Determining Pure Premium of Motor Vehicle Insurance with Generalized Linear Models (GLM)

Tyrenia Rahmawati, Dwi Susanti, Riaman Riaman
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Abstract

Motor vehicle insurance guarantees protection, coverage, and compensation for the risks of accidents, damages, and loss of motor vehicles. It is crucial for companies to determine appropriate insurance premium rates as a preventive measure to avoid difficulties in meeting claims filed by policyholders. This research aims to determine the pure premium of motor vehicle insurance using the Generalized Linear Models (GLM) method, which utilizes the concept of a general linear relationship between independent variables and the dependent/response variable, as well as identifying motor vehicle characteristics that influence the determination of pure premiums. The data used in this study is from Swedish motor vehicle insurance. The research aims to determine the pure premium in the data by modeling claim frequency using the Poisson distribution and claim severity using the Gamma distribution, depending on the significantly influential characteristics. The Maximum Likelihood Estimation method is employed for parameter estimation. After conducting the research, the estimated parameters , , and the pure premium of motor vehicle insurance are found to be 35,572,223.27 kr, with the characteristics influencing the pure premium being the distance traveled by the vehicle, the insured's geographic zone, and the no-claim bonus.
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用广义线性模型(GLM)确定机动车辆保险的纯保费
机动车辆保险为机动车辆的事故、损坏和损失风险提供保障、覆盖和赔偿。作为一项预防措施,公司必须厘定适当的保险费率,以避免投保人索赔时遇到困难。本研究旨在使用广义线性模型(GLM)方法确定机动车辆保险的纯保费,该方法利用了自变量与因变量/响应变量之间的一般线性关系概念,并确定了影响纯保费确定的机动车辆特征。本研究使用的数据来自瑞典机动车辆保险。研究的目的是根据影响较大的特征,利用泊松分布对索赔频率进行建模,利用伽马分布对索赔严重程度进行建模,从而确定数据中的纯保费。参数估计采用最大似然估计法。经过研究发现,估计参数 、 、 和机动车辆保险的纯保费为 35,572,223.27 韩元,其中影响纯保费的特征为车辆行驶距离、被保险人的地理区域和无索赔奖金。
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