Reserving in Non-Life Insurance
Course content
Introduction of the claims reserving problem.
Topics could include but are not limited to:
- Reserving methods based on a loss triangle. Chainladder and various extensions. Stochastic methods including Mack's model and generalized linear models and other flexible structures. Uncertainty quantification both analytically and via bootstrap.
- Reserving methods based on a loss triangle and additional data.
- Granular claims reserving methods based on marked point processes.
- Machine learning methods for claims reserving.
- Model selection and backtesting.
MSc Programme in Actuarial Mathematics
MSc Programme in Mathematics-Economics
Knowledge:
- Various methods for claims reserving, their data requirements, their assumptions, their strengths and their weaknesses
- Uncertainty quantification for some methods
- Model selection and backtesting
Skills:
- A general ability to calcualte and evaluate claims reserves
Competences:
- Read and reflect on actuarial research papers
- Know how to use R to solve practical problems
4 hours of lectures and 2 hours of exercises per week for 7 weeks.
Lecture notes and research papers, which are made available on Absalon.
Non-life insurance 2 (Skade 2) or similar. A class in regression
is very useful. It is possible to follow the class without these,
but of course it will be more demanding.
Academic qualifications equivalent to a BSc degree is
recommended.
- ECTS
- 7,5 ECTS
- Type of assessment
-
Oral examination
- Type of assessment details
- 30min oral examination with 30min preparation time.
- Exam registration requirements
-
Two mandatory assignments must be approved before the student is allowed attending the exam.
- Aid
- All aids allowed
- Marking scale
- 7-point grading scale
- Censorship form
- No external censorship
Several internal examiners
- Re-exam
-
Same as ordinary exam.
If the two mandatory homework assignments were not approved before the ordinary exam they must be resubmitted. They must be resubmitted no later than four weeks before the beginning of the reexam week.
Criteria for exam assessment
The student should convincingly and accurately demonstrate the knowledge, skills and competences described under Intended learning outcome.
Single subject courses (day)
- Category
- Hours
- Lectures
- 28
- Preparation
- 110
- Project work
- 42
- Exam
- 12
- Exercises
- 14
- English
- 206
Kursusinformation
- Language
- English
- Course number
- NMAK22012U
- ECTS
- 7,5 ECTS
- Programme level
- Full Degree Master
- Duration
-
1 block
- Placement
- Block 1
- Schedulegroup
-
C
- Capacity
- No limit.
The number of seats may be reduced in the late registration period - Studyboard
- Study Board of Mathematics and Computer Science
Contracting department
- Department of Mathematical Sciences
Contracting faculty
- Faculty of Science
Course Coordinator
- Munir Eberhardt Hiabu (2-7c774f7c7083773d7a843d737a)
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Courseinformation of students