NMAA06068U Topics in Non-Life Insurance (Skade2)
MSc Programme in Actuarial Mathematics
MSc Programme in Mathematics-Economics
Various distributions that are useful in non-life insurance
The impact of deductibles on the insurance premium calculations
Maximum likelihood methods, including the adjustment for deductibles. Also use of the delta method.
Asymptotic properties of the estimators
Model selection methods
Some linear and generalized linear model theory
Course description: Distributions in insurance, deductibles, maximum likelihood estimation, model choice, non parametric method, linear and generalized linear models.
Understand basic claim number and claim frequency models.
Understand the impact of deductibles, and how to compensate for this in modelling.
Know how to use maximum likelihood to fit insurance data.
Have some insight into the art of picking relevant and useful models for the data.
Know something about the consequences of picking a poor model
A good understanding of linear and generalized linear models, and the difference between continuous and discrete models.
Know how to fit nonstandard models, such as Pareto regression with deductibles.
Be able to take raw data and prepare for statistical analysis.
Be able to fit and select a meaningful model among a variety of alternatives. This includes picking good distributions, good covariates and avoid overfitting.
Run, and if necessary program in R, the necessary calculations.
Be able to go from raw data to practical and useful statistical models. A typical application is in pricing insurance products.
Academic qualifications equivalent to a BSc degree is recommended.
- Theory exercises
- Project work
As an exchange, guest and credit student - click here!
- 7,5 ECTS
- Type of assessment
- Written examination, 3 hours under invigilation
- Exam registration requirements
Two mandatory assignments must be approved and valid before the student is allowed to attend the exam
- All aids allowed
- Marking scale
- 7-point grading scale
- Censorship form
- External censorship
30 minutes oral exam. No preparation time and no aids.
The two mandatory assignments must be approved and valid. If they were not approved during the course the non-approved assignments must be (re)submitted. They have to be approved no later than three weeks before the beginning of the re-exam week.
Criteria for exam assesment
The student should convincingly and accurately demonstrate the knowledge, skills and competences described under Intended learning outcome.
- Course code
- 7,5 ECTS
- Full Degree Master
- 1 block
- Block 4
- Course capacity
- No limit
The number of seats may be reduced in the late registration period
- Study Board of Mathematics and Computer Science
- Department of Mathematical Sciences
- Faculty of Science
- Jostein Paulsen (7-6c717576676b70426f63766a306d7730666d)