Asset-Liability Management with in Life Insurance

Abstract: In recent years, new regulations and stronger competition have further increased the importance of stochastic asset-liability management (ALM) models for life insurance firms. However, the often complex nature of life insurance contracts makes modeling to a challenging task, and insurance firms often struggle with models quickly becoming too complicated and inefficient. There is therefore an interest in investigating if, in fact, certain traits of financial ratios could be exposed through a more efficient model. In this thesis, a discrete time stochastic model framework, for the simulation of simplified balance sheets of life insurance products, is proposed. The model is based on a two-factor stochastic capital market model, supports the most important product characteristics, and incorporates a reserve-dependent bonus declaration. Furthermore, a first approach to endogenously model customer transitions is proposed, where realized policy returns are used for assigning transition probabilities. The model's sensitivity to different input parameters, and ability to capture the most important behaviour patterns, are demonstrated by the use of scenario and sensitivity analyses. Furthermore, based on the findings from these analyses, suggestions for improvements and further research are also presented.