Models of Life Insurance
- Credits: 8
- Ending: Examination
- Range: 16sP
- Semester: summer
- Faculty of Economic Informatics
Teachers
Included in study programs
Teaching results
The course aim is to provide advanced knowledge in the principles of modeling in life insurance with a special focus on stochastic models of premium and reserves valuation.
The graduate of the course will obtain:
Knowledge and understanding
- to expand knowledge of actuarial techniques used in modeling risks, premiums and reserves of life insurance products,
- to acquire knowledge of mortality patterns used in life insurance.
Skills
- students can solve fundamental problems of modelling mortality by using appropriate software systems,
- students will be able to use a stochastic approach to solving the issue of valuation in life insurance
Competence
- knowledge and skills that can be used in solving practical problems in the insurance practice.
Indicative content
1. Survival models. Mortality models.
2. Classical and stochastic models for product pricing in life insurance.
3. Estimation and valuation of risks in product pricing in life insurance.
4. Stochastic models for determining reserves in life insurance. Modelling of insurer's loss from defined products
Support literature
1. Borowiak, D. S., & Shapiro, A. F. (2003). Financial and actuarial statistics: an introduction. CRC Press.
2. Dickson, D. C. M., Hardy, M. R. & Waters, H. R. (2009). Actuarial Mathematics for Life Contingent Risks. New York: Cambridge University Press.
3. Kleinbaum, D. G. (1996). Survival Analysis: A Self-Learning Text, Springer-Verlag, New York.
4. Macdonald A. S., Richards & S. J., Currie, I. D. (2018). Modelling Mortality with Actuarial Applications. Cambridge University Press.
5. Olivieri, A., Pitacco, E. (2015). Introduction to insurance mathematics: technical and financial features of risk transfers. New York: Springer.
6. Rolski, T., Schmidli, H., Schmidt, V. & Teugels, J. L. (2009). Stochastic processes for insurance and finance (Vol. 505). John Wiley & Sons.
7. Rotar, V. I. (2014). Actuarial models: the mathematics of insurance (2nd ed.). Chapman and Hall/CRC.
8. Šoltésová, T., Šoltés, E. (2013). Embedded value as the value reporting tool of the life insurance companies. In The 7th professor Aleksander Zelias international conference on modeling and forecasting of socio-economic phenomena: proceedings, may 7-10, Zakopane, Poland.
9. Willemse, W. J. (2001). Computational Intelligence: Mortality models for the actuary. Delft. DUP Science.
Syllabus
1. Survival models. Mortality models. 2. Classical and stochastic models for product pricing in life insurance. 3. Estimation and valuation of risks in product pricing in life insurance. 4. Stochastic models for determining reserves in life insurance. Modelling of insurer's loss from defined products
Requirements to complete the course
The participation in consultations - 10%,
The project elaboration - 60%
The project presentation and oral exam - 30%
Student workload
Total study load (in hours):
Participation in lectures - 16
Individual exercises - 42
Project preparation and implementation - 100
Preparation for the final exam - 50
Total load - 208
Language whose command is required to complete the course
slovak
Date of approval: 10.02.2023
Date of the latest change: 15.05.2022