Bachelor of Actuarial Science (Honours)

The aim of the Actuarial Control Cycle 1 and 2 is to provide students with an understanding of how the underlying actuarial principles can be applied to a range of real-world problems and issues in commercial and business environments. Applications will include various insurance practice areas and wider fields. Examples will be drawn from traditional and non-traditional areas to illustrate and establish the underlying actuarial principles in a problem-based learning approach, using case studies and business-based examples to cover contemporary issues.  This subject, Actuarial Control Cycle 1, introduces the concept of the Actuarial Control Cycle and uses it as a framework to analyse the impact of issues such as legislative changes and technological changes on the firm.

The aim of the Actuarial Control Cycle 1 and 2 is to provide students with an understanding of how the underlying actuarial principles can be applied to a range of real-world problems and issues in commercial and business environments. Applications will include various insurance practice areas and wider fields. Examples will be drawn from traditional and non-traditional areas to illustrate and establish the underlying actuarial principles in a problem-based learning approach, using case studies and business-based examples to cover contemporary issues.  This subject, Actuarial Control Cycle 2, is the sequel to Actuarial Control Cycle 1. The focus is on advanced applications of the Actuarial Control Cycle framework to a broad array of business issues.

This advanced subject provides an opportunity for students to work on an applied research project in actuarial science. Students will work on a topic motivated by recent developments and innovations in actuarial industries or more generally in the financial services markets.

This advanced subject provides an opportunity for students to work on an applied research project in actuarial science. Students will work on a topic motivated by recent developments and innovations in actuarial industries or more generally in the financial services markets.

This subject covers the theory and practice of modern statistical learning, regression and classification modelling. Techniques covered range from traditional model selection and generalised linear model structures to modern, computer-intensive methods including generalised additive models, splines and tree methods. Methods to handle continuous, ordinal and nominal response variables and assessment of fit via cross-validation and residual diagnostics are also considered.  All techniques will be investigated via practical application on real data using the statistical software package R.