ITM Web Conf.
Volume 36, 2021The 16th IMT-GT International Conference on Mathematics, Statistics and their Applications (ICMSA 2020)
|Number of page(s)||9|
|Section||Statistics and Data Science|
|Published online||26 January 2021|
Prediction region for average claim occurrence rate and average claim size in motor insurance
Department of Mathematical and Actuarial Sciences, Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman, Malaysia
2 School of Mathematical and Computer Sciences, Heriot-Watt University Malaysia
3 Centre for Mathematical Sciences, Universiti Tunku Abdul Rahman, Malaysia
* Corresponding author: email@example.com
The third-party motor insurance data from Sweden for 1977 described by Andrews and Herzberg in 1985 contain average claim occurrence rate (Pc) , average claim size (Ca) for category of vehicles specified by the kilometres travelled per year (K), geographical zone (Z), no claims bonus (B) and make of car (M). The categorical variables Z and M may first be represented respectively by the vectors (Z1, Z2, … , Z6) and (M1, M2, … , M8) of binary variables. The variable (Pc, Ca) is next modelled to be dependent on X∗ = (K, Z1, Z2, … , Z6, B, M1, M2, … , M8) via a conditional distribution which is derived from an 18-dimensional powernormal distribution. From the conditional distribution, a prediction region for (Pc, Ca) can be obtained to provide useful information on the possible ranges of average claim occurrence rate and average claim size for a given category of vehicles.
© The Authors, published by EDP Sciences, 2021
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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