Shengwang Meng, Liang Yang

【Abstract】

It’s an important work to predict claim frequency in non-life insure ratemaking. Poisson and negative binomial regression models and the corresponding zero-inflated modes are widely used in prediction of claim frequency. However, when claim data includes zero-inflated characteristics and inter dependency structure, these models can not fit the data well. This paper considers to construct random effect zero-inflated claim frequency regression models under the condition of Poisson distribution, negative binomial distribution, generalized Poisson distribution, and P type negative binomial distribution. In order to improve prediction accuracy, we introduce quadratic smooth item in the models and also build a regression between structural zero probability and rating factors. The models are applied to a set of insurance loss data and the result shows that the goodness-of-fit can be effectively improved.

【Keywords】

random effect, P type negative binomial, zero-inflated, claim frequency