AKT702 - NON LIFE INSURANCE MATHEMATICS
| Course Name | Code | Semester | Theory (hours/week) |
Application (hours/week) |
Credit | ECTS |
|---|---|---|---|---|---|---|
| NON LIFE INSURANCE MATHEMATICS | AKT702 | 2nd Semester | 3 | 0 | 3 | 10 |
| Prequisites | None | |||||
| Course language | Turkish | |||||
| Course type | Elective | |||||
| Mode of Delivery | Face-to-Face | |||||
| Learning and teaching strategies | Lecture Discussion | |||||
| Instructor (s) | Department Instructors | |||||
| Course objective | Aim of this course is to calculate net risk premium by using claim count and claim size distributions and in addition to that calculating gross premium by using principles of premium calculation and depict effects of risk factors and experience rating related with non-life insurance branches on pricing, and teach the reserve pricing techniques most commonly applied. | |||||
| Learning outcomes |
| |||||
| Course Content | Insurance process; utility theory; claim count distributions; claim size distributions; risk premium; principles of premium calculation; credibility theory; non-life reserving methods; poisson processes; no-claim discount; Bonus-Malus method. | |||||
| References | 1. Straub, E., Non-Life Insurance Mathematics, Association of Swiss Actuaries, Zürih, 1988. 2. Hogg, R.V.,Klugman S.A., Loss Distributions, John Wiley &Sons, 1984. 3. Brown, L.B., Gottlieb, L.R., Introduction to Ratemaking and Loss Reserving for Property and Casualty Insurance, Actex Publications, Connecticut, 1993. 4. Klugman S.,A., Panjer, H.H., Willmot, G .E.,Loss Models: From Data to Decisions, John Wiley and Sons, N.Y, 1998. 5. Tse Yiu-Kuen, Nonlife Actuarial Models: Theory, Methods and Evaluation, Cambridge University Press, Cambridge, 2009. | |||||
Course outline weekly
| Weeks | Topics |
|---|---|
| Week 1 | Insurance process |
| Week 2 | Utility theory |
| Week 3 | Claim count distributions |
| Week 4 | Claim size distributions |
| Week 5 | Risk premium |
| Week 6 | Principles of premium calculation |
| Week 7 | Midterm exam |
| Week 8 | Credibility theory I |
| Week 9 | Credibility theory II |
| Week 10 | Non-life reserving methods I |
| Week 11 | Non-life reserving methods II |
| Week 12 | Poisson processes |
| Week 13 | No-claim discount |
| Week 14 | Bonus-Malus method |
| Week 15 | Preparation for Final Exam |
| Week 16 | Final exam |
Assesment methods
| Course activities | Number | Percentage |
|---|---|---|
| Attendance | 0 | 0 |
| Laboratory | 0 | 0 |
| Application | 0 | 0 |
| Field activities | 0 | 0 |
| Specific practical training | 0 | 0 |
| Assignments | 4 | 10 |
| Presentation | 0 | 0 |
| Project | 4 | 20 |
| Seminar | 0 | 0 |
| Midterms | 1 | 20 |
| Final exam | 1 | 50 |
| Total | 100 | |
| Percentage of semester activities contributing grade succes | 9 | 50 |
| Percentage of final exam contributing grade succes | 1 | 50 |
| Total | 100 | |
WORKLOAD AND ECTS CALCULATION
| Activities | Number | Duration (hour) | Total Work Load |
|---|---|---|---|
| Course Duration (x14) | 14 | 3 | 42 |
| Laboratory | 0 | 0 | 0 |
| Application | 0 | 0 | 0 |
| Specific practical training | 0 | 0 | 0 |
| Field activities | 0 | 0 | 0 |
| Study Hours Out of Class (Preliminary work, reinforcement, ect) | 12 | 4 | 48 |
| Presentation / Seminar Preparation | 0 | 0 | 0 |
| Project | 4 | 25 | 100 |
| Homework assignment | 4 | 10 | 40 |
| Midterms (Study duration) | 1 | 30 | 30 |
| Final Exam (Study duration) | 1 | 40 | 40 |
| Total Workload | 36 | 112 | 300 |
Matrix Of The Course Learning Outcomes Versus Program Outcomes
| D.9. Key Learning Outcomes | Contrubition level* | ||||
|---|---|---|---|---|---|
| 1 | 2 | 3 | 4 | 5 | |
| 1. Develop new strategies and techniques in modelling actuarial problems and produce solutions specific to a problem. | X | ||||
| 2. Conduct detailed research in a specific subject in actuarial science area. | X | ||||
| 3. Have the required level of competency in actuarial sciences to be able to make contribution to the actuarial literature. | X | ||||
| 4. Able to use the knowledge in actuarial sciences in multidisciplinary studies. | X | ||||
| 5. Arrange events and projects in actuarial sciences . Able to conduct the stages of designing, executing and reporting results of a project. | X | ||||
| 6. Have scientific scepticism. | X | ||||
| 7. Able to produce scientific publications in the area of actuarial science. | X | ||||
| 8. Able to think analytically. | X | ||||
| 9. Follow national and international innovations and improvements in the area. | X | ||||
| 10. Follow actuarial literature | X | ||||
| 11. Improve foreign language skills in order to do work and presentation in that language. | X | ||||
| 12. Use information technology in an advanced level. | X | ||||
| 13. Able to work individually and have the ability to decide independently. | X | ||||
| 14. Have the qualifications necessary for a team work and able to be the team leader. | X | ||||
| 15. Have the consciousness of professional and social responsibility. | X | ||||
*1 Lowest, 2 Low, 3 Average, 4 High, 5 Highest