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

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<strong>Risk</strong> <strong>Classification</strong> 99<br />

Number <strong>of</strong> policyholders<br />

17000<br />

16000<br />

15000<br />

14000<br />

13000<br />

12000<br />

11000<br />

10000<br />

9000<br />

8000<br />

7000<br />

6000<br />

5000<br />

4000<br />

3000<br />

2000<br />

1000<br />

0<br />

LP LP LP MP MP MP SP SP<br />

18–22 23–30 >30 18–22 23–30 >30 18–22 23–30<br />

Interaction Age–Power<br />

SP<br />

>30<br />

Annual claim frequency<br />

0.36<br />

0.34<br />

0.32<br />

0.30<br />

0.28<br />

0.26<br />

0.24<br />

0.22<br />

0.20<br />

0.18<br />

0.16<br />

0.14<br />

0.12<br />

0.10<br />

0.08<br />

0.06<br />

0.04<br />

0.02<br />

0.00<br />

0.000<br />

LP<br />

18–22<br />

0.253<br />

LP<br />

23–30<br />

0.158<br />

0.341<br />

0.218<br />

0.171<br />

0.302<br />

0.204<br />

LP MP MP MP SP SP<br />

>30 18–22 23–30 >30 18–22 23–30<br />

Interaction Age–Power<br />

0.160<br />

SP<br />

>30<br />

Figure 2.16 Composition <strong>of</strong> Portfolio B with respect to the Age–Power interaction (left panel) and<br />

annual claim frequencies according to the Age–Power interaction (right panel).<br />

Table 2.9 Results <strong>of</strong> the Poisson regression for model with interactions between Age and Power,<br />

Portfolio B.<br />

Variable Level Coeff Std error Wald 95 % conf limit Chi-sq Pr>Chi-sq<br />

Intercept −19248 00312 −19859 −18637 381603 −166022 6143464 −120576 1202437 000 09978<br />

110 kW<br />

Age ∗ Power 17–22<br />

07596 01333 04983 10208 3247 30<br />

00547 00357 −00152 01246 235 01250<br />

66–110 kW<br />

Age ∗ Power > 30 < 66 kW 0 0 0 0 <br />

Size <strong>of</strong> the city Large 02556 00306 01956 03156 6962

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