MSc Financial Technology with Data Science
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 startups have quickly scaled to challenge the dominance of traditional banks by developing new forms of finance from the ground up.
This MSc offers an opportunity to join the financial technology revolution. You will learn the key design features of a number of financial technology applications and will develop skills to implement, assess and engineer these technologies. You 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 a flourishing fintech ecosystem. The programme has been co-designed with industrial partners and will offer opportunities to engage with industry on real-world commercial projects
On entry, you will take one of two foundational units, depending on your 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. When you arrive, your unit choice will be decided, based on your previous experience, in consultation with your personal tutor.
The remainder of the programme consists of compulsory units in Large-Scale Data Engineering (20 credits); Introduction to Financial Technology (20 credits); Introduction to Artificial Intelligence (10 credits); Introduction to Data Analytics (10 credits); Advanced Financial Technology (20 credits); and Financial Technology Group Project (20 credits).
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 Financial Technology with Data Science.
A strong (65%) upper-second class honours degree (or international equivalent) in a numerate science, computer science, or engineering. Examples of acceptable degree titles include, but are not limited to Computer Science, Computing, Mathematics, Statistics, Operations Research, Data Science, Software, Engineering, Psychology, Physics, Chemistry, Genetics, Biology, Neuroscience, Economics, Finance, Accounting, Econometrics, AstroPhysics, Geology / Earth Sciences, Civil, Engineering, Mechanical Engineering, Aeronautical Engineering, Chemical Engineering, Systems, Engineering, Electronic Engineering, Electrical Engineering, Nuclear Engineering, Manufacturing, Engineering, Software Engineering, Mining Engineering or Medicine.
For applicants who are currently completing a degree, we understand that their final grade may be higher than the interim grades or module/unit grades they achieve during their studies.
We will consider applicants whose interim grades are currently slightly lower than the programme's entry requirements. We may make these applicants an aspirational offer. This offer would be at the standard level, so the applicant would need to achieve the standard entry requirements by the end of their degree. Specific module requirements may still apply.
We will consider applicants whose grades are slightly lower than the programme's entry requirements, if they have at least one of the following:
- evidence of significant, relevant work experience;
- a relevant postgraduate qualification.
If this is the case, applicants should include their CV (curriculum vitae / résumé) when they apply, showing details of their relevant work experience and/or qualifications.
See international equivalent qualifications on the International Office website.
Read the programme admissions statement for important information on entry requirements, the application process and supporting documents required.Go to admissions statement
Fees and funding
- UK: full-time
- £17,700 per year
- UK: part-time (two years)
- £8,850 per year
- UK: part-time (three years)
- £5,900 per year
- Overseas: full-time
- £34,200 per year
Fees are subject to an annual review. For programmes that last longer than one year, please budget for up to an 8% increase in fees each year.
More about tuition fees, living costs and financial support.
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 or could go on to launch a fintech startup.