University course · real outcomes from HESA / Discover Uni · part of Careermash
University degree

FinTech with Data Analytics

The University of Westminster
Qualification
Degree
Length
3 yrs
UK fees / yr
£9,535
Study
full-time
Worth knowing: about 20% of students don't make it past first year here - ask the uni what support they offer.
Robin · your guide
Here's the honest picture on this course - what you'd study, whether you'd likely get in, what it pays, and where it leads. Everything's real data.
About this course

FinTech with data analytics sits at one of the most dynamic intersections in the contemporary economy, combining the rapidly evolving world of financial technology with the quantitative and computational skills needed to make sense of the vast amounts of data that financial systems generate and depend on. Financial technology encompasses the digital platforms, payment systems, algorithmic trading, blockchain applications, lending marketplaces, and regulatory technologies that are reshaping how financial services are delivered. Data analytics provides the tools to extract insight from complex datasets, to build predictive models, and to support decision-making in finance and beyond.

At the University of Westminster in London, this three-year full-time degree draws together computer science and finance, building your computing literacy from the ground up while developing your theoretical understanding of the frameworks that underpin FinTech and data analytics. You will master industry-standard software and programming languages alongside the conceptual foundations of financial markets, risk, and regulation. The programme includes a sandwich year, a year abroad option, and a work placement, providing structured opportunities to apply your skills in professional settings and to develop the industry connections that are increasingly important in a competitive graduate market.

Westminster's London location gives you direct access to one of the world's leading financial and technology centres.

Graduates from FinTech with Data Analytics programmes are well placed for careers across financial services, technology companies, and the growing FinTech sector itself. Roles in quantitative analysis, financial data science, software development for financial applications, algorithmic trading, compliance technology, and product management in FinTech firms are all accessible. The combination of financial and technical skills is also valued in consultancy, regulation, and the technology functions of banks, insurers, and investment managers.

For those drawn to research or advanced study, the degree provides a strong foundation for postgraduate programmes in data science, financial engineering, or FinTech. The typical entry tariff is 120 points.

Could you get in?
The grades students arrived with
48-63 pts5%
64-79 pts10%
80-95 pts20%
96-111 pts10%
112-127 pts15%
128-143 pts10%
144-159 pts15%
160-175 pts5%
208-223 pts5%
How they qualified
90% got in with A-levels. The rest came in a mix of ways:
A-levels90%
the IB5%
a foundation year5%
Could I get in? Try your grades
120 UCAS pts
Pay & prospects
80%
In work or further study after
80%
Continue past first year
83%
Student satisfaction
What graduates earn over time
£28,000
3 years on
£33,000
5 years on
What graduates actually go on to do % of leavers
Finance ProfessionalsHighly skilled20%
Administrative occupations30%
Elementary occupations10%
Managers, directors and senior officialsHighly skilled10%
Teaching ProfessionalsHighly skilled10%
Animal care and control services5%
Sales occupations5%
What students say National Student Survey
83%
of students are satisfied with the course overall
Teaching76%
Assessment & feedback80%
Academic support83%
Well organised82%
Learning resources85%
Student community90%
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Where this degree can lead
Like the look of it?
When you're ready, the full entry requirements and application are on The University of Westminster's own site.
Apply on uni site
Careermash · real course data from HESA / Discover Uni, in plain English.

Career data: role, pay and progression profiles built for Careermash's careers engine; AI-impact estimates from Anthropic's observed AI-usage telemetry and OpenAI's AI Jobs Transition Framework. Course data: HESA / Discover Uni, including Graduate Outcomes, LEO and the National Student Survey. Apprenticeships: IfATE-published standards, approved only.

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