本文選題：未決賠款 + RBNS準(zhǔn)備金��； 參考：《華東師范大學(xué)》2013年碩士論文

【摘要】：本文基于包含索賠信息、進(jìn)展信息、結(jié)案信息等的個(gè)體數(shù)據(jù)研究非壽險(xiǎn)業(yè)務(wù)的RBNS準(zhǔn)備金的預(yù)測(cè)問(wèn)題。以往的未決賠款準(zhǔn)備金預(yù)測(cè)在方法上分為確定性方法、隨機(jī)性方法和比較新的動(dòng)態(tài)性方法,按照這些預(yù)測(cè)方法所使用的數(shù)據(jù)可以分為聚合數(shù)據(jù)模型和個(gè)體數(shù)據(jù)模型,大多方法使用的數(shù)據(jù)基礎(chǔ)是聚合數(shù)據(jù),本文則是基于個(gè)體數(shù)據(jù)在廣義線性模型的基本假設(shè)下對(duì)未決賠款準(zhǔn)備金進(jìn)行有效預(yù)測(cè)。此外本文比較具有創(chuàng)新性的研究了加入個(gè)體結(jié)案信息這一重要因素后的RBNS準(zhǔn)備金預(yù)測(cè)問(wèn)題,利用貝葉斯方法結(jié)合極大似然估計(jì)給出了未決賠款在個(gè)體數(shù)據(jù)下的條件分布,而傳統(tǒng)的鏈梯法及其衍生出的確定性方法得出的是準(zhǔn)備金的低階估計(jì),有的時(shí)候并不能滿足評(píng)估人員的分析需求。 由于加入了個(gè)體的結(jié)案信息,對(duì)于同一事故年或者報(bào)告年的已觀測(cè)個(gè)案,其進(jìn)展年份是不同的,因而以往的確定性方法和隨機(jī)性方法無(wú)法合理有效的進(jìn)行預(yù)測(cè)。對(duì)于已結(jié)案?jìng)�(gè)體從原則上是無(wú)需考慮的,但是任何信息的丟失都有可能使得評(píng)估結(jié)果無(wú)法達(dá)到預(yù)期,本文將已結(jié)案?jìng)�(gè)體數(shù)據(jù)作為參數(shù)估計(jì)的基礎(chǔ),在多元正態(tài)分布假設(shè)下結(jié)合結(jié)案時(shí)間分布及后驗(yàn)均值給出了多元正態(tài)分布情形下RBNS準(zhǔn)備金的預(yù)測(cè)模型,并與傳統(tǒng)鏈梯法模型進(jìn)行比較。本文的預(yù)測(cè)模型在穩(wěn)定性及謹(jǐn)慎性等原則上更為合理有效,綜合比較可得出本文預(yù)測(cè)模型更能滿足評(píng)估人員的分析需求。
[Abstract]:Based on individual data including claim information, progress information and closure information, this paper studies the prediction of RBNS reserve for non-life insurance business. According to the data used in these forecasting methods, they can be divided into aggregate data model and individual data model, which can be divided into deterministic method, randomness method and relatively new dynamic method. Most of the methods are based on aggregate data, and this paper is based on individual data to effectively predict the pending claims reserve under the basic assumptions of the generalized linear model. In addition, this paper studies the problem of RBNS reserve forecasting after adding the important factor of individual closure information, and gives the conditional distribution of pending claims under individual data by using Bayesian method combined with maximum likelihood estimation. However, the traditional chain ladder method and its derived deterministic method can not meet the needs of the evaluators. Because of adding the case information of the individual, the progress years of the observed cases in the same accident year or reporting year are different, so the previous deterministic methods and stochastic methods can not be reasonably and effectively predicted. In principle, there is no need to consider the individual who has completed the case, but any loss of information may make the evaluation result impossible to achieve the expected results. In this paper, the individual data of the case has been used as the basis of parameter estimation. Under the assumption of multivariate normal distribution, the prediction model of RBNS reserve under the condition of multivariate normal distribution combined with the closed time distribution and the posteriori mean is given, and compared with the traditional chain ladder method. The prediction model in this paper is more reasonable and effective in the principles of stability and caution, and it can be concluded that the prediction model in this paper can meet the needs of the evaluators.
【學(xué)位授予單位】：華東師范大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2013
【分類號(hào)】：F224;F840.4

【參考文獻(xiàn)】

相關(guān)期刊論文 前1條

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本文編號(hào)：2087148