Actuarial Mathematics BSc

3 Years On Campus Bachelors Program

University of Leeds

Program Overview

The Actuarial Mathematics BSc at the University of Leeds combines rigorous mathematical and statistical training with practical actuarial applications. It’s ideal for students aiming for careers in insurance, pensions, risk management, finance, or for progression toward professional actuarial qualifications.


Curriculum structure

Year 1 – Core mathematical and statistical foundations
In your first year, you’ll study modules such as Calculus, Linear Algebra, Probability, and Introduction to Statistics, building a solid foundation in quantitative methods. These modules provide the essential tools for actuarial modelling and financial analysis.

Year 2 – Developing actuarial and analytical skills
The second year introduces applied modules such as Financial Mathematics, Statistical Modelling, and Life Contingencies, enabling you to apply mathematics to insurance and risk problems. You’ll begin preparing for the early professional actuarial exams.

Year 3 – Advanced actuarial mathematics
In your final year, you’ll study advanced modules such as Risk Theory, Pension Mathematics, and Stochastic Processes, alongside a final-year project. This allows you to integrate your mathematical and statistical knowledge in actuarial applications, preparing for professional practice or postgraduate study.


Focus areas:
Actuarial science, mathematics, statistics, probability, risk modelling, financial mathematics

Learning outcomes:
Ability to apply mathematics and statistics to actuarial problems, strong quantitative and analytical skills, preparation for professional actuarial exams, problem-solving in finance and insurance

Professional alignment (accreditation):
Partially accredited by the Institute and Faculty of Actuaries (IFoA) and the Institute of Mathematics and its Applications (IMA), supporting progression toward professional actuarial qualification.

Reputation (employability & rankings):
The University of Leeds is consistently ranked in the QS World University Rankings by Subject for Mathematics and Statistics, and is recognised for strong graduate employability in actuarial and quantitative careers.

Experiential Learning (Research, Projects, Internships etc.)

At Durham University, the Actuarial Mathematics BSc degree combines rigorous mathematical training with practical actuarial skills, preparing you for professional actuarial exams and careers in insurance, pensions, risk management, and finance. From the first year, you’ll engage in applied learning through statistical modelling, probability, and financial mathematics, supported by research-active academics and specialist facilities. The programme is designed to develop both your analytical expertise and professional readiness:

  • Dedicated computing laboratories within the Department of Mathematical Sciences, used for actuarial modelling, statistical analysis, and computational coursework

  • Extensive use of R, Python, MATLAB, and Excel, integrated into modules covering probability theory, financial mathematics, risk modelling, and stochastic processes

  • Applied coursework and group projects, allowing you to implement actuarial and mathematical methods in real-world scenarios

  • Research-informed teaching, delivered by academics active in actuarial science, statistics, and applied mathematics

  • Opportunities for final-year individual projects, enabling you to explore actuarial, statistical, or mathematical topics in depth

  • Access to teaching and study spaces across Durham, including lecture theatres, seminar rooms, and dedicated computing facilities

  • Full use of the Durham University Library, providing specialist resources in mathematics, statistics, and actuarial science, including textbooks, journals, and online databases

  • Embedded career and professional support, including guidance for actuarial exams and preparation for graduate roles in finance, insurance, and risk management

This programme is ideal if you want a mathematics degree focused on actuarial science, combining strong theoretical foundations with practical, professional, and computational skills.

Progression & Future Opportunities

Graduates from the Actuarial Mathematics program are well-prepared for careers in actuarial consultancy, risk management, finance, and insurance analytics:

  • University Services for Employment: Leeds Careers Centre provides tailored one-to-one guidance, CV and interview workshops, internship support, and access to networking events with employers in actuarial science and finance.

  • Employment Stats and Salary Figures: Over 90% of graduates secure employment or further study within six months, with starting salaries typically ranging from £28,000–£45,000.

  • University–Industry Partnerships: The program works closely with top insurance firms, consulting companies, and financial institutions, offering internships, live projects, and guest lectures from industry professionals.

  • Long-Term Accreditation Value: Accredited by the Institute and Faculty of Actuaries (IFoA) and the Institute of Mathematics and its Applications (IMA), supporting professional qualification and career progression in actuarial science.

  • Graduation Outcomes: Graduates commonly pursue roles in actuarial consultancy, risk analysis, insurance analytics, financial consultancy, and data-driven decision-making roles.

Further Academic Progression:
Graduates can continue with MSc or PhD programs in Actuarial Science, Financial Mathematics, Data Analytics, or Applied Mathematics, providing advanced expertise for specialist careers or research.

Program Key Stats

£29,500 (Annual cost)
£9,535
£ 29
Sept Intake : 14th Jan


No
Yes

Eligibility Criteria

AAA
3.0
17
75

1300
NA
6.0
80
No

Additional Information & Requirements

Country Requirements

Career Options

  • Data Analyst
  • Statistician
  • Actuary
  • Financial Analyst
  • Investment Analyst
  • Quantitative Researcher
  • Operations Research Analyst
  • Risk Analyst
  • Economist
  • Market Research Analyst
  • Business Analyst
  • Data Scientist
  • Cryptographer
  • Software Developer
  • Machine Learning Engineer
  • Accountant
  • Auditor
  • Teacher
  • Research Scientist
  • Meteorologist
  • Biostatistician
  • Financial Planner
  • Mathematical Modeler
  • Academic Researcher
  • Artificial Intelligence Specialist

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