Attributes, outcomes and skills: Master of Actuarial Science (Extended) (MC-ACTSCEX)

You’re currently viewing the 2021 version of this course

Intended learning outcomes

Describe, explain and apply the fundamental theories of actuarial science as they apply in life insurance, general insurance and superannuation;
Assess the suitability of actuarial, financial and economic models in solving actuarial problems;
Interpret and critically evaluate articles in the actuarial research literature.
Analyse actuarial data using advanced statistical techniques;
Calculate quantities such as premiums, reserves and superannuation contribution rates using actuarial techniques;
Analyse real and hypothetical problems in insurance and superannuation;
Demonstrate creativity and initiative in application of knowledge to problem solving and innovation;
Describe the core areas of actuarial practice and relate to those areas actuarial principles, theories and models;
Demonstrate a capacity to successfully work independently with personal accountability;
Execute a project requiring research or a real-world application.

Recognising the interrelationships and synergies which exist between the disciplines of the faculty;
Synthesizing ideas, theories and data in developing solutions to actuarial problems;
Critical evaluation of evidence in support of an argument or proposition;
Problem solving in actuarial practice through the application of appropriate theories, principles and data;
The use of software packages applicable to actuarial and statistical modelling;
Written and oral communication of actuarial ideas, theories and solutions to peers and the wider community;
Research including the retrieval of information from a variety of sources.

Receptive to alternate ideas through a review of the literature and through class participation and assessment;
Ethical in their approach to research and work practices;
Advanced in their use, critical evaluation and testing of actuarial models;
Adept in statistical reasoning through completion of core quantitative subjects in the degree;
Skilled in working effectively with computer software for the analysis of data;
Adept at retrieval, summary and interpretation of actuarial and financial information through class exercises and assessment;
Advanced in problem solving through their understanding of financial, statistical and actuarial techniques;
Able to apply and synthesise mathematical, statistical, financial and actuarial theory, models and evidence to a variety of financial and insurance issues;
Able to apply data science in insurance;
Independent and effective in communication of ideas;
Able to collaborate and be effective in team work.

Last updated: 17 December 2021