  In this research, we show how to expand existing approaches of using
generative adversarial networks (GANs) as economic scenario generators (ESG) to
a whole internal market risk model - with enough risk factors to model the full
band-width of investments for an insurance company and for a one year time
horizon 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 a data-driven alternative
way of market risk modeling.
