T. NGUYEN ET AL. 57

However, the Solvency IIves the possi-

bility to apply also the concto capture de-

odel. Tsupervisory aut

mp

a

ers which measure the dependencies

be

ve

us

pean Par-

liament and of the Council on the Taking-Up and Pursuit

ss of Insurance and Reinsurance,” 2009.

nsilium.europa.eu/pdf/en/09/st03/

Valdez, “Understanding Relation-

T of

78, No. 6, 2007, pp.

doi:10.1080/00949650701255834

framework gi

ept of copulas

pendencies in an internal m

ties may even require the co

he

anies to apply an inter-

ho-

ri

nl model for calculating the Solvency Capital Require-

ment, or a part thereof, if it is inappropriate to calculate

the Solvency Capital Requirement using the standard ap-

proach [1]. That means that if the approach for consider-

ing dependencies that is given in the standard model does

not lead to a realistic picture of the actual risk situation

of the company, the supervisory authorities may oblige

the company to use a more sophisticated way for captur-

ing dependencies.

Since the Solvency II framework does not use copulas

in the standard formula for reason of the proportionality

principle, we recommend that Solvency II should at least

reward those insur

tween their risks in a more sophisticated way. This could

be achieved either by reducing the SCR for those insur-

ers or the other way around by imposing higher require-

ments on companies which use the rudimental standard

approach. That would also be justifiable from an econo-

mical point of view: Companies that use linear correlations

may severely underestimate their overall risk and should

therefore be protected by higher capital requirements.

It would also make sense and give additional incen-

tives to explicitly mention the concept of copulas in the

directive and to rework the standard formula once the de-

velopment in multivariate modeling allows the effecti

e of copulas also for smaller insurance companies [20].

Moreover, we have discovered that the given correlations

do not seem to reflect an actual average of the insurance

industry. So, if correlations are used, they should at least

be actually measured in the insurance industry.

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