Advances in Life Insurance Mathematics

Course content

Selection of topics related to modeling, valuation, and pricing in multi-state life insurance and pensions with a strong connection to the research of the present century. Topics may include but are not limited to: cashflows, policyholder behavior, estimation, market consistent valuation, projection and computation of bonus, higher order moments, implementation of procedures in R.


MSc Programme in Actuarial Mathematics

Learning outcome

At the end of the course the student is expected to have:


Knowledge about selected topics related to modeling, valuation, and pricing in the Markov life insurance setup.


Skills to formulate, formalize, and solve theoretical and practical problems related to modeling, valuation, and pricing in the Markov life insurance setup.
Skills to implement procedures related to modeling, valuation, and pricing in the Markov life insurance setup in R.


The course will strengthen the student's competences in navigating inside the Markov life insurance setup and develop the student's ability to formulate and handle new models inside this setup.

5 hours of lectures each week for 7 weeks. In addition to this a total of 2 x 2 hours of exercise classes where the students can work on their mandatory homework sets.

The course literature will primarily consist of research papers from primarily actuarial journals, which will be made available on Absalon.

Stochastic Processes in Life Insurance (LivStok)

Academic qualifications equivalent to a BSc degree is recommended.

The student is also recommended to have prior experience in programming using the language R, e.g. obtained through the bachelor programme in Actuarial Mathematics from the University of Copenhagen.

Continuous feedback during the course of the semester
Feedback by final exam (In addition to the grade)


The students will recieve either oral or written feedback in connection with their two mandatory homework sets.

7,5 ECTS
Type of assessment
Oral examination, 30 minutes
Without preparation.
Without aids
Marking scale
7-point grading scale
Censorship form
No external censorship
Several internal examiners.
Criteria for exam assessment

The student must in a satisfactory way demonstrate that he/she has mastered the learning outcome of the course.

Single subject courses (day)

  • Category
  • Hours
  • Lectures
  • 35
  • Preparation
  • 166
  • Theory exercises
  • 4
  • Exam
  • 1
  • English
  • 206


Course number
7,5 ECTS
Programme level
Full Degree Master

1 block

Block 2
No limit
Study Board of Mathematics and Computer Science
Contracting department
  • Department of Mathematical Sciences
Contracting faculty
  • Faculty of Science
Course Coordinator
  • Jamaal Ahmad   (6-746b776b6b764a776b7e7238757f386e75)
Saved on the 01-03-2021

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