Students
ACST862 – General Insurance Pricing and Reserving
2014 – S2 Day
General Information
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| Unit convenor and teaching staff |
Unit convenor and teaching staff
Unit Convenor
Piet de Jong
Contact via email
E4A610
Tues 15h-16h
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| Credit points |
Credit points
4
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| Prerequisites |
Prerequisites
STAT806 or STAT810(P)
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| Corequisites |
Corequisites
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| Co-badged status |
Co-badged status
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| Unit description |
Unit description
This unit examines the use of statistical models in the general insurance context. Applications will include methods of estimating reserves for future insurance payments, generalised linear models and time series models.
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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:
- Use the R statistical software package to conduct statistical analyses of the types covered in this unit.
- Understand and perform calculations using simple no claim discount systems.
- Understand and apply the method of maximum likelihood estimation.
- Understand and apply generalised linear models.
- Understand simple stationary univariate time series models for description and forecasting.
- Understand and apply deterministic and basic stochastic methods for the calculation of outstanding claims provisions in general insurance.
- Apply knowledge and understanding to a complex problem.
General Assessment Information
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To be eligible to pass this unit, a pass is required in the final examination
- Criteria and standards for grading
- Numerically correct answers based on correct reasoning
- Submission methods
- Assignments are submitted via iLearn
- Midterm is in class on the indicated date
- Late assessments, extensions, penalties, resubmissions
- No extensions will be granted. Students who have not submitted the task prior to the deadline will be awarded a mark of 0 for the task, except for cases in which an application for special consideration is made and approved.
- Midterm and Final examination conditions.
- You are permitted ONE A4 page of paper containing reference material printed on both sides. The material may be handwritten or typed. The page will not be returned at the end of the midterm or final examination.
- It is the responsibility of students to view their marks for each within session assessment on iLearn within 20 working days of posting. If there are any discrepancies, students must contact the unit convenor immediately. Failure to do so will mean that queries received after the release of final results regarding assessment marks (not including the final exam mark) will not be addressed.
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Standardised Numerical Grade (SNG) will be awarded based on your overall performance. An SNG gives you an indication of how you have performed within the band for your descriptive grade. The SNG is not a mark, and you may not be able to work it out based on your raw examination and other assessment marks. Nor are you able to determine you are “one mark away” from a different grade.
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Supplementary Exams. Further information regarding supplementary exams, including dates, is available here http://www.businessandeconomics.mq.edu.au/current_students/undergraduate/how_do_i/special_consideration
Assessment Tasks
| Name | Weighting | Due |
|---|---|---|
| 1. Class Test | 10% | Tuesday 7 October 4pm |
| 2. Group Assignment | 20% | TBA |
| 3. Final Examination | 70% | Examination period |
1. Class Test
Due: Tuesday 7 October 4pm
Weighting: 10%
Closed book test. Non-programmable calculators with no text-retrieval capacity are allowed.
On successful completion you will be able to:
- Use the R statistical software package to conduct statistical analyses of the types covered in this unit.
- Understand and perform calculations using simple no claim discount systems.
- Understand and apply the method of maximum likelihood estimation.
- Understand and apply generalised linear models.
2. Group Assignment
Due: TBA
Weighting: 20%
Application of methods from the unit to the problem of forecasting mortality rates.
On successful completion you will be able to:
- Use the R statistical software package to conduct statistical analyses of the types covered in this unit.
- Understand and apply the method of maximum likelihood estimation.
- Understand and apply generalised linear models.
- Understand simple stationary univariate time series models for description and forecasting.
- Apply knowledge and understanding to a complex problem.
3. Final Examination
Due: Examination period
Weighting: 70%
Examination under usual exam conditions. Formulae sheet will be provided. Non-programmable calculators with no text-retrieval capacity are allowed.
On successful completion you will be able to:
- Use the R statistical software package to conduct statistical analyses of the types covered in this unit.
- Understand and perform calculations using simple no claim discount systems.
- Understand and apply the method of maximum likelihood estimation.
- Understand and apply generalised linear models.
- Understand simple stationary univariate time series models for description and forecasting.
- Understand and apply deterministic and basic stochastic methods for the calculation of outstanding claims provisions in general insurance.
- Apply knowledge and understanding to a complex problem.
Delivery and Resources
Classes
The timetable for classes can be found on the University web site at www.timetables.mq.edu.au.
Required and Recommended Texts and/or Materials
Required texts
Lecture Handouts (i.e. notes with gaps) are available for downloading from the ACST357/862 teaching website.
Optional ActEd material
The ActEd CT6 are not set as required or recommended reading for this unit, since the unit notes are comprehensive and detailed.
Other useful references
Hossack, I.B., Pollard J.H, and Zehnwirth, B. (1999). Introductory statistics with applications in general insurance, second edition. Cambridge University Press: Cambridge.
De Jong, P. and Heller, G.Z., (2008). Generalized linear models for Insurance Data. Cambridge University Press: Cambridge.
Casualty Actuarial Society. (2001). Foundations of Casualty Actuarial Science, 4th edition. Casualty Actuarial Society.
Unit Web Page
To access the website, go to http://ilearn.mq.edu.au and login using your usual login and password.
Learning and Teaching Activities
The unit is taught using three hours of lectures and a weekly tutorial. Tutorials commence in Week 2.
You are expected to read lecture materials in advance of the lectures and to participate actively in the tutorial classes.
Technology Used and Required
MS Excel and MS Word will be used throughout the unit.
The R statistical software package will be used throughout the unit. Students will be required to use a non-programmable calculator in the final examination and during the in-class test.
What has changed since the previous offering of this unit?
Development of a new assignment relating to forecasting mortality rates and updates to material in the curriculum to reflect minor changes to the CT6 professional syllabus.
