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The model of life insurance claims with actuarial smoothing approach by using GLM Poisson regression

机译:使用GLM Poisson回归与精算平滑方法的人寿保险索赔模型

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Many statistical models are used in the actuarial calculation process in modeling insurance data, one of which is the Generalized Linear Model (GLM). This study will estimate the actuarial approach of the value of the claims in the multinomial setting with the GLM Poisson Regression model. The data used in this study is the value of life insurance claims with Poisson distribution at West Sumatra Province as many as 1021 data. The best model is selected by comparing the smallest Akaike's Information Criterion (AIC) value, with significant risk factor parameters such as contract, age, month, and benefit. The smoothing approach is due to the best model of GLM Poisson Regression. The average claim value of the best GLM Poisson Regression model is lying in the second category between 20 million until 40 million rupiah. It is mean with the increase of the value of the claims on insurance indicates the high awareness of the public about the importance of insurance.
机译:许多统计模型用于建模保险数据中的精算计算过程中,其中一个是广义线性模型(GLM)。 本研究将估计随着GLM Poisson回归模型的多项式环境中的索赔价值的精算方法。 本研究中使用的数据是West Sumatra省泊松分布的人寿保险索赔的价值,多达1021个数据。 通过比较最小的Akaike的信息标准(AIC)值,具有重大风险因素参数,如合同,年龄,月和福利,选择了最佳模型。 平滑的方法是由于GLM Poisson回归的最佳模型。 最佳GLM Poisson回归模型的平均声明价值在于2000万到4000万卢比的第二类。 它是卑鄙的,随着保险权利要求的价值,表明公众对保险重要性的高意识。

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