Statistical Techniques in Insurance

Subject ACTL90008 (2015)

Note: This is an archived Handbook entry from 2015.

Credit Points: 12.5
Level: 9 (Graduate/Postgraduate)
Dates & Locations:

This subject has the following teaching availabilities in 2015:

Semester 2, Parkville - Taught on campus.
Pre-teaching Period Start not applicable
Teaching Period 27-Jul-2015 to 25-Oct-2015
Assessment Period End 20-Nov-2015
Last date to Self-Enrol 07-Aug-2015
Census Date 31-Aug-2015
Last date to Withdraw without fail 25-Sep-2015


Timetable can be viewed here. For information about these dates, click here.
Time Commitment: Contact Hours: A 2 hour seminar and a 1 hour workshop per week
Total Time Commitment:

Estimated total time commitment of 120 hours per semester
Prerequisites:
Subject
Study Period Commencement:
Credit Points:
Corequisites:

None
Recommended Background Knowledge:

Students should be competent in the use of Excel.
Non Allowed Subjects:

None
Core Participation Requirements:

For the purposes of considering requests for Reasonable Adjustments under the Disability Standards for Education (Cwth 2005), and Students Experiencing Academic Disadvantage Policy, academic requirements for this subject are articulated in the Subject Description, Subject Objectives, Generic Skills and Assessment Requirements for this entry.

The University is dedicated to provide support to those with special requirements. Further details on the disability support scheme can be found at the Disability Liaison Unit website: http://www.services.unimelb.edu.au/disability/

Coordinator

Dr Enrique Calderin

Contact

Email: enrique.calderin@unimelb.edu.au

Subject Overview:

Topics include experience rating; claim run-off triangles; generalised linear models; time series and their applications; simulation.
Learning Outcomes:

On successful completion of this subject a student should be able to:

  • Describe the fundamental concepts of rating and apply them to simple experience rating systems;
  • Describe and apply techniques for analysing a delay (or run-off) triangle and projecting the ultimate position;
  • Explain the fundamental concepts of a generalised linear model (GLM), and describe how a GLM may apply;
  • Define and apply the main concepts underlying the analysis of time series models;
  • Explain the concepts of “Monte Carlo” simulation using a series of pseudorandom numbers.
Assessment:
  • 1000 word assignment due week 6 (10%);
  • One hour mid-semester test (20%); and
  • Two hour end of semester exam (70%).
Prescribed Texts:

You will be advised of prescribed texts by your lecturer.
Breadth Options:

This subject is not available as a breadth subject.
Fees Information: Subject EFTSL, Level, Discipline & Census Date
Generic Skills:

High level of development:

  • Written communication;
  • Problem solving;
  • Statistical reasoning;
  • Application of theory to practice;
  • Interpretation and analysis;
  • Synthesis of data and other information;
  • Evaluation of data and other information;
  • Use of computer software.
Related Course(s): Graduate Diploma in Actuarial Science
Master of Actuarial Science
Postgraduate Diploma in Actuarial Science

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