Shengwang Meng, Zizhen Qiu

【Abstract】

Generalized linear models are widely used in non-life insurance ratemaking, but they may produce unreliable parameter estimates when some factors have too many levels (called multi-level factors). One approach to solving this problem is treating a multi-level factor as a random effect: 1) combining generalized linear models and Buhlmann-Straub credibility model; 2) Building generalized linear mixed models for claim frequency and claim data set of vehicle damage insurance from a Chinese property insurance company, the paper shows that the three methods produce the similar results, but GLMM is more advisable.

【Keywords】

non-life insurance, multi-level factor, mixed effect, credibility model, GLMM, ratemaking