Unit Schedule
|
Week Number |
Week Beginning Monday |
Topic and Notes | Tutorial |
| 1 |
4 August |
Section 1: Introduction to R | No tutorial |
| 2 |
11 August |
Section 2: No claim discount, Section 3: MLE |
Section 1 Exercises |
| 3 |
18 August |
Section 3: MLE |
Section 2 Exercises |
| 4 |
25 August |
Section 4: Generalized Linear Models I | Section 3 Exercises |
| 5 | 1 September | Section 5: Generalized Linear Models II | Section 4 Exercises |
| 6 | 8 September | Section 6: Time Series I | Section 5 Exercises |
| 7 | 15 September |
Section 7: Time Series II:
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Mock Test |
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STUDY BREAK |
22 September 29 September |
No classes No classes |
STUDY BREAK |
| 8 | 6 October |
Tuesday: Class Test: Wed: Section 7 Time Series II |
Section 6: Exercises |
| 9 | 13 October | Section 8: Time Series III | Section 7 Exercises |
| 10 | 20 October |
Section 9: Time Series IV: Section 10: Outstanding Claims (deterministic) |
Section 8 Exercises |
| 11 | 20 October | Section 10: Outstanding Claims (deterministic) | Section 9 Exercises |
| 12 | 27 October | Section 11: Outstanding Claims (stochastic) | Section 10 Exercises |
| 13 |
3 November |
Section 11: Outstanding Claims (stochastic) | Section 11 Exercises |
Policies and Procedures
Macquarie University policies and procedures are accessible from Policy Central. Students should be aware of the following policies in particular with regard to Learning and Teaching:
Academic Honesty Policy http://mq.edu.au/policy/docs/academic_honesty/policy.html
Assessment Policy http://mq.edu.au/policy/docs/assessment/policy.html
Grading Policy http://mq.edu.au/policy/docs/grading/policy.html
Grade Appeal Policy http://mq.edu.au/policy/docs/gradeappeal/policy.html
Grievance Management Policy http://mq.edu.au/policy/docs/grievance_management/policy.html
Disruption to Studies Policy http://www.mq.edu.au/policy/docs/disruption_studies/policy.html The Disruption to Studies Policy is effective from March 3 2014 and replaces the Special Consideration Policy.
In addition, a number of other policies can be found in the Learning and Teaching Category of Policy Central.
Student Code of Conduct
Macquarie University students have a responsibility to be familiar with the Student Code of Conduct: https://students.mq.edu.au/support/student_conduct/
Student Support
Macquarie University provides a range of support services for students. For details, visit http://students.mq.edu.au/support/
Learning Skills
Learning Skills (mq.edu.au/learningskills) provides academic writing resources and study strategies to improve your marks and take control of your study.
Student Services and Support
Students with a disability are encouraged to contact the Disability Service who can provide appropriate help with any issues that arise during their studies.
Student Enquiries
For all student enquiries, visit Student Connect at ask.mq.edu.au
IT Help
For help with University computer systems and technology, visit http://informatics.mq.edu.au/help/.
When using the University's IT, you must adhere to the Acceptable Use Policy. The policy applies to all who connect to the MQ network including students.
Graduate Capabilities
PG - Discipline Knowledge and Skills
Our postgraduates will be able to demonstrate a significantly enhanced depth and breadth of knowledge, scholarly understanding, and specific subject content knowledge in their chosen fields.
This graduate capability is supported by:
Learning outcomes
- Understand and perform calculations using simple no claim discount systems.
- Understand and apply the method of maximum likelihood estimation.
- Understand and apply generalised linear models.
- Understand simple stationary univariate time series models for description and forecasting.
- Understand and apply deterministic and basic stochastic methods for the calculation of outstanding claims provisions in general insurance.
Assessment tasks
- 1. Class Test
- 2. Group Assignment
- 3. Final Examination
PG - Critical, Analytical and Integrative Thinking
Our postgraduates will be capable of utilising and reflecting on prior knowledge and experience, of applying higher level critical thinking skills, and of integrating and synthesising learning and knowledge from a range of sources and environments. A characteristic of this form of thinking is the generation of new, professionally oriented knowledge through personal or group-based critique of practice and theory.
This graduate capability is supported by:
Learning outcomes
- Use the R statistical software package to conduct statistical analyses of the types covered in this unit.
- Understand and perform calculations using simple no claim discount systems.
- Understand and apply the method of maximum likelihood estimation.
- Understand and apply generalised linear models.
- Understand simple stationary univariate time series models for description and forecasting.
- Understand and apply deterministic and basic stochastic methods for the calculation of outstanding claims provisions in general insurance.
- Apply knowledge and understanding to a complex problem.
Assessment tasks
- 1. Class Test
- 2. Group Assignment
- 3. Final Examination
PG - Research and Problem Solving Capability
Our postgraduates will be capable of systematic enquiry; able to use research skills to create new knowledge that can be applied to real world issues, or contribute to a field of study or practice to enhance society. They will be capable of creative questioning, problem finding and problem solving.
This graduate capability is supported by:
Learning outcomes
- Use the R statistical software package to conduct statistical analyses of the types covered in this unit.
- Understand and perform calculations using simple no claim discount systems.
- Understand and apply the method of maximum likelihood estimation.
- Understand and apply generalised linear models.
- Understand simple stationary univariate time series models for description and forecasting.
- Understand and apply deterministic and basic stochastic methods for the calculation of outstanding claims provisions in general insurance.
- Apply knowledge and understanding to a complex problem.
Assessment tasks
- 1. Class Test
- 2. Group Assignment
- 3. Final Examination
Research and Practice
The unit will include some links to research through the use of a group assignment. Professional practice in the area of general insurance will also be discussed during the unit.