BSc Mathematics with Finance

3 Years On Campus Bachelors Program

University of Manchester

Program Overview

The BSc (Hons) Mathematics with Finance at University of Manchester gives students a strong grounding in mathematics while also teaching the fundamentals of finance and financial analysis. It suits those who enjoy rigorous maths and want a degree that opens pathways into banking, investment, risk‑management, data analytics, or further study in finance or mathematics.

Curriculum Structure

Year One
In the first year, the student studies core mathematics — including Linear Algebra, Real Analysis, Mathematical Foundations & Analysis, Vector Calculus, Ordinary Differential Equations, Probability I, and Statistics I. Alongside, introductory finance/business modules such as Fundamentals of Management, Financial Decision Making and Financial Reporting provide an introduction to financial systems and corporate finance.

Year Two
In the second year, the course deepens both mathematical and financial knowledge. Students take Introduction to Financial Mathematics, Probability and Statistics II, and core finance modules such as Investment Analysis and Foundations of Finance. Optional modules — including programming with Python, modelling, numerical analysis, or further pure‑math courses (e.g. metric spaces, algebra, PDEs) — let students tailor the degree depending on whether they lean more mathematical or finance‑oriented.

Year Three (Final Year)
In the final year, core finance‑math integration takes center stage: mandatory units include Financial Derivatives, Martingales with Applications to Finance, and Mathematical Modelling in Finance. On top of that, students can choose from a wide array of optional modules — ranging from deep pure/applied mathematics (e.g. geometry, number theory, topology, machine learning, differential geometry) to more finance/business‑oriented ones (e.g. corporate finance, accounting & financial reporting, financial engineering) — or even complete a staff‑supervised independent project.

Focus areas
Pure mathematics · Probability & statistics · Mathematical modelling · Financial mathematics · Derivatives & risk · Corporate finance · Quantitative finance · Data analysis & computation

Learning outcomes
Graduates will be able to apply advanced mathematical techniques — including real analysis, probability, statistics, and modelling — to analyse, model and solve complex financial problems; value derivatives; manage financial risk; understand corporate financial statements; and combine rigorous maths with practical finance and data skills.

Professional alignment (accreditation)
The programme is accredited by both the Royal Statistical Society (RSS) and the Institute of Mathematics and its Applications (IMA), making graduates eligible for recognized professional statuses: RSS’s “Graduate Statistician” (depending on chosen modules and honours class) and — when combined with suitable post‑graduate training or work experience — IMA accreditation towards “Chartered Mathematician.”

Reputation (employability & outcomes)
Graduates from this degree at Manchester are strongly sought after by employers in finance, banking, consulting, technology, data analytics, and other quantitative industries. A substantial proportion of graduates are employed or pursuing further studies within 15 months of graduation. The broad mix of rigorous maths and finance/business training gives flexibility — graduates can enter finance (e.g. investment banking, risk management, corporate finance), data science, or continue to postgraduate study in mathematics, finance or related fields.

Experiential Learning (Research, Projects, Internships etc.)

This programme offers a robust mathematical foundation along with in‑depth training in finance — giving students not only strong quantitative skills but also an understanding of financial decision‑making, markets, investment, risk, and financial instruments. The environment is highly supportive, with access to first-rate facilities — including modern computer clusters (with powerful mathematical and statistical software such as MATLAB, Minitab, Mathematica), and a well‑equipped university library, giving students the infrastructure they need to work on both theoretical and applied finance‑mathematics projects.

How students learn in practice — what the experience includes:

In Year 1, students cover core mathematics (linear algebra; real analysis; vector calculus; ordinary differential equations; probability; statistics) alongside foundational finance and business‑related units (financial decision‑making, financial reporting, fundamentals of management). This ensures a balanced grounding in both maths and finance from early on.
From Year 2 onwards, students choose among themes — including Pure Mathematics, Applied Mathematics, or Probability & Statistics — while continuing finance‑oriented modules such as “Introduction to Financial Mathematics”, investment analysis, and other finance/management units. Optional modules like programming with Python support computational and modelling skills.
In the final year, the curriculum includes rigorous finance‑math units such as “Financial Derivatives”, “Martingales with Applications to Finance”, and “Mathematical Modelling in Finance”. This allows students to apply advanced mathematical techniques (stochastic processes, modelling, statistics) directly to finance problems.
Teaching is delivered through lectures, small‑group tutorials, computer‑lab sessions, and coursework + examinations — giving both theoretical grounding and practical computational experience.
Students have the opportunity to undertake a work-based placement year, giving a chance to gain real‑world experience in finance or related industry — a strong boost for employability.

