Answers to the European Commission on the ... - Eiopa - Europa

those insurers this possible increase in complexity may already be
<strong>the</strong>re when determining <strong>the</strong> valuation of <strong>the</strong>se non-linear instruments
(depending on CfAs 7 and 8).
10.89 A fac<strong>to</strong>r-based approach could be viewed as a practical alternative <strong>to</strong> a
pre-specified stress test. This could follow a 'hybrid approach', where
<strong>the</strong> fac<strong>to</strong>rs are be calibrated by running stress tests (on, for example, a
series of hypo<strong>the</strong>tical insurance undertakings), or by using data from
QIS. For linear risks, <strong>the</strong> resulting fac<strong>to</strong>r-based model would replicate
<strong>the</strong> effects of a pre-specified stress test. For non-linear risks, a fac<strong>to</strong>rbased
model might be seen as a reasonable approximation for a stress
test. The quality of approximation may be increased by adding
additional risk fac<strong>to</strong>rs. For example, convexity captures non-linear
effects in interest rate risk which are not covered by duration.
10.90 Although <strong>the</strong> quality of <strong>the</strong> approximation may be increased by adding
fur<strong>the</strong>r risk fac<strong>to</strong>rs, <strong>the</strong> need for <strong>the</strong> standard formula <strong>to</strong> be easy <strong>to</strong>
implement and verify will place a limit on its complexity. This means
<strong>the</strong>re will be cases where <strong>the</strong> approximation delivered by a fac<strong>to</strong>rbased
model differs significantly from <strong>the</strong> results that would be
generated by stress tests. This may arise where an undertaking has
more material (or substantially different) non-linear effects, due <strong>to</strong>
different features embedded with <strong>the</strong>ir products or investments. In
such circumstances an internal model may give a better reflection of an
undertaking’s individual risk profile than <strong>the</strong> fac<strong>to</strong>r-based model.
Credit risk
10.91 Credit risk is <strong>the</strong> risk of loss of value resulting from default and change
in creditworthiness of issuers of securities within <strong>the</strong> investment
portfolio, counterparties (through, for example, reinsurance or
derivative contracts) and intermediaries <strong>to</strong> whom <strong>the</strong> insurance
undertaking has exposure, and any o<strong>the</strong>r risks normally reflected in
credit spreads. It is <strong>the</strong>refore also <strong>the</strong> loss of value arising from
deterioration in <strong>the</strong> market's perception of counterparty or issuer's
creditworthiness.
10.92 Credit risk may also impact <strong>the</strong> value of technical provisions, for
example in <strong>the</strong> case of with-profits contracts in life insurance.
10.93 Concentration in credit risk may arise through <strong>the</strong> combination of
different business activities. For example, an insurer might hold bonds
of a reinsurer and have a significant reinsurance exposure <strong>to</strong> <strong>the</strong> same
counterparty.
10.94 Within <strong>the</strong> range of possible modelling approaches for credit risk a prespecified
stress test may allow features such as undertaking-specific
reinsurance and hedging effects <strong>to</strong> be taken in<strong>to</strong> account. However, a
pre-specified stress test may increase <strong>the</strong> complexity of calculation.
10.95 A pre-specified stress test can be approximated by a fac<strong>to</strong>r-based
model reflecting <strong>the</strong> linear elements of credit risk. This may be a
reasonable approximation for undertakings with non-material credit
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