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Estimated value of insurance premium due to Citarum River flood by using Bayesian method

机译:山西河洪水采用贝叶斯方法估计保险费的估计价值

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Citarum river flood in South Bandung, West Java Indonesia, often happens every year. It causes property damage, producing economic loss. The risk of loss can be mitigated by following the flood insurance program. In this paper, we discussed about the estimated value of insurance premiums due to Citarum river flood by Bayesian method. It is assumed that the risk data for flood losses follows the Pareto distribution with the right fat-tail. The estimation of distribution model parameters is done by using Bayesian method. First, parameter estimation is done with assumption that prior comes from Gamma distribution family, while observation data follow Pareto distribution. Second, flood loss data is simulated based on the probability of damage in each flood affected area. The result of the analysis shows that the estimated premium value of insurance based on pure premium principle is as follows: for the loss value of IDR 629.65 million of premium IDR 338.63 million; for a loss of IDR 584.30 million of its premium IDR 314.24 million; and the loss value of IDR 574.53 million of its premium IDR 308.95 million. The premium value estimator can be used as neither a reference in the decision of reasonable premium determination, so as not to incriminate the insured, nor it result in loss of the insurer.
机译:西爪哇印度尼西亚西爪哇省南万兰河洪水经常发生每年。它造成财产损失,产生经济损失。遵循洪水保险计划可以减轻损失风险。在本文中,我们讨论了由于贝叶斯方法雪花河洪水的保险费估计价值。假设洪水损失的风险数据遵循右脂肪尾的帕累托分布。通过使用贝叶斯方法来完成分布模型参数的估计。首先,参数估计是假设先前来自伽玛分布系列的假设,而观察数据遵循帕匹码分布。其次,基于每个洪水影响区域损坏的概率模拟洪水损失数据。分析结果表明,基于纯保费原则的保险估计溢价如下:亏损价值629.65亿溢价为3,3863百万;亏损的IDR 584.30百万美元的溢价为314.24亿;和损益价值为574.53亿美元的保费IDR为30895万。优质值估计器可以在合理的优质决定决定中使用既不参考,以免因被保险人而非指责,也不会导致保险公司损失。

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