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

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

Cn<br />

1.1<br />

1.0<br />

0.9<br />

0.8<br />

0.7<br />

0.6<br />

0.5<br />

0.4<br />

0.3<br />

0.2<br />

0.1<br />

0.0<br />

0 1 2 3 4 5 6 7 8<br />

Age <strong>of</strong> policy<br />

Figure 8.3 Convergence <strong>of</strong> the transient policyholders’ distributions to the steady state distribution<br />

for the system −1/ + 2.<br />

The corresponding relativies ¯r l are presented in Table 8.15 for a uniform distribution <strong>of</strong><br />

age <strong>of</strong> policy. The last column gives the steady state relativities. We notice that the relativities<br />

are more severe when the initial distribution is closer to the bottom initial distribution.<br />

This seems reasonable since, with the bottom initial distribution, many policyholders are in<br />

the bonus level from the beginning. Therefore, the bonus must be weaker and the maluses<br />

stronger to ensure the financial balance. As for the −1/top bonus-malus scale, the relativities<br />

obtained starting from the bottom initial distribution are the closest to the stationary<br />

relativities.<br />

Influence <strong>of</strong> the Maturity <strong>of</strong> the Portfolio<br />

Let us consider the following three distributions <strong>of</strong> age <strong>of</strong> policy:<br />

Age <strong>of</strong> Mature Young Old<br />

policy portfolio portfolio portfolio<br />

1 125 % 25 % 5 %<br />

2 125 % 20 % 5 %<br />

3 125% 15% 10%<br />

4 125% 10% 10%<br />

5 125% 10% 10%<br />

6 125% 10% 15%<br />

7 125% 5% 20%<br />

8 125% 5% 25%

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