In this research study, we show how existing approaches of using generative adversarial networks (GANs) as economic scenario generators (ESG) can be extended to an entire internal market risk model-with enough risk factors to model the full band-width of investments for an insurance company and for a time horizon of one year, as required in Solvency 2. We demonstrate that the results of a GAN-based internal model are similar to regulatory-approved internal models in Europe. Therefore, GAN-based models can be seen as an alternative data-driven method for market risk modeling.
bonus and dividends; profit and loss attribution; redistribution of surplus; sequential decompositions; With-profit life insurance; Aufsatz in Zeitschrift
Scandinavian actuarial journal Stockholm : Taylor & Francis, 1974 2022(2022), 10, Seite 901-925 Online-Ressource