| Location | Term | Level | Credits (ECTS) | Current Convenor | 2018-19 |
|---|---|---|---|---|---|
| Canterbury | Spring View Timetable |
5 | 15 (7.5) | DR X Wang |
Pre-requisites
MA629 Probability and Inference or MA529 Probability and Statistics for Actuarial Science 2
Restrictions
None
Overview
This module covers aspects of Statistics which are particularly relevant to insurance. Some topics (such as risk theory and credibility theory) have been developed specifically for actuarial use. Other areas (such as Bayesian Statistics) have been developed in other contexts but now find applications in actuarial fields. Stochastic processes of events such as accidents, together with the financial flow of their payouts underpin much of the work. Since the earliest games of chance, the probability of ruin has been a topic of interest. Outline Syllabus includes: Decision Theory; Bayesian Statistics; Loss Distributions; Reinsurance; Credibility Theory; Empirical Bayes Credibility theory; Risk Models; Ruin Theory; Generalised Linear Models; Run-off Triangles.Marks on this module can count towards exemption from the professional examination CT6 of the Institute and Faculty of Actuaries. Please see http://www.kent.ac.uk/casri/Accreditation/index.html for further details.
Details
This module appears in:
Contact hours
32 lectures, 3 example classes (1 hour each)
Method of assessment
90% Examination, 10% Coursework
Indicative reading
The students are provided with the study notes published by the Actuarial Education Company and a copy of "Formulae and Tables for Examinations".
The following book is also relevant:
PJ Boland Statistical and Probabilistic Methods in Actuarial Science (Chapman & Hall, 2007) (R)
Learning outcomes
The Intended Subject Specific Learning Outcomes. On successful completion of the module students will be able to:
- explain basic concepts and models in decision analysis and statistics, as presented in the module, and apply them in insurance;
- construct risk models appropriate to short term insurance contracts and make the relevant inference;
- describe and apply the fundamental concepts of creditbility theory;
- describe and apply the basic methodology used in rating general insurance business;
- describe and apply techniques for analysing a delay (or run-off) triangle;
The Intended Generic Learning Outcomes. One successful completion of the module, students will:
- be able to demonstrate probabilistic and statistical skills in solving financial problems;
- have enhanced their conceptual skills and logical reasoning abaility;
- demonstrate a broad understanding of the range of application of statistics to financial processes.