The supreme body of the pension fund (board of trustees) is responsible for the overall management of the pension fund. The non-transferable and inalienable duties of the supreme body include the following tasks among others: the setting of the financing system and comprehensibly designing, monitoring, and controlling the asset management to improve the returns and benefits for the members of the pension fund. Since being a member of the board of trustees is not a full-time job, the scope of duties is enormous: meeting the aforementioned legal requirements requires a lot of time and expertise. Pension fund accredited actuaries, investment consultants, auditors as well as pension fund management teams should fully support the board of trustees to make proper decisions.

The reliable forecast of liabilities is very important for the determination of the pension funds' financing system and its control (with risk budgeting). Since many liability parameters depend on the development of yield curves and inflation, it is worthwhile to prepare the analysis of their historical data, visualize them and additionally forecast them reliably.

The aim of this web session is to show how useful the yield curve and inflation forecasting are with the deep learning approach, the visualization of the results and the liability forecast based on them. These approaches are implemented using Python (Anaconda/Jupiter) and R-Project. This type of analysis helps the board of trustees to make their decisions and to better understand the forecast results (compared to affine models). In addition, we will show that such approaches are useful for forecasting international accounting results (IFRS, US GAAP, IPSAS) and for preparing asset allocation to be the strong third contributor.