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

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<strong>Risk</strong> <strong>Classification</strong> 55<br />

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

7000<br />

6722<br />

.220 .213<br />

6000<br />

.210<br />

.200<br />

.190<br />

.180<br />

.170<br />

5000<br />

.160<br />

.155<br />

4686<br />

.150<br />

.140<br />

.130<br />

4000<br />

.123<br />

.120<br />

.110<br />

.108<br />

3000<br />

.100<br />

.090<br />

2295<br />

.080<br />

.070<br />

2000<br />

.060<br />

1000<br />

0<br />

18–24 25–30 31–60<br />

802<br />

>60<br />

.050<br />

.040<br />

.030<br />

.020<br />

.010<br />

.000<br />

18–24 25–30 31–60 >60<br />

Age<br />

Age<br />

Figure 2.2 Composition <strong>of</strong> Portfolio A with respect to Age (left panel) and observed annual claim<br />

frequencies according to Age (right panel).<br />

Annual claim frequency<br />

Assuming that the numbers <strong>of</strong> claims filed by the policyholders in the portfolio are<br />

independent random variables, the likelihood then becomes<br />

1 2 3 4 =<br />

∝<br />

n∏<br />

i=1<br />

) ki<br />

( )<br />

(d i Agei<br />

exp − d i Agei<br />

k i !<br />

(<br />

4∏<br />

exp − j<br />

j=1<br />

∑<br />

iAgei=j<br />

)<br />

∑<br />

iAgei=j k<br />

d i <br />

i<br />

j<br />

where k i denotes the observed number <strong>of</strong> claims for policyholder i, and ‘∝’ reads ‘is<br />

proportional to’. Differentiating L 1 2 3 4 = ln 1 2 3 4 with respect to j<br />

and setting the derivative equal to 0 gives<br />

−<br />

∑<br />

iAgei=j<br />

d i + 1 j<br />

∑<br />

iAgei=j<br />

k i = 0

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