  Motivated by insurance applications, we propose a new approach for the
validation of real-world economic scenarios. This approach is based on the
statistical test developed by Chevyrev and Oberhauser (2022) and relies on the
notions of signature and maximum mean distance. This test allows to check
whether two samples of stochastic processes paths come from the same
distribution. Our contribution is to apply this test to a variety of stochastic
processes exhibiting different pathwise properties (H{\"o}lder regularity,
autocorrelation, regime switches) and which are relevant for the modelling of
stock prices and stock volatility as well as of inflation in view of actuarial
applications.
