Modeling and Estimation for Health and Disability Insurance

Course content

Elements of marked point process theory; parametric modeling and inference for multi-state claims reserving models; implementation of estimation procedures in R; practical issues related to valuation and pricing of health and disability insurance.

Education

MSc Programme in Mathematics-Economics
MSc Programme in Actuarial Mathematics

Learning outcome

Knowledge:

  • Insight into selected aspects of marked point process theory.
  • Insight into the role and limitations of the classic multi-state framework for life insurance.
  • In-depth understanding of theory regarding claims reserving in multi-state models with a focus on health and disability insurance schemes.
  • In-depth understanding of statistical methods for intensity estimation in the presence of delays and contamination.

 

Skills: Ability to

  • Compute claims reserves for health and disability insurance schemes.
  • Estimate parameters of multi-state claims reserving models via for example likelihood methods.
  • Implement the necessary computations in R.

 

Competences: Ability to 

  • Select and interpret appropriate claims reserving models for health and disability insurance schemes.
  • Read and reflect on actuarial research papers.

4 hours of lectures and 2 hours of practical/exercise classes each week for 7 weeks.

Stochastic Processes in Life Insurance and Regression.

Academic qualifications equivalent to a BSc degree is recommended.

Oral
Individual
Collective
Continuous feedback during the course of the semester
ECTS
7,5 ECTS
Type of assessment
Written assignment, 27 hours
Aid
All aids allowed
Marking scale
7-point grading scale
Censorship form
No external censorship
One internal examiner.
Re-exam

The same as the ordinary exam. If 10 or fewer have signed up for the re-exam, then the form of assesment is changed to an oral exam of 30 minutes without preparation and without aids (and multiple internal examiners).  

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
  • 105
  • Exercises
  • 14
  • Exam Preparation
  • 41
  • Exam
  • 18
  • English
  • 206

Kursusinformation

Language
English
Course number
NMAK23011U
ECTS
7,5 ECTS
Programme level
Full Degree Master
Duration

1 block

Placement
Block 3
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
  • Oliver Lunding Sandqvist   (8-726f6c7968753176437064776b316e7831676e)
Saved on the 28-02-2023

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