Mathematics with Finance BSc

Mathematics with Finance is a degree that combines mathematical theory, statistical analysis, and financial principles to understand and solve problems in banking, investment, and economics. It focuses on how mathematical models and quantitative techniques are used to analyse financial markets, manage risk, and make informed business decisions.

A Bachelor of Science (BSc) in Mathematics with Finance provides students with strong analytical and numerical skills, alongside a practical understanding of how mathematics underpins modern finance. The course prepares graduates for careers in areas such as investment banking, actuarial science, data analysis, and financial modelling.

Why Study Mathematics with Finance?

There are many reasons why students choose to study Mathematics with Finance:

• An interest in applying mathematics to economics, business, and financial systems.

  
  

• Development of advanced analytical, problem-solving, and quantitative reasoning skills.

  
  

• Understanding how mathematics supports financial decision-making and risk assessment.

  
  

• Preparation for high-demand careers in banking, data analysis, and financial services.

  
  

• The opportunity to combine theory with real-world financial applications.

  
  

• A foundation for postgraduate study in finance, economics, or applied mathematics.

  
  

This degree suits students who are logical, detail-oriented, and enjoy working with numbers, patterns, and data to understand how money and markets behave.

Course Duration and Structure

In the UK, a BSc in Mathematics with Finance typically takes three years of full-time study, or four years with a placement year or integrated Master’s option (MMath).

A typical course structure includes:

Year 1: Core modules in calculus, linear algebra, probability, and statistics, alongside introductory finance and economics.

Year 2: Intermediate modules in mathematical modelling, numerical methods, financial mathematics, and econometrics. Students also study corporate finance, investment theory, and risk analysis.

Year 3: Advanced study in stochastic processes, financial derivatives, and quantitative risk management. The final year often includes a dissertation or research project applying mathematics to a financial problem.

Some universities also offer optional modules in machine learning, data analytics, or computational finance, as well as internships or industry placements.

Entry Requirements

Entry requirements vary by university but typically include one of the following:

• A Levels: Including Mathematics, and sometimes Further Mathematics or Economics.

  
  

• BTEC: A relevant Extended Diploma in Applied Science, Business, or Engineering.

  
  

• International Baccalaureate (IB): Including Higher Level Mathematics or Mathematics: Analysis and Approaches.

  
  

• Other qualifications: Access or foundation courses in Mathematics, Economics, or Finance.

  
  

• English language proficiency: Required for applicants whose first language is not English.

Applicants should have strong numerical ability and an interest in both mathematics and financial systems.

Teaching and Assessment

Mathematics with Finance degrees combine theoretical and applied learning through lectures, tutorials, computer-based workshops, and independent study. Students learn through:

• Lectures and small-group tutorials

  
  

• Practical workshops in finance and computing

  
  

• Group projects and case studies

  
  

• Independent research and applied projects

  
  

• Guest lectures from industry professionals

  
  

Assessment methods typically include:

• Written examinations

  
  

• Coursework and problem sets

  
  

• Data analysis and financial modelling projects

  
  

• Group presentations and reports

  
  

• A final dissertation or applied finance project

  
  

Courses often use mathematical and financial software such as MATLAB, Python, R, or Excel for data modelling and quantitative analysis.

Skills You Will Develop

A degree in Mathematics with Finance develops both theoretical and practical skills that are valued across multiple industries, including:

• Mathematical and statistical modelling

  
  

• Financial analysis and quantitative reasoning

  
  

• Risk management and forecasting

  
  

• Problem-solving and logical thinking

  
  

• Programming and computational analysis

  
  

• Communication and presentation of data

  
  

• Research and critical evaluation

  
  

• Decision-making under uncertainty

These skills are essential in finance, banking, data science, and business analytics.

Career Prospects

Graduates of Mathematics with Finance degrees are highly employable in a wide range of analytical, technical, and financial roles. The combination of mathematical expertise and financial understanding is particularly valued in the banking and investment sectors.

Typical career paths include:

• Quantitative analyst or financial modeller

  
  

• Investment analyst or portfolio manager

  
  

• Actuary or risk manager

  
  

• Data analyst or data scientist

  
  

• Financial consultant or advisor

  
  

• Corporate finance analyst

  
  

• Insurance or pensions analyst

  
  

• Researcher or academic in applied mathematics or finance

Employers include banks, insurance firms, investment companies, consultancies, and government departments.

Tips for Prospective Students

• Strengthen your knowledge of mathematics, statistics, and economics before starting the degree.

  
  

• Learn basic programming and data analysis skills using Python or Excel.

  
  

• Follow financial news and trends to understand real-world applications of your studies.

  
  

• Practise problem-solving and analytical reasoning regularly.

  
  

• Seek internships or part-time work in finance or data analytics.

  
  

• Engage with university finance or investment societies to build experience and networks.

Course Variations

Universities offer several related or specialist Mathematics and Finance degrees, such as:

• Mathematics with Finance (General): Balanced study of mathematics and financial principles.

  
  

• Financial Mathematics: Focusing on stochastic modelling and quantitative analysis.

  
  

• Mathematics with Economics: Exploring the mathematical foundations of economic systems.

  
  

• Actuarial Mathematics: Applying mathematics to risk management and insurance.

  
  

• Mathematics and Accounting: Combining quantitative and business-focused study.

  
  

• Computational Finance: Emphasising algorithms, modelling, and financial computing.

  
  

• Year Abroad or Placement Year: Offering professional or international experience.

Recommended Wider Reading for Aspiring Mathematics with Finance Students

For those considering or beginning a degree in Mathematics with Finance, the following books and resources offer useful insight and preparation:

“The Mathematics of Finance” by Steven Roman – A clear introduction to financial mathematics and models.

“The Signal and the Noise” by Nate Silver – An exploration of prediction and uncertainty in data and finance.

“Fooled by Randomness” by Nassim Nicholas Taleb – Examines probability and risk in financial decision-making.

“An Introduction to Quantitative Finance” by Stephen Blyth – A practical look at financial modelling.

“Principles of Corporate Finance” by Richard Brealey, Stewart Myers, and Franklin Allen – A foundational text for finance students.

The Institute and Faculty of Actuaries (IFoA) – Offers professional insight into mathematics and risk careers.

Financial Times and The Economist – Recommended for keeping up with financial developments and market trends.