What makes this programme a strong launchpad for future careers or further study

Graduates come away with a versatile skill set: strong mathematics (analysis, probability and statistics, modelling), computational tools (Python and mathematical software), and financial knowledge (investment, derivatives, risk, reporting). This opens doors in finance, banking, quantitative analysis, risk management, data science, consulting, and more.
The finance‑focused coursework (derivatives, stochastic finance, financial modelling) makes the degree particularly attractive for roles in trading, financial engineering, risk analytics, and investment banking.
The option of a placement year means students can gain practical exposure and build industry contacts before graduation — a valuable advantage when seeking jobs or internships.
For those interested in academia or advanced qualifications, the strong mathematical base supports further postgraduate study (e.g. MSc in Finance, Mathematical Finance, Applied Mathematics, Data Science, etc.).

Facilities for Mathematics with Finance students include modern computer clusters with mathematical/statistical software (MATLAB, Minitab, Mathematica), computer labs, lecture theatres, and a well-resourced university library supporting both theoretical and applied mathematics and finance work.

Progression & Future Opportunities

A graduate from University of Manchester’s BSc (Hons) Mathematics with Finance will acquire a powerful combination of deep mathematical knowledge and practical finance‑theory skills — making them well suited for careers such as Quantitative Analyst, Financial Analyst, Risk Analyst, Data Analyst in finance, or Financial Modeller. Because the degree builds strong foundations in mathematics, probability & statistics, financial instruments and markets, graduates are equipped to work in banking, finance, fintech, data analysis, or quantitative finance roles.

What makes this degree stand out at Manchester:

Balanced mathematics + finance + optional specialisation: In early years students learn core mathematics. From the second year onward they choose themes (Pure Mathematics, Applied Mathematics, Probability & Statistics) in combination with finance‑oriented modules from the business school — giving flexibility to tailor learning towards mathematical theory or finance depending on interest.
Strong teaching environment and excellent facilities: Students study at the purpose‑built mathematics building, with access to computing labs and software for mathematical & statistical work — supporting both theoretical and applied learning.
Option for work placement / real‑world experience: The programme offers a chance to take a work‑based placement year, allowing students to gain practical experience in finance or industry — often improving their employability and chances of securing a job after graduation.
Accreditation and professional recognition potential: The course is accredited by both the Royal Statistical Society (RSS) and the Institute of Mathematics and its Applications (IMA), meaning graduates are eligible for recognised professional credentials (e.g. Graduate Statistician status, or, with further training/experience, the pathway to Chartered Mathematician).
Strong graduate employability and employer demand: Historically, a high percentage of Mathematics with Finance graduates are in work or further study within 15 months of graduation — reflecting the demand from employers across finance, computing, industry and business sectors.

Career paths graduates typically follow
Graduates of this course are prepared for roles including:

Quantitative Analyst or Quant‑Modeller in banks, hedge funds or finance firms
Financial Analyst / Financial Data Analyst / Risk Analyst in banking, corporate finance, or insurance
Data Analyst or Statistical Analyst leveraging mathematical and statistical skills in finance or business analytics
Financial Engineer, Portfolio Analyst or roles dealing with derivatives, modelling and investment decisions
Roles in industry or consulting where strong numerical, modelling and analytical skills are valued

Long‑term value and accreditation
Given the rigorous combination of mathematics and finance, graduates remain versatile: they can pivot between finance, data science, analytics, or further quantitative specializations. The dual accreditation (RSS and IMA) enhances their professional credibility and makes them eligible for recognized credentials — which helps long‑term career mobility and credibility in financial, statistical, and analytical fields.

Further Academic Progression:
After completing the BSc (Hons) Mathematics with Finance, a student could move on to a Master’s degree — for example in Quantitative Finance, Mathematical Finance, Financial Engineering, Applied Mathematics or Data Science. If interested in research, they could also pursue doctoral studies (MSc → PhD) in mathematics, statistics or mathematical finance — opening pathways into academia or high‑end quantitative research.