Applying a Genetic Algorithm to Determine Premium Rate of Occupational Accident Insurance

Jia-Ching Ying, Chi-Kai Chan, Yen-Ting Chang
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引用次数: 1

Abstract

At present, the Occupational Accident Labor Insurance premium rate is calculated based on the business categories in Taiwan. The premium rate is calculated as a combination of the experience rate and the manual rate for each business category. The traditional actuarial methods are based on many hypotheses to calculate future actual claims and adjust the rate for each business category. Unfortunately, with such adjustments, the risk level of the insured in the business category will be affected. To accurately estimate the size of actual losses for specific industries, we propose a genetic algorithm applied grouping to determine the premium rate for occupational accidents. The proposed approach has been evaluated using the real-world dataset from the Bureau of Labor Insurance in Taiwan that includes occupational accident insurance data from 2009 to 2015. The results demonstrate that the method is practicable at predicting the applicable premium. The proposed method differs from Taiwan's prevailing occupational accident premium rate calculation method. Moreover, it is efficient at selecting the best group of the Standard Industrial Classification from the genetic algorithm. Lastly, the accuracy of the estimates of the total claim amounts are analyzed.
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应用遗传算法确定职业意外保险费率
目前,我国职业意外劳动保险费率是按业务类别计算。保险费率是根据每个业务类别的经验费率和人工费率的组合计算的。传统的精算方法是基于许多假设来计算未来的实际索赔并调整每个业务类别的费率。不幸的是,通过这样的调整,业务类别中的被保险人的风险水平将受到影响。为了准确估计特定行业的实际损失规模,我们提出了一种应用分组的遗传算法来确定职业事故的保险费率。本文使用台湾劳动保险局的真实数据集(包括2009年至2015年的职业意外保险数据)对所提出的方法进行了评估。结果表明,该方法在预测适用溢价方面是可行的。本方法不同于台湾现行的职业意外保险费率计算方法。此外,它还能有效地从遗传算法中选择出标准工业分类的最佳组。最后,对索赔总额估计的准确性进行了分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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