Students

ACST357 – 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
piet.dejong@mq.edu.au
Contact via email
E4A610
Tues 15h-16h
Credit points Credit points
3
Prerequisites Prerequisites
ACST356(P) and STAT271(P)
Corequisites Corequisites
Co-badged status Co-badged status
Unit description Unit description
This unit examines the use of statistical models in general insurance. The models include those used in time series analysis, generalised linear statistical modelling and runoff triangle models. Time series models are considered for both single and multiple time series. These models are often used for forecasting and inferring the behaviour of times series. Generalised linear models are used in the pricing of insurance such as automobile or home owner insurance. Runoff triangle models are used to predict outstanding insurance liabilities. The use of no claim discount systems as a method of experience rating is also described. A good knowledge of the material covered in STAT271 is essential. Students should understand regression analysis, and the nature and use of a statistical model. Students gaining a grade of credit or higher in both ACST356 and ACST357 are eligible for exemption from subject CT6 of the professional exams of the Institute of Actuaries of Australia.

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.

General Assessment Information

  • 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. 

  • 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. 

  • 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
Class Test 10% Tuesday 7 October 16:00h
Final Examination 70% In the university exam period
Group assignment 20% TBA

Class Test

Due: Tuesday 7 October 16:00h
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.

Final Examination

Due: In the university exam period
Weighting: 70%

Examination under usual exam conditions. Formulae sheet will be provided. 

 
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.

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.

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.

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.

Unit Web Page

To access the website, go to http://ilearn.mq.edu.au and login using your usual login and password.

Teaching and Learning Strategy

  • 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.

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:  

 

 Mock Test

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

Discipline Specific Knowledge and Skills

Our graduates will take with them the intellectual development, depth and breadth of knowledge, scholarly understanding, and specific subject content in their chosen fields to make them competent and confident in their subject or profession. They will be able to demonstrate, where relevant, professional technical competence and meet professional standards. They will be able to articulate the structure of knowledge of their discipline, be able to adapt discipline-specific knowledge to novel situations, and be able to contribute from their discipline to inter-disciplinary solutions to problems.

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

  • Class Test
  • Final Examination
  • Group assignment

Critical, Analytical and Integrative Thinking

We want our graduates to be capable of reasoning, questioning and analysing, and to integrate and synthesise learning and knowledge from a range of sources and environments; to be able to critique constraints, assumptions and limitations; to be able to think independently and systemically in relation to scholarly activity, in the workplace, and in the world. We want them to have a level of scientific and information technology literacy.

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.

Assessment tasks

  • Class Test
  • Final Examination
  • Group assignment

Problem Solving and Research Capability

Our graduates should be capable of researching; of analysing, and interpreting and assessing data and information in various forms; of drawing connections across fields of knowledge; and they should be able to relate their knowledge to complex situations at work or in the world, in order to diagnose and solve problems. We want them to have the confidence to take the initiative in doing so, within an awareness of their own limitations.

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.

Assessment tasks

  • Class Test
  • Final Examination
  • Group assignment

Research and Practice

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.

Changes since First Published

Date Description
05/08/2014 No change