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

Learning outcome


  • Various methods for claims reserving, their data requirements, their assumptions, their strengths and their weaknesses
  • Uncertainty quantification for some methods
  • Model selection and backtesting


  • A general ability to calcualte and evaluate claims reserves


  • 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.

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.

All aids allowed
Marking scale
7-point grading scale
Censorship form
No external censorship
Several internal examiners

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


Course number
7,5 ECTS
Programme level
Full Degree Master

1 block

Block 1
No limit.
The number of seats may be reduced in the late registration period
Study Board of Mathematics and Computer Science
Contracting department
  • Department of Mathematical Sciences
Contracting faculty
  • Faculty of Science
Course Coordinator
  • Munir Eberhardt Hiabu   (2-706b437064776b316e7831676e)
Saved on the 28-02-2023

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