MSc Financial Technology with Data ScienceFind a programme
New programme for 2021
|Faculty||Faculty of Engineering|
|Programme length||One year full-time|
|Location of programme||Clifton campus|
|Part-time study available||No, full-time only|
|Start date||September 2021|
From crowdfunding to cryptocurrencies, and from automated trading to Alipay, recent innovations in financial technologies have revolutionised the way we spend, save, borrow, and invest. Companies in the financial services sector are now able to intelligently harness data to provide tailored products and services; big technology corporations offer financial services to customers through their social media accounts; and disruptive technology start-ups have quickly scaled to challenge the dominance of traditional banks by developing new forms of finance from the ground up.
This new MSc offers an opportunity to join the financial technology revolution. Students will learn the key design features of a number of financial technology applications and will develop skills to implement, assess, and engineer these technologies. Students will also develop an understanding of the computational, statistical, and machine learning principles necessary for insightful large-scale data analysis used in data-driven finance.
Hosted by a world-leading engineering faculty, this is a technology-focused MSc and not a finance or accounting programme that is traditionally provided by a business school. Therefore, we expect applicants to have a strong background in computer science, engineering, or a numerate science; a background in economics or finance is not expected or required.
This MSc is likely to appeal to applicants looking to start or advance their careers in data-driven finance and technology. The UK is a world leader in financial technology and the Bristol region has the largest fintech ecosystem outside of London. The programme has been co-designed with industrial partners and will offer opportunities to engage with industry on real-world commercial projects.
Fees for 2021/22
We charge an annual tuition fee. Fees for 2021/22 are as follows:
- UK: full-time
- Overseas (including EU): full-time
- Channel Islands/Isle of Man: full-time
Fees are subject to an annual review. For programmes that last longer than one year, please budget for up to a five per cent increase in fees each year. Find out more about tuition fees.
University of Bristol students and graduates can benefit from a ten per cent reduction in tuition fees for postgraduate study. Check your eligibility for an alumni scholarship.
Funding for 2021/22
Further information on funding for prospective UK, EU and international postgraduate students.
On entry, students will take one of two foundational units, depending on their previous experience. Students without software development experience will take a 20-credit unit in Software Development, Programming and Algorithms; alternatively, students with software development experience will take a 20-credit unit in Statistical Computing and Empirical Methods.
The remainder of the programme consists of compulsory units in Large-Scale Data Engineering (20 credits); Internet Economics and Financial Technology, Part I (20 credits); Introduction to Artificial Intelligence (ten credits); Introduction to Data Analytics (ten credits); Internet Economics and Financial Technology, Part II (20 credits); and Financial Technology Mini-project (20 credits). The last of these is a group activity which will be aligned, wherever possible, with an external client.
All students will complete their studies with a 60-credit individual research or implementation project of their choosing from a selection proposed by project supervisors. This unit will provide students with first-hand experience in planning, running, documenting, and presenting a substantial piece of original work in the field of financial technology. The aim of this unit is to give students a substantial opportunity to integrate material from all taught units that they have studied as part of the programme, to demonstrate the breadth and depth of their learning on the MSc.
Visit our programme catalogue for full details of the structure and unit content for our MSc in Financial Technology with Data Science.
Applicants must hold/achieve a minimum of an upper-second class honours degree (or international equivalent) in numerate science, computer science, or engineering.
See international equivalent qualifications on the International Office website.
English language requirements
If English is not your first language, you need to meet this profile level:
Further information about English language requirements and profile levels.
Read the programme admissions statement for important information on entry requirements, the application process and supporting documents required.
This programme has been co-designed with industrial partners to ensure that graduates are equipped with highly in-demand analytical, statistical and programming skills suitable for a range of technology careers in the financial services sector, as well as data scientist and data engineer roles in other non-finance industries. Graduates will also be prepared for careers in research and development; while more entrepreneurial-minded graduates may go on to launch a fintech startup.
18 January 2021 for International applicants. 19 August 2021 for UK applicants. Early applications recommended; places may fill before the deadline. As students from different regions tend to apply at different points in the application period, applications from some regions may close earlier in the year.
The School continues to welcome applications that fulfil our admissions criteria to select a balanced international student cohort. As students from different countries tend to apply at different points in the application period, applications from some countries may close earlier in the year. Due to very high demand, applications will now close to students from China on 7 December 2020, applications received after this time will not be reviewed.
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REF 2014 results
- 20% of research is world-leading (4 star)
- 45% of research is internationally excellent (3 star)
- 30% of research is recognised internationally (2 star)
- 5% of research is recognised nationally (1 star)
Results are from the most recent UK-wide assessment of research quality, conducted by HEFCE. More about REF 2014 results.