Students
ACST3060 – Quantitative Methods for Risk Analysis
2026 – Session 2, In person-scheduled-weekday, North Ryde
General Information
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| Unit convenor and teaching staff |
Unit convenor and teaching staff
Unit Convenor
Ken Siu
Lecturer
Colin Zhang
|
|---|---|
| Credit points |
Credit points
10
|
| Prerequisites |
Prerequisites
ACST3058
|
| Corequisites |
Corequisites
|
| Co-badged status |
Co-badged status
ACST8085
|
| Unit description |
Unit description
This unit explores the use of statistical models in insurance: loss distributions with and without risk sharing, compound distributions and their applications in risk modelling, introduction to copulas, extreme value theory. The concepts underlying time series models and actuarial applications of time series models are also studied. Students gaining a weighted average of credit across all of ACST3058, ACST3060 and the CS2-related components of the assessment in ACST3059 (minimum mark of 60% on all three components) will satisfy the requirements for exemption from the professional subject CS2 of the Actuaries Institute. |
Important Academic Dates
Information about important academic dates including deadlines for withdrawing from units are available at https://www.mq.edu.au/study/calendar-of-dates
Learning Outcomes
On successful completion of this unit, you will be able to:
- ULO1: Model insurance claims using loss distributions.
- ULO2: Construct risk models with frequency and severity distributions.
- ULO3: Use premium principles to price insurance products.
- ULO4: Model dependence and extreme events by copulas and extreme value theory.
- ULO5: Apply time series models to financial and economic variables.
General Assessment Information
Late Submission Penalties
If you submit your assessment late, 5% of the total possible marks will be deducted for each day (including weekends), up to 7 days. Submissions more than 7 days late will receive a mark of 0.
Example 1 (out of 100):
If you score 85/100 but submit 20 hours late, you will lose 5 marks and receive 80/100.
Example 2 (out of 30):
If you score 27/30 but submit 20 hours late, you will lose 1.5 marks and receive 25.5/30.
Assessment Tasks
| Name | Weighting | Hurdle | Due | Groupwork/Individual | Short Extension | AI Approach |
|---|---|---|---|---|---|---|
| Formal examination: Test | 20% | No | 16/09/2026 | Individual | No | Observed |
| Professional practice: Risk analysis by using R | 20% | No | 30/10/2026 | Individual | Yes | Open AI |
| Formal examination | 60% | No | Exam Period | Individual | No | Observed |
Formal examination: Test
Assessment Type 1: Examination
Indicative Time on Task 2: 25 hours
Due: 16/09/2026
Weighting: 20%
Groupwork/Individual: Individual
Short extension 3: No
AI Approach: Observed
The purpose of this assessment is for you to demonstrate your ability to model insurance claims using loss distributions and to construct risk models incorporating frequency and severity distributions.
You will complete an individual in-class test to assess your understanding and application of these concepts.
Skills in focus:
- Discipline knowledge
Deliverable(s): Class test (approximately 90 minutes, including 10 mins reading time) during class time.
Individual assessment
On successful completion you will be able to:
- Model insurance claims using loss distributions.
- Construct risk models with frequency and severity distributions.
- Use premium principles to price insurance products.
- Model dependence and extreme events by copulas and extreme value theory.
Professional practice: Risk analysis by using R
Assessment Type 1: Problem-based task
Indicative Time on Task 2: 15 hours
Due: 30/10/2026
Weighting: 20%
Groupwork/Individual: Individual
Short extension 3: Yes
AI Approach: Open AI
The purpose of this assessment is for you to demonstrate your problem-solving skills in R statistical computing software by modelling insurance claims, building risk models, pricing using premium principles, and addressing dependence or extreme by enhancing your professional readiness
You will solve a set of questions available on iLearn using R software.
Skills in focus :
- Discipline knowledge
- Digital skills
- Critical thinking and problem solving
Deliverable(s): Written report including supporting documents, results of the analyses and R code. Only the written report will be marked.
Individual assessment
On successful completion you will be able to:
- Model insurance claims using loss distributions.
- Construct risk models with frequency and severity distributions.
- Use premium principles to price insurance products.
- Model dependence and extreme events by copulas and extreme value theory.
Formal examination
Assessment Type 1: Examination
Indicative Time on Task 2: 28 hours
Due: Exam Period
Weighting: 60%
Groupwork/Individual: Individual
Short extension 3: No
AI Approach: Observed
The purpose of this assessment is for you to formally demonstrate the expertise you have gained in this unit.
You will participate in a 2-hour exam held during the University Examination period. Important information about the exam will be made available on the unit iLearn page. You should also review the MQ Exams website for general tips.
Deliverable(s): Formal exam
Individual assessment
On successful completion you will be able to:
- Model insurance claims using loss distributions.
- Construct risk models with frequency and severity distributions.
- Use premium principles to price insurance products.
- Model dependence and extreme events by copulas and extreme value theory.
- Apply time series models to financial and economic variables.
1 If you need help with your assignment, please contact:
- the academic teaching staff in your unit for guidance in understanding or completing this type of assessment
- Academic Success for academic skills support.
2 Indicative time-on-task is an estimate of the time required for completion of the assessment task and is subject to individual variation.
3 An automatic short extension is available for some assessments. Apply through the Service Connect Portal.
Delivery and Resources
Delivery
The unit will be delivered by weekly lectures and tutorials.
Resources
The unit material will be available for download from iLearn. Some references or recommended reading materials will be introduced whenever appropriate. Please refer to iLearn for details. Students will be required to use iLearn, R, PDF, Excel, Word, a non-programmable calculator and other resources to be mentioned on iLearn.
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- Assessment Policy
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Results
Results published on platform other than eStudent, (eg. iLearn, Coursera etc.) or released directly by your Unit Convenor, are not confirmed as they are subject to final approval by the University. Once approved, final results will be sent to your student email address and will be made available in eStudent. For more information visit connect.mq.edu.au or if you are a Global MBA student contact globalmba.support@mq.edu.au
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Unit information based on version 2026.03 of the Handbook