We develop compression methods for large life insurance portfolios, where the insured collective is grouped into cohorts based on selected contract-related criteria. This allows us to simulate an extremely reduced number of representative contracts. We also show how to efficiently integrate new contracts into the existing insurance portfolio. Furthermore, we investigate the efficiency of the compression methods and their quality in approximating the uncompressed life insurance portfolio. For the simulation of the insurance business, we devise a stochastic asset-liability management model. The incorporated balance sheet model is in line with the principle of double-entry bookkeeping as required in accounting. In extensive simulation studies, we illustrate the short- and long-term behavior of our model and show impacts of different compression methods regarding performance and reliability.