.

IPAspecialisation
DFSspecialisation

Shared by IPA and DFS

Compulsory core · 12 AU

All students complete the same quantitative, programming, finance and FinTech foundation.

MH6817Principles and Statistical Foundations of Finance & Risk3 AU
MH6805Machine Learning in Finance3 AU
MH6807Introduction of FinTech Innovation and Ecosystem3 AU
MH6810Programming and Data Analysis with Python3 AU

IPA pathway

IPA prescribed electives · 12 AU

Choose courses from this technical FinTech pool to fulfil the 12-AU specialisation requirement.

MH6812Natural Language Understanding for Retrieval-Augmented Generation3 AU
MH6018Blockchains and Cryptocurrency3 AU
MH6311Stochastic Processes for Data Science1.5 AU
MH6815Algorithmic Trading and Robo-Advisors1.5 AU
MH6816Introduction to Cybersecurity1.5 AU
MH6818FinTech Innovation with AI1.5 AU
MH6831Quantitative Methods in Finance1.5 AU
MH6832Reinforcement Learning for Finance1.5 AU

IPA pathway

Other electives · 6 AU

For IPA students, DFS prescribed electives may be counted as other electives. The Practicum is also available within the unrestricted-elective pool, subject to current programme rules.

MH6331Market Risk and Derivatives Analytics1.5 AU
MH6332Financial and Risk Analytics II1.5 AU
MH6821Anti-Financial Crime and Compliance1.5 AU
MH6822Regulatory Technology1.5 AU
MH6823Financial Inclusion and Decentralized Finance1.5 AU
MH6824Fundamentals of FinTech Entrepreneurship1.5 AU
MH6825FinTech Entrepreneurial Practice1.5 AU
MH6826Investment and Portfolio Management1.5 AU
MH6827Financial Data Management and Business Intelligence1.5 AU
MH6833Microeconomics and Macroeconomics1.5 AU
MH6834Green FinTech and Sustainable Finance1.5 AU
MH6838Practicum3 AU

DFS pathway

DFS prescribed electives · 12 AU

Choose courses from this digital-finance and financial-services pool to fulfil the 12-AU specialisation requirement.

MH6331Market Risk and Derivatives Analytics1.5 AU
MH6332Financial and Risk Analytics II1.5 AU
MH6821Anti-Financial Crime and Compliance1.5 AU
MH6822Regulatory Technology1.5 AU
MH6823Financial Inclusion and Decentralized Finance1.5 AU
MH6824Fundamentals of FinTech Entrepreneurship1.5 AU
MH6825FinTech Entrepreneurial Practice1.5 AU
MH6826Investment and Portfolio Management1.5 AU
MH6827Financial Data Management and Business Intelligence1.5 AU
MH6833Microeconomics and Macroeconomics1.5 AU
MH6834Green FinTech and Sustainable Finance1.5 AU

DFS pathway

Other electives · 6 AU

For DFS students, IPA prescribed electives may be counted as other electives. The Practicum is also available within the unrestricted-elective pool, subject to current programme rules.

MH6812Natural Language Understanding for Retrieval-Augmented Generation3 AU
MH6018Blockchains and Cryptocurrency3 AU
MH6311Stochastic Processes for Data Science1.5 AU
MH6815Algorithmic Trading and Robo-Advisors1.5 AU
MH6816Introduction to Cybersecurity1.5 AU
MH6818FinTech Innovation with AI1.5 AU
MH6831Quantitative Methods in Finance1.5 AU
MH6832Reinforcement Learning for Finance1.5 AU
MH6838Practicum3 AU

Course offerings can change. The official NTU programme page remains the authoritative source for current availability and graduation requirements.

Official curriculum & course information My Quantitative Methods in Finance course

Learning by doing

Bring the methods
to a real problem.

My teaching places emphasis on applying methods, analysing data and explaining the reasoning behind a result. The MH6805 course includes a group project connecting machine learning with realistic data analysis.

Practicum and project arrangements, including research or internship pathways, are subject to current programme rules and approvals; an internship placement is not guaranteed.

Teaching & project resources

Useful next steps

Where should I check eligibility and fees?

Use the official programme site for current admissions criteria, application dates, tuition fees and financial information. They are intentionally not duplicated here.

Official programme information
Who should I contact?

Programme enquiries: MScFinTech@ntu.edu.sg. Questions about my research or teaching: cspun@ntu.edu.sg.

What about other graduate programmes?

Explore SPMS graduate programmes for broader coursework options, or Mathematics PhD for research training.