Impact of dependence modeling of non-life insurance risks on capital requirement: D-Vine Copula approach

摘要

The purpose of this paper is to provide an extension to recent contributions in the field of quantitative risk management by modeling non-life insurance risks in a multivariate framework. This contribution examines the impact of explicit dependence modeling among non-life insurance losses on capital requirement. First, we focus on the modeling of dependence structure using copulas when the losses from the different business lines are dependent in some sense. Second, we concentrate on Value-at-Risk and Tail-Value-at-Risk as popular risk measures combined with D-Vine copulas model for the total risk capital estimates. For copula calibration, we use claims data from four lines of business of a Tunisian insurance company. Finally, we have conducted a comparative study of different methods under the two hypotheses of dependency and independency. Using Monte-Carlo simulation, our results reveal the advantages of D-Vine copula in modeling inhomogeneous structures of dependency due to its flexibility of use in a simulation context.