Swansea University

What you'll study

This degree blends pure and applied mathematics with modules focused on probability, statistics and financial modelling. Early years establish foundations in calculus, linear algebra and analysis, together with introductory probability and programming for numerical work. Later stages introduce stochastic processes, time series, optimisation, numerical methods for partial differential equations and models for pricing and hedging derivatives.

• Core mathematical analysis and algebra
• Probability theory and stochastic processes
• Statistical inference and econometric techniques
• Numerical methods, scientific computing and programming (commonly using Python, MATLAB or similar)
• Financial mathematics: Black–Scholes and other pricing models, risk-neutral valuation
• Modules in optimisation, portfolio theory and risk management
• Final-year project applying mathematical tools to a finance-related problem

The programme typically offers optional modules and pathways so students can tailor study to interests such as computational finance, actuarial topics or data analytics. An optional placement year or short industry placements may be available to gain practical experience, depending on the intake and student choices.

Entry requirements

Applicants are expected to have strong mathematics background. Typical entry asks for A-level Mathematics (or equivalent qualification such as Core Mathematics plus additional algebra/calculus training) together with further qualifications at a similar standard. International and alternative qualifications (for example, the International Baccalaureate, BTEC or recognised overseas equivalents) are accepted where they demonstrate adequate mathematical preparation. Applicants without standard qualifications are considered on an individual basis; relevant prior study, strong performance in diagnostic assessments and evidence of numeracy may support an application.

All applicants whose first language is not English must demonstrate proficiency in English through an approved test or recognised qualification to meet the University's language requirements.

Career prospects

Graduates are well placed for roles that require quantitative and analytical skills. Typical career destinations include:

• Quantitative analyst (buy-side or sell-side)
• Risk analyst and risk manager in banking and insurance
• Financial modeller and derivatives pricing specialist
• Actuarial trainee (combined with further professional exams)
• Data analyst, statistician or data scientist roles in a variety of sectors
• Further study: MSc in Financial Mathematics, Statistics, Applied Mathematics or MSc programmes that support progression to research or specialist professional qualifications

The programme develops transferable skills — problem solving, programming, communication of technical material and project work — valued across finance, technology and consultancy sectors. The University’s careers service supports CVs, interview preparation and employer engagement.

Why study at Swansea University

Swansea University’s mathematics provision is taught by an established department with a balance of pure and applied expertise, giving students rigorous training alongside applied project opportunities. Teaching typically combines lectures, small-group tutorials and practical computing sessions, so students gain both theoretical depth and hands-on modelling experience.

The University’s campus environment and links across Wales and the wider UK provide opportunities for industry engagement, placement activity and guest lectures from finance professionals. Facilities commonly include dedicated computing labs and access to mathematical software used in quantitative finance. Students also benefit from support services for study skills, mathematics learning and careers advice to help transition from degree study into employment or postgraduate study.