The unit covers a range of statistical models and methods for analysing quantitative actuarial data in general insurance. Both maximum likelihood estimation and Bayesian estimation methods are adopted for statistical inferences with the use of modern software tools such as the R and OpenBUGS packages. Topics covered include probability distributions for actuarial modelling, claim size modelling, claim frequency modelling, loss reserve forecasting, pure premium calculation, premium rates reviewing and revising (credibility theory), linear and generalised linear models, Poisson process and Markov process in actuarial modelling. Upon the completion of this unit and other relevant business analytics units, students may undertake professional examinations for actuaries or may get exemptions in some professional examination papers.
1x 2hr lecture per week and 1x 1hr tutorial per week
assignments (30%), mid-semester exam (20%), final exam (50%)
BUSS1020 or ECMT1010 or ENVX1001 or ENVX1002 or ((MATH1005 or MATH1015) and MATH1115) or 6 credit points in MATH 1000-level units including MATH1905.
QBUS2810 or DATA2002 or ECMT2110