Abstract
This paper deals with the risks aggregation issue and adequate risk capital modeling within a multivariate setting. Focusing on the non-life insurance risk module, we examine the sensitivity of capital requirement to the dependence among risks for a multi-line Tunisian insurance firm. Such a context entails a nonlinear dependence of risks problem whose resolution may be intended by means of multivariate copulas. The relevant analysis relies profoundly on the dependence modeling by the means of vine copulas which are a flexible technique to model multivariate distributions constructed using a cascade of bivariate copulas. Under various confidence levels in VaR and TailVaR, the reached findings reveal the advantages of D-Vine copula in modeling inhomogeneous structures of dependency due to its flexibility of use in a simulation context. Practitioners and regulators can explore our conclusions for the assessment of risk capital under Solvency 2, which is based on stochastic models.