MSc Financial Technology
12 monthsProgramme duration
39,000 GBPTuition Fee/year
27 Aug, 2026Application Deadline
SepStarting Month
Programme overview
Main Subject
Finance
Degree
MSc
Study Level
Masters
Study Mode
On Campus
The MSc in Financial Technology will provide you with a comprehensive grounding in the various analytical methods of financial technology, or 'FinTech', as well as knowledge of how these methods are utilised in practice in financial markets. The content will combine finance theory with extensive applications through to practical issues using real-world data. The programme includes units addressing the latest technological developments that have transformed many aspects of the finance industry such as big data, artificial intelligence, machine learning, process automation, cryptocurrencies and blockchain, alongside units that cover the underpinning theory and practice of finance.
Artificial intelligence and machine learning are reshaping the financial services sector and are being used across a range of applications including trading, portfolio construction and evaluation, risk management, financial intermediation and corporate finance. You will gain a broad, high-level overview of the impact that technology is having in reshaping many aspects of financial services. You will also develop specific practical skills in programming, statistical analysis and financial modelling, which will enable you to apply these technological innovations in a variety of contexts. This may include algorithmic trading, robo-advising, peer-to-peer lending, mobile payments, crowdfunding and digital currencies.
The MSc Financial technology offers the opportunity to closely work with industry partners through undertaking applied projects. The teaching will be research-led and undertaken by subject experts, involving a mixture of lectures and small-group tutorials as well as computer lab-based sessions for the completion of data-based case studies and applications. Industry-relevant skills are embedded in the units throughout the programme, which are practical in nature without compromising academic rigour.
Teaching for this postgraduate programme will be delivered at our new Temple Quarter Enterprise Campus, opening 2026. Here, enhanced links with industry and collaborative learning spaces will provide students with real-world knowledge, networks and skills to succeed once you graduate. Depending on your choice of optional units, you may also be taught on the Clifton Campus.
Programme overview
Main Subject
Finance
Degree
MSc
Study Level
Masters
Study Mode
On Campus
The MSc in Financial Technology will provide you with a comprehensive grounding in the various analytical methods of financial technology, or 'FinTech', as well as knowledge of how these methods are utilised in practice in financial markets. The content will combine finance theory with extensive applications through to practical issues using real-world data. The programme includes units addressing the latest technological developments that have transformed many aspects of the finance industry such as big data, artificial intelligence, machine learning, process automation, cryptocurrencies and blockchain, alongside units that cover the underpinning theory and practice of finance.
Artificial intelligence and machine learning are reshaping the financial services sector and are being used across a range of applications including trading, portfolio construction and evaluation, risk management, financial intermediation and corporate finance. You will gain a broad, high-level overview of the impact that technology is having in reshaping many aspects of financial services. You will also develop specific practical skills in programming, statistical analysis and financial modelling, which will enable you to apply these technological innovations in a variety of contexts. This may include algorithmic trading, robo-advising, peer-to-peer lending, mobile payments, crowdfunding and digital currencies.
The MSc Financial technology offers the opportunity to closely work with industry partners through undertaking applied projects. The teaching will be research-led and undertaken by subject experts, involving a mixture of lectures and small-group tutorials as well as computer lab-based sessions for the completion of data-based case studies and applications. Industry-relevant skills are embedded in the units throughout the programme, which are practical in nature without compromising academic rigour.
Teaching for this postgraduate programme will be delivered at our new Temple Quarter Enterprise Campus, opening 2026. Here, enhanced links with industry and collaborative learning spaces will provide students with real-world knowledge, networks and skills to succeed once you graduate. Depending on your choice of optional units, you may also be taught on the Clifton Campus.
Admission Requirements
OR
If your degree subject is not listed above, you will typically need an upper second-class honours degree (60% or higher) or an international equivalent with three units of mathematics with 60% or above (or an international equivalent) in each unit, from the units listed in Maths qualification requirements below.
OR
A-level Mathematics with grade A if no mathematics or quantitative units in your degree.
English language requirements
If English is not your first language, you will need to reach the requirements outlined in our profile level B.
Maths qualification requirements
If your degree subject is not listed in the main entry requirements, you must have evidence of an upper second class honours degree which includes three units of mathematics with 60% or above (or international equivalent) in each unit. Examples of acceptable units include:
- Advanced Maths (introductory maths does not count towards maths unit requirements)
- Algebra/Linear Algebra
- Calculus
- Financial Maths
- Maths
- Pure Maths
- Business Mathematics
- Business Statistics
- Computer Science (including programming/algorithms)
- Data Mining/Data Science/ Data Analytics
- Derivatives
- Econometrics
- Financial Modelling
- Financial Statement Analysis
- Investment Analysis
- Probability
- Quantitative Methods
- Quantitative Research Methods
- Statistics/Statistical Methods/Statistical Analysis
- Candidates are required to submit references or letter(s) of recommendation for acceptance
- Candidates are required to submit an essay(s) for acceptance
Tuition fees
Domestic
International
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