Our contribution is threefold. First, we build the first stylized model for re-estimated solvency ratio in insurance. Second, we solve a new theoretical problem in statistical theory: what is the asymptotic impact of a record on the re-estimation of tail quantiles and tail probabilities for classical extreme value estimators? Third, we quantify the impact of the re-estimation of tail quantiles and of loss absorbing capacities on real-world solvency ratios thanks to regulatory data from EIOPA. Our analysis sheds a first light on the role of the loss absorbing capacity and its paramount importance in the Solvency II capital charge computations. We conclude with a number of policy recommendations for insurance regulators.

Updated on the 3rd of January 2025