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The University of Southampton

STAT3010 Statistical Methods in Insurance

Module Overview

Aims and Objectives

Learning Outcomes

Learning Outcomes

Having successfully completed this module you will be able to:

  • Understand the definitions of some basic insurance terms, particular those relating to short-term contracts
  • Understand the properties of some loss distributions: gamma, exponential, Pareto, generalised Pareto, normal, log-normal, Weibull and Burr, and how to fit them to complete claim size data
  • Understand how simple forms of proportional and excess of loss re-insurance are arranged
  • Model the distribution of the aggregate claims for both the insurer and the re-insurer, particularly using the compound Poisson distribution
  • Use Bayesian approaches to credibility theory to calculate premiums in general insurance
  • Describe and apply basic principles of machine learning
  • Understand the fundamental concepts of generalised linear models and how they may be applied
  • Understand the main concepts underlying the analysis of time series and how to apply them
  • Apply problem solving and numerical skills


Review of distribution theory; loss distributions; risk models – collective and individual; reinsurance; copulas; extreme value theory; Bayesian credibility theory; machine learning; generalised linear models; time series.

Learning and Teaching

Teaching and learning methods

If full face-to-face teaching has not been resumed, teaching will be delivered by a mixture of synchronous and asynchronous online methods, which may include lectures, quizzes, discussion boards, workshop activities, exercises, and videos. A range of resources will also be provided for further self-directed study. Face-to-face teaching opportunities will be explored depending on circumstances and feasibility.

Independent Study105
Total study time150

Resources & Reading list

Dobson, A. J. (2001). An Introduction to Generalized Linear Models. 

Dickson, D. C. M. (2005). Insurance Risk and Ruin. 

Chatfield, C. (2004). The Analysis of Time Series. 

Klugman, S. A., Panjer, H. H. and Willmot, G. E. (2008). Loss Models: From Data to Decisions. 

Boland, P. J. (2007). Statistical and Probabilistic Methods in Actuarial Science. 


Assessment Strategy

There will be opportunities to evaluate your progress through formative assessment, with summative assessment based on a class test, two assignments and a final exam.


MethodPercentage contribution
Assignment 10%
Assignment 10%
Class Test 10%
Exam  (2 hours) 70%


MethodPercentage contribution
Exam 100%

Repeat Information

Repeat type: Internal & External

Linked modules

Pre-requisite: ECON2006 OR MATH2011


Costs associated with this module

Students are responsible for meeting the cost of essential textbooks, and of producing such essays, assignments, laboratory reports and dissertations as are required to fulfil the academic requirements for each programme of study.

In addition to this, students registered for this module typically also have to pay for:

Books and Stationery equipment

You will require a copy of Formulae and Tables for Actuarial Examinations 2002, 2nd edition, the "Gold Book".

Recommended texts for this module may be available in limited supply in the University Library and students may wish to purchase reading texts as appropriate.

Please also ensure you read the section on additional costs in the University’s Fees, Charges and Expenses Regulations in the University Calendar available at

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