Risk and insurance

MAT15 Risk and insurance

Autumn 2020

  • Topics

    Basic topics in insurance mathematics.

    The probabilistic theoretical basis for life insurance.

    Statistical analysis of life expectancy and mortality.

    Calculation of premium and premium reserve.

  • Learning outcome

    Students can, after completing the course:


    • Understand basic concepts in life insurance mathematics.


    • Master basic concepts in insurance mathematics (preferences and uncertainty, equivalence principle, premium reserves, stochastic dependence, costs, profits and bonuses).
    • Use mortality tables.
    • Use basic methods in life insurance mathematics (pension insurance, life insurance contracts on one and more lives).
    • Make insurance calculations. Interpret and present results achieve. 

    General competence

    • Learn new methods in insurance mathematics that have many applications in actuarial mathematics.

  • Teaching

    Plenary lectures

  • Recommended prerequisites

    MAT10 Analysis and Linear Algebra

  • Required prerequisites

    MET1 Mathematics for Economists

    MET2 Statistics for Economists

  • Requirements for course approval

    Course approval is granted on the basis of one individual written submission. This submission must be accepted in order to get access for the exam.

  • Assessment

    5 hour written school exam

  • Grading Scale

    Grading scale A - F

  • Literature

    Knut K Aase: Anvendt Sannsynlighetsteori: Forsikringsmatematikk (available online)


ECTS Credits
Teaching language

Autumn. Offered Autumn 2020 (first time).

Written school exam is offered both semesters (according to Regulations for Full-time Study Programmes at the Norwegian School of Economics (NHH), section 3-1).

Please note: Due to the present corona situation, please expect parts of this course description to be changed before the autumn semester starts. Particularly, but not exclusively, this relates to teaching methods, mandatory requirements and assessment.

Course responsible

Professor Roman Kozlov, Department of Business and Management Science.