Asset-Liability-Management in Insurance (ALM)


Prof. Dr. Hans-Joachim Zwiesler


Stefan Schelling


4/2 SWS

See LSF for the module description (including ECTS).


First Lecture



Tuesday, 4-6 pm (H12)

Thursday, 2-6 pm (H12)


Monday, 17.07.2017, 10 s.t. in H4/5 (and H8)

Authorized Auxiliaries: Pens, ruler and a non programmable calculator

2nd Exam

Monday, 16.10.2017, 10 s.t. in N24-101


  • The course language will be English.


Exercises and other course material will be provided via Moodle. Register here for the course on Moodle.




Asset-Liability-Management (ALM) describes the management and controlling of liabilities and assets within an insurance company. It is based on techniques from actuarial science and financial mathematics. The course covers the most important methods, which are widely used in practice. These methods become more and more relevant for the risk-management and controlling of insurance companies (e.g. due to the "Solvency II" requirements). The course discusses models, which handle the entire insurance company, as well as models, which focus on single insurance products and the matching of insurance guarantees and the asset allocation.

DAV Exam

Within the lecture it is possible to achieve the certificate of the German actuarial society (DAV) in "Modellierung”. This certificate is a basic requirement for becoming an actuary in Germany.

This certificate can only be achieved in the first exam (typically in July), it is not possible to get the certificate in the second exam (October).


This course is oriented to students enrolled in Mathematics and Management (Wirtschaftsmathematik), Management and Exonomics (Wirtschaftswissenschaften) and Finance with specialization Actuarial Science.

Prerequisites are:

Life-, Health- and Pension-Mathematics, Probability Theory, Basic knowledge in Finance and Risk Theory are desirable, but not necessary.

Basic coding skills are desirable, but not necessary. You can use a coding language of your choice. We will discuss the solutions mostly in MS Excel and VBA. Additionally, we will discuss some solutions in Matlab and R.