Historical trends in pension fund membership could be comprehensively analyzed by the administration firm for each pension fund. Formally, administration firms should be able to automatically make such analysis and then visualize it without giving fully historical individual personal data outside. It would help actuaries to accurately assess the pension fund liabilities and create the most accurate liability forecast for ALM studies.

The assumptions for liability forecasting should be discussed with the board of trustees based on analysis and suggestions prepared by actuaries to get the board of trustee’s confirmation. That is why the visualization of assumptions for potential pension fund membership evolution will help to explain them and support the confirmation of board of trustees.

For this workshop several examples how to analyze and provide such assumptions will be prepared and explained. Many useful visualization techniques will be presented with practical examples.

The web session is suited for pension fund actuaries and actuarial professionals, IT-developers of pension fund administration software tools and for administration teams that are directly or indirectly involved in actuarial and investment consulting for pension funds and collective foundations with occupational provisions. Additionally, these topics could be useful for members of pension fund board of trustees, pension fund managers, and pension fund auditors.

Technical Requirements
Please check with your IT department if your firewall and computer settings support web session participation (the programme Zoom will be used for this online training). Please also make sure that you are joining the web session with a stable internet connection.

Liability forecasting depends on different kinds of strategies. In relation to pension fund membership evolution, the HR-Policy has a strong impact: salary, turn-over rates, new hire profiles, restructuring measures, possible range for retirement, etc. The aim of this web session is to provide insights into the approach related to the liability forecasting for ALM studies.

The language of the web session will be English.

Dr. Ljudmila Bertschi
Ljudmila is a qualified member of the Swiss actuarial association (SAV/SAA) and an accredited pension actuary of the Swiss chamber of pension fund experts (SKPE). She has a PhD in phys.-math. from the MSU and has worked in pension fund consulting for about 20 years in different Swiss and international consulting firms and insurance companies. She conducted a research study for the Federal Office of Social Security (2015), prepared many publications and presentations for international conferences as well as made training presentations for Swiss chamber of pension fund experts (liability forecasting with Markov chains incl.).

Dr. Mauro Triulzi
Mauro is a qualified member of the Swiss actuarial association (SAV) and has a Dr. math. ETHZ. He has worked for about 20 years as a developer of actuarial tools and implemented the nested stochastic modelling for pension fund liabilities including mortality rates for ALM studies. Currently he develops different actuarial tools for local and international accounting valuations as well as pension fund administration services. He prepared presentations for international conferences together with Ljudmila.

We both performed EAA online workshop “How Visualization and Computer Science (AI) could support Pension Funds” on Oct 9, 2023.