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Actuarial Modelling of Claim Counts Risk Classification, Credibility ...

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240 <strong>Actuarial</strong> <strong>Modelling</strong> <strong>of</strong> <strong>Claim</strong> <strong>Counts</strong><br />

The total pure premium <strong>of</strong> a policyholder belonging to the reference class is then<br />

E31676 + E4306 = E35982<br />

Note that the fitted mean equal to E 368 018.80 is close to the observed mean <strong>of</strong> the 17 large<br />

losses recorded in Table 5.2.<br />

Recall that the analysis <strong>of</strong> large claims performed in this chapter is based on an estimation<br />

<strong>of</strong> their final cost six months after the end <strong>of</strong> the observation year 1997. We thus work with<br />

incurred losses (payments plus reserves). In practice, the company should maintain a data<br />

base recording the costs <strong>of</strong> large claims that have occurred in the past, corrected for the<br />

different sources <strong>of</strong> inflation (reinsurance companies can <strong>of</strong>ten provide valuable assistance<br />

to the ceding companies in this respect). The typical price for a reinsurance treaty covering<br />

motor third party liability insurance losses in excess <strong>of</strong> E 350 000 represents about 5 % <strong>of</strong><br />

the total motor premium income <strong>of</strong> a Belgian insurance company, so that the expected cost<br />

<strong>of</strong> large claims computed in Portfolio C seems to be <strong>of</strong> the right order <strong>of</strong> magnitude.<br />

Remark 5.5 If the sum <strong>of</strong> the individual pure premiums obtained above exceeds the<br />

observed total loss for the insurance portfolio during the reference period, or if we expect<br />

larger losses in the future (because, e.g., <strong>of</strong> different sources <strong>of</strong> inflation), we can then<br />

keep the same relative premium amounts applied to the anticipated future total claim cost.<br />

This allows us to incorporate in the individual premiums observed trends in the total claim<br />

amount.<br />

5.3 Measures <strong>of</strong> Efficiency for Bonus-Malus Scales<br />

The elasticity <strong>of</strong> a bonus-malus system measures its response to a change in the expected<br />

claim frequency or expected aggregate claim amount. We expect that the premium paid by<br />

the policyholders subject to bonus-malus scales is increasing in the expected claim frequency<br />

or total claim amount. The rate <strong>of</strong> increase is related to the concept <strong>of</strong> efficiency.<br />

5.3.1 Loimaranta Efficiency<br />

Definition<br />

Let us denote as r the average relativity once stationarity has been reached, for a<br />

policyholder with annual expected claim frequency , i.e.<br />

r =<br />

s∑<br />

l r l <br />

l=0<br />

The Loimaranta efficiency Eff Loi is then defined as the elasticity <strong>of</strong> the relative premium<br />

induced by the bonus-malus system, that is,<br />

Eff Loi =<br />

dr<br />

r<br />

d<br />

<br />

=<br />

d ln r<br />

d ln

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