Coursework
Master of Actuarial Science (Enhanced)
- CRICOS Code: 0100879
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What will I study?
Overview
The degree is designed to be completed in 2-years of full-time study or part time equivalent and requires completion of 200 points. The degree consists of 16 semester-length subjects comprising:
- 6 discipline core subjects;
- 2 capstone subjects; and
- 8 elective subjects.
Sample course plan
View some sample course plans to help you select subjects that will meet the requirements for this degree.
Sample course plan - Example 200 point plan
KEY
- Core
- Elective
- Capstone
Year 1
Total
100 Points
Semester 1
50 Points
- Core
ACTL90001 Mathematics of Finance I
12.5 Points
- Core
ACTL90006 Life Insurance Models I
12.5 Points
- Elective
ACCT90042 Accounting and Finance for Actuaries
12.5 Points
- Elective
ACTL90023 Data Analytics in Insurance 1
12.5 Points
- Core
Semester 2
50 Points
- Core
ACTL90002 Mathematics of Finance II
12.5 Points
- Core
ACTL90007 Life Insurance Models 2
12.5 Points
- Core
ACTL90021 Topics in Insurance and Finance
12.5 Points
- Capstone
ACTL90005 Life Contingencies
12.5 Points
- Core
Year 2
Total
100 Points
Semester 3
50 Points
- Core
ACTL90003 Mathematics of Finance III
12.5 Points
- Capstone
ACTL90020 General Insurance Modelling
12.5 Points
- Elective
ACTL90010 Actuarial Practice And Control I
12.5 Points
- Elective
ACTL90022 Economics for Actuaries
12.5 Points
- Core
Semester 4
50 Points
- Elective
ACTL90008 Statistical Techniques in Insurance
12.5 Points
- Elective
ACTL90011 Actuarial Practice and Control II
12.5 Points
- Elective
ACTL90019 Data Analytics in Insurance 2
12.5 Points
- Elective
12.5 Points
- Elective
Explore this course
Explore the subjects you could choose as part of this degree.
- 12.5 pts
Topics include data analysis, the principles of actuarial modelling, the description of financial transactions; the understanding of real and nominal interest rates, the time value of money, the present value and accumulated value for a given cashflow, the term structure of interest rates; the duration, convexity and immunisation of cashflows; the equation of value and its usage to solve various practical problems, project appraisals.
- 12.5 pts
Topics include: measures of investment risk, portfolio theory, models of asset returns, asset liability modelling, equilibrium models, the efficient markets hypothesis, stochastic models of security prices, and Brownian Motion and its application.
- 12.5 pts
This subject aims to provide students with grounding in advanced financial mathematics, covering option pricing under the binomial model; risk‐neutral pricing of derivative securities; Brownian motion; introduction to Itô΄ formula and SDEs; stochas asset models; Black‐Scholes model; arbitrage and hedging; interest‐rate models; actuarial applications and simple models for credit risk.
- 12.5 pts
Topics include survival models concepts; estimation procedures for lifetime distributions; multiple state models; multiple decrements; binomial and Poisson model of mortality; actuarial applications of continuous‐time and discrete‐time Markov processes; exact and census methods for estimating transition intensities based on age.
- 12.5 pts
This subject examines auditing and assurance services at an advanced level. It is designed to facilitate detailed analysis of complex situations auditors face in contemporary practice. Instruction is carried out by industry practitioners. Topics covered include the use of data analytics, engagement risk and practice management, and auditing asset and liability valuations. Students will have the opportunity to deepen their understanding of contemporary assurance practices.
- 12.5 pts
Topics include distributions of accumulations and present values; stochastic interest rate models; time series models; an introduction to ruin theory; claim run-off triangles; stochastic simulation.
- 12.5 pts
This subject has two primary aims:
To provide fundamental principles of actuarial modelling.
To discuss techniques used to model and value cashflows dependent on death, survival, or other uncertain risks.
- 12.5 pts
Topics include loss distribution with and without risk sharing; collective risk model, calculation of moments and moment generating function of aggregate claims, recursion formulae, effect of reinsurance; individual risk model, recursion formulae and approximations; copulas; extreme value theorems; time series.
- 12.5 pts
This subject has two main objectives. Firstly, it is designed to enable students to have the ability to analysis and interpret the financial statements of companies and financial institutions. Secondly, to provide a basic understanding of corporate finance including a knowledge of the instrument used by companies to raise finance and manage financial risks.
- 12.5 pts
This subject aims to further develop students’ knowledge of modern analytical tools and techniques, including GLM, shrinkage techniques (e.g., LASSO and ridge regression), tree-based methods (e.g., random forests and GBM) and neural networks. It also teaches students to connect data analytics work to the actuarial control cycle and real-world business environments. Effective communication of findings to a range of business decision making audiences is also stressed.
- 12.5 pts
Topics include insurance markets and products; underwriting and risk assessment; policy design; actuarial modelling; actuarial assumptions and feedback; reserving methods.
- 12.5 pts
This subject introduces core economic principles and how these can be used in a business environment to help decision making and behaviour. It provides the fundamental concepts of microeconomics that explain how economic agents make decisions and how these decisions interact. It explores the principles underlying macroeconomics that explain how the economic system works, where it fails and how decisions taken by economic agents affect the economic system.
- 12.5 pts
This subject aims to provide students with basic training on modern data analytics methods, which include linear regression, classification, resampling methods, spline-based methods, generalised additive models and tree-based methods. This subject focuses on applying the above methods to modelling non-life insurance claims frequency and severity.
- 12.5 pts
Topics include multiple linear regression; Spearman´s and Kendall´s measures of correlation; principal component analysis; generalised linear models; bootstrap method; Bayesian statistics; credibility theory.
- 12.5 pts
Topics include assessment of solvency; analysis of experience; analysis of surplus; actuarial techniques in the wider fields; and an introduction to professionalism.