Financial Mathematics

Financial mathematics applies the tools of advanced mathematics to the analysis of financial markets, instruments, and risk. It is a discipline that sits at the boundary of pure mathematical reasoning and practical financial problem-solving, asking questions such as how to price a derivative contract, how to measure and manage risk in a portfolio, and how to model the behaviour of asset prices over time. These are not merely academic questions: they are the problems that financial institutions, central banks, insurers, and technology companies need to solve every day.

At the University of Surrey you will study across three years on a full-time programme. The curriculum covers the mathematical foundations, including probability theory, stochastic processes, differential equations, and numerical methods, alongside the financial content, including derivatives pricing, risk management, portfolio optimisation, and financial modelling. You will develop strong quantitative skills and the ability to use mathematical tools to analyse and solve problems in financial contexts, but the degree also prepares you for adjacent fields: the techniques used in financial mathematics are increasingly relevant to data science, machine learning, and software engineering, and the programme explicitly prepares you for these directions as well as for more traditional finance roles.

Computational work and programming are woven through the curriculum, reflecting the reality that modern financial mathematics is heavily computational.

Graduates of financial mathematics enter careers across a range of analytically demanding sectors. Quantitative analysis and modelling roles in investment banks, asset managers, hedge funds, and insurance companies are well-established directions. Risk management, financial technology, and data science roles across financial services draw heavily on the quantitative skills the degree develops.

Actuarial careers are a further option for students who complete relevant professional examinations alongside the degree. Postgraduate study in financial mathematics, mathematical finance, statistics, or data science is a natural route for those who wish to deepen their specialism or pursue research roles.