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Signs of dependence and heavy tails in non-life insurance data

Jonas Alm (Institutionen för matematiska vetenskaper, matematisk statistik)
Scandinavian Actuarial Journal (0346-1238). 10, p. 859-875. (2016)
[Artikel, refereegranskad vetenskaplig]

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.

Nyckelord: risk aggregation, dependence modelling, solvency capital requirement

Denna post skapades 2016-11-25.
CPL Pubid: 245652


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Institutioner (Chalmers)

Institutionen för matematiska vetenskaper, matematisk statistik (2005-2016)



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