Bachelor of Science (BSc)

BSc Mathematics with Finance

  • Duration: 3 years
  • Year of entry: 2025
  • UCAS course code: G1N3 / Institution code: M20
  • Key features:
  • Scholarships available
  • Accredited course

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Fees and funding

Fees

Tuition fees for home students commencing their studies in September 2025 will be £9,535 per annum (subject to Parliamentary approval). Tuition fees for international students will be £34,500 per annum. For general information please see the undergraduate finance pages.

Policy on additional costs

All students should normally be able to complete their programme of study without incurring additional study costs over and above the tuition fee for that programme. Any unavoidable additional compulsory costs totalling more than 1% of the annual home undergraduate fee per annum, regardless of whether the programme in question is undergraduate or postgraduate taught, will be made clear to you at the point of application. Further information can be found in the University's Policy on additional costs incurred by students on undergraduate and postgraduate taught programmes (PDF document, 91KB).

Scholarships/sponsorships

The University of Manchester is committed to attracting and supporting the very best students. We have a focus on nurturing talent and ability and we want to make sure that you have the opportunity to study here, regardless of your financial circumstances.

For information about scholarships and bursaries please visit our undergraduate student finance pages and our Department funding pages

Course unit details:
Tools for Risk Management

Course unit fact file
Unit code MATH37542
Credit rating 10
Unit level Level 3
Teaching period(s) Semester 2
Available as a free choice unit? No

Overview

A “risk” is any future gain/loss of uncertain size, and obviously we would like to be able to “manage” such risks. From a mathematical perspective that entails: model and analyse the risk, in order to understand the situation and make sensible decisions. The uncertainty involved means that random variables and more generally probability theory are very important fundamentals. Building on these, many tools and techniques for risk management have been developed over time, and in this course we will discuss some of the most prominent ones. Although the focus will mainly be on examples from/applications in finance, insurance and related, the possible applications are much more diverse. This course also contains some light use of the software package R.

Note: this course does not consider (investing in) financial markets, there are several other courses dedicated to that topic. 

Pre/co-requisites

Unit title Unit code Requirement type Description
Probability and Statistics 2 MATH27720 Pre-Requisite Compulsory

Aims

The unit aims to: introduce students to a number of (mathematical) risk management tools prominent in finance, insurance and elsewhere. 

Learning outcomes

On the successful completion of the course, students will be able to: 

  • Implement and use Monte Carlo simulations to analyse various characteristics of random quantities
  • Discuss and evaluate dependence between random variables using copulas and related concepts  
  • Apply risk measures to random quantities and interpret the result
  • Build and evaluate appropriate models for risks, including parameter dependence and risk sharing

Syllabus

1. Monte Carlo simulations [2 weeks]

2. Copulas [4 weeks]

3. Risk measures [2 weeks]

4. Loss Models [3 weeks] 

Teaching and learning methods

Initially, each week a two hour lecture in which the materials are discussed followed by a one hour tutorial in which exercises are discussed. Later, when the course materials are fully developed and tested, we will move to a “flipped classroom” approach. 

Assessment methods

Method Weight
Other 20%
Written exam 80%

End of semester exam - 80% weighting

In-class test (computer cluster) - 20% weighting

Feedback methods

Individual feedback for in-class test after marking completed.

Group level feedback for exam after marking completed.

Recommended reading

Extensive typeset notes to be provided.

Study hours

Scheduled activity hours
eAssessment 1
Lectures 22
Tutorials 11
Independent study hours
Independent study 66

Teaching staff

Staff member Role
Kees Van Schaik Unit coordinator

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