Statistics for Insurance - MAT00061M
- Department: Mathematics
- Credit value: 10 credits
- Credit level: M
- Academic year of delivery: 2022-23
Related modules
Module will run
| Occurrence | Teaching period |
|---|---|
| A | Spring Term 2022-23 |
Module aims
This module aims to introduce statistics theory and methodology which are relevant to insurance and actuarial science.
Module learning outcomes
At the end of the module you should be able to:
- have developed a knowledge and good understanding of models for analysing insurance data;
- have a good degree of familiarity with distributions and inferential techniques in the analysis of insurance data;
- have a reasonable degree of familiarity with the main statistical theory in the analysis of insurance data;
- know what sorts of methodologies should be applied to model insurance risk in different periods;
- use statistical software to analyse insurance data by various methodologies.
Module content
This module covers the following five topics:
1) Claims reserving and pricing with run-off triangles;
2) Commonly-used loss distributions;
3) Risk theory;
4) Ruin theory;
5) Generalised linear models.
Indicative assessment
| Task | % of module mark |
|---|---|
| Closed/in-person Exam (Centrally scheduled) | 100.0 |
Special assessment rules
None
Indicative reassessment
| Task | % of module mark |
|---|---|
| Closed/in-person Exam (Centrally scheduled) | 100.0 |
Module feedback
Current Department policy on feedback is available in the undergraduate student handbook. Coursework and examinations will be marked and returned in accordance with this policy.
Indicative reading
Boland, P. (2011). Statistical and Probabilistic Methods in Actuarial Science. Chapman & Hall/CRC Interdisciplinary Statistics.
Cizek, P., Hardle, W. and Weron, R. (2011). Statistical Tools for Finance and Insurance (2nd Edition). Springer.
Daykin, C. D., Pentikainen, T. and Pesonen, M. (1993). Practical Risk Theory for Actuaries. Chapman & Hall/CRC.
Dickson, D. (2010). Insurance Risk and Ruin. International Series on Actuarial Science, Cambridge University Press.
Kaas, R., Goovaets, M. and Dhaene, J. (2008). Modern Actuarial Risk Theory: Using R. Springer