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.

90% Exam, 10% Coursework

• BSc students are recommended to purchase the relevant study notes published by the Actuarial Education Company. Arrangements will be made for students to purchase these directly from the publisher at a discounted price. The BSc students are strongly advised to purchase a copy of "Formulae and Tables for Examinations". This can be purchased at a discount price through the School - further information will be given in class. The following books are also relevant:
• PJ Boland Statistical and Probabilistic Methods in Actuarial Science (Chapman & Hall, 2007) (R)
• N Bowers et al. Actuarial Mathematics. (Society of Actuaries, 1986). (B)
• IB Hossack, JH Pollard, & B Zehnwirth Introductory Statistics with Applications in General Insurance. (CUP 1983)(B)

See the library reading list for this module

• The Intended Subject Specific Learning Outcomes and, as Appropriate, Their Relationship to Programme 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 related statistical inference; -describe and apply the fundamental concepts of credibility 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 and, as Appropriate, Their Relationship to Programme Learning Outcomes: On 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 ability; -demonstrate a broad understanding of the range of application of statistics to financial processes

MA629 Probability and Inference or MA529 Probability and Statistics for Actuarial Science 2