In life insurance, it is essential to have adequate mortality rates, be it for reserving or pricing purposes. The course provides the classical tools necessary to create mortality tables from scratch as well as modern machine learning approaches to forecast mortality rates. It also covers the basics of survival analysis.
Learning objective
The course's objective is to provide the students with the understanding and the tools to create mortality tables on their own. Additionally, students should learn the basics of survival analysis.
Content
Following main topics are covered:
- Determining raw mortality rates - Smoothing techniques - Trends in mortality rates - Integration of safety margins - Stochastic mortality model due to Lee and Carter - Neural network extension of the Lee-Carter model - Machine learning for mortality forecasts - Survival analysis
Lecture notes
Lectures notes and slides will be provided
Prerequisites / Notice
The exams ONLY take place during the official ETH examination period.
The course counts towards the diploma of "Aktuar SAV".
Basic knowledge in probability theory is assumed. Some knowledge in financial mathematics is useful.
Competencies
Subject-specific Competencies
Concepts and Theories
assessed
Techniques and Technologies
assessed
Method-specific Competencies
Analytical Competencies
assessed
Problem-solving
assessed
Performance assessment
Performance assessment information (valid until the course unit is held again)