Signs of dependence and heavy tails in non-life insurance data
Artikel i vetenskaplig tidskrift, 2016

In this paper, we study data from the yearly reports the four major Swedish non-life insurers have sent to the Swedish Financial SupervisoryAuthority (FSA). We aim at finding marginal distributions of, and dependence between, losses on the five largest lines of business (LoBs) in order to create models for solvency capital requirement (SCR) calculation. We try to use data in an optimal way by sensibly defining an accounting year loss in terms of actuarial liability predictions and by pooling observations from several companies when possible to decrease the uncertainty about the underlying distributions and their parameters. We find that dependence between LoBs is weaker in our data than what is assumed in the Solvency II standard formula. We also find dependence between companies that may affect financial stability and must be taken into account when estimating loss distribution parameters. Moreover, we discuss under what circumstances an insurer is better (or worse) off using an internal model for SCR calculation, instead of the standard formula.

dependence modelling

solvency capital requirement

risk aggregation

Författare

Jonas Alm

Göteborgs universitet

Chalmers, Matematiska vetenskaper, Matematisk statistik

Scandinavian Actuarial Journal

0346-1238 (ISSN) 1651-2030 (eISSN)

Vol. 2016 10 859-875

Ämneskategorier

Geofysik

DOI

10.1080/03461238.2015.1017527

Mer information

Senast uppdaterat

2022-04-05