Fast remote but not extreme quantiles with multiple factors. Applications to Solvency II and Enterprise Risk Management

Matthieu Chauvigny (1) , Laurent Devineau (1, 2) , Stéphane Loisel (2) , Véronique Maume-Deschamps (2)

1 R&D Milliman
2 SAF - Laboratoire de Sciences Actuarielle et Financière

For operational purposes, in Enterprise Risk Management or in insurance for example, it may be important to estimate remote (but not extreme) quantiles of some function ƒ of some random vector. The call to ƒ may be time- and resource-consuming so that one aims at reducing as much as possible the number of calls to ƒ. In this paper, we propose some ways to address this problem of general interest. We then numerically analyze the performance of the method on insurance and Enterprise Risk Management real-world case studies.

Domaines: Economies et finances; Probabilités [math.PR]; Statistiques [math.ST]; Théorie [stat.TH]

Matthieu Chauvigny, Laurent Devineau, Stéphane Loisel, Véronique Maume-Deschamps. Fast remote but not extreme quantiles with multiple factors. Applications to Solvency II and Enterprise Risk Management. European Actuarial Journal, 2011, 1 (1), pp.131-157. ⟨hal-00517766v2⟩