發(fā)布時間：2019-04-03 21:16

【摘要】：未決賠款準備金作為非壽險公司最大的負債項目,其計提水平將直接影響保險公司的盈利能力、償付能力和產(chǎn)品定價。在所有準備金估計方法中,鏈梯法思路明確,方法簡單,是最常用的確定性方法之一,但這種方法對原始數(shù)據(jù)有非常嚴格的假設(shè)條件且無法完成統(tǒng)計檢驗。因此,研究人員考慮在隨機模型的范圍內(nèi)建立準備金估計模型,這其中發(fā)展最為完善的就是廣義線性模型。廣義線性模型因其具有適宜于保險精算的良好特性,為精算學的發(fā)展提供了有力的工具。而以此為基礎(chǔ)的兩階段廣義線性模型通過引入理賠次數(shù)變量,又實現(xiàn)了對廣義線性模型的拓展。 在末決賠款準備金的估計過程中,由于突發(fā)事件、信用欺詐等問題所造成的異常賠款數(shù)據(jù)時有發(fā)生,這些數(shù)據(jù)往往會使準備金的估計結(jié)果產(chǎn)生較大的偏差,并最終影響非壽險公司的運營決策。因此,文章通過對多種常用準備金估計方法的比較,以研究不同模型下異常賠款數(shù)據(jù)對準備金估計結(jié)果的影響程度,并嘗試建立更加合理、穩(wěn)健的準備金估計模型,為保險公司準確計提準備金提供參考。 基于對鏈梯法和的廣義線性模型的改進,本文引入兩種更加穩(wěn)健的模型：穩(wěn)健鏈梯法和穩(wěn)健廣義線性模型,并在兩階段廣義線性模型和穩(wěn)健廣義線性模型的基礎(chǔ)上提出了兩階段穩(wěn)健廣義線性模型。同時,本文對模型的估計結(jié)果利用Bootstrap方法進行了統(tǒng)計檢驗。通過實證分析發(fā)現(xiàn),穩(wěn)健估計方法對原始數(shù)據(jù)中的異常值起到了很好的規(guī)避作用,大大降低了異常值對估計結(jié)果的影響,保險公司將可以得到與原始數(shù)據(jù)中不存在異常值時類似數(shù)量的準備金。并且,通過鏈梯法與穩(wěn)健鏈梯法的比較,可以迅速的定位異常值出現(xiàn)的位置,方便保險公司精算人員據(jù)此探究異常數(shù)據(jù)出現(xiàn)的原因并對原始數(shù)據(jù)做出修正。
[Abstract]:As the largest liability item of non-life insurance companies, the amount of outstanding indemnity reserve will directly affect the profitability, solvency and product pricing of insurance companies. Among all reserve estimation methods, chain ladder method is one of the most commonly used deterministic methods because of its clear train of thought and simple method, but this method has very strict assumptions on the original data and can not complete statistical test. Therefore, researchers consider establishing a reserve estimation model within the scope of stochastic models, among which the most perfect development is the generalized linear model. The generalized linear model provides a powerful tool for the development of actuary because of its good characteristics suitable for actuarial insurance. The two-stage generalized linear model based on this model extends the generalized linear model by introducing the variable of claim number. In the process of estimating the final compensation reserve, the abnormal compensation data caused by unexpected events, credit fraud and other problems often occur, and these data often cause a large deviation in the estimation result of the reserve. And ultimately affect the operation of non-life insurance companies decision-making. Therefore, through the comparison of many common reserve estimation methods, this paper studies the influence degree of abnormal compensation data on reserve estimation results under different models, and tries to establish a more reasonable and robust reserve estimation model. Provide reference for the insurance company to accurately calculate the reserve. Based on the improvement of the generalized linear model of the chain ladder method, this paper introduces two more robust models: the robust chain ladder method and the robust generalized linear model. Based on the two-stage generalized linear model and the robust generalized linear model, a two-stage robust generalized linear model is proposed. At the same time, the Bootstrap method is used to test the estimated results of the model. Through the empirical analysis, it is found that the robust estimation method has a good evading effect on the abnormal values in the original data, and greatly reduces the influence of the outliers on the estimation results. Insurers will be able to obtain reserves similar to those in the original data when there are no exceptions. By comparing the chain ladder method with the robust chain ladder method, the position of the abnormal value can be located quickly, and the actuarial staff of the insurance company can explore the reason of the abnormal data and revise the original data according to the comparison between the chain ladder method and the robust chain ladder method.
【學位授予單位】：天津財經(jīng)大學
【學位級別】：碩士
【學位授予年份】：2013
【分類號】：F840.3;F224

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本文編號：2453589