發(fā)布時間：2018-03-08 01:05

  本文選題：欺詐類操作風(fēng)險(xiǎn)　切入點(diǎn)：PSD-LDA　出處：《保險(xiǎn)研究》2017年02期 　論文類型：期刊論文

【摘要】：我國財(cái)險(xiǎn)企業(yè)的操作風(fēng)險(xiǎn)管理起步較晚,目前尚未建立損失事件庫,損失數(shù)據(jù)的缺失導(dǎo)致量化分析的研究較少。通過搜集整理并分析近15年來財(cái)險(xiǎn)企業(yè)的欺詐類操作風(fēng)險(xiǎn)損失事件,發(fā)現(xiàn)數(shù)據(jù)具有"高頻低損"和"低頻高損"的特征,因此采用兩階段損失分布法(PSD-LDA)進(jìn)行擬合。考慮到操作風(fēng)險(xiǎn)事件的屬性以及數(shù)據(jù)搜集的不完整性,運(yùn)用復(fù)合Poisson-Geometric分布來擬合損失頻率從而度量欺詐類操作風(fēng)險(xiǎn)損失,并計(jì)提了相應(yīng)的經(jīng)濟(jì)資本來抵御非預(yù)期的操作風(fēng)險(xiǎn)損失。結(jié)果表明,相對于設(shè)定損失頻率為齊次泊松分布,基于復(fù)合PG分布的PSD-LDA模型能更好的擬合財(cái)險(xiǎn)企業(yè)欺詐類操作風(fēng)險(xiǎn)損失,為我國財(cái)險(xiǎn)企業(yè)操作風(fēng)險(xiǎn)的度量和管理提供了新思路。
[Abstract]:The operational risk management of property insurance enterprises in our country started relatively late. At present, a loss event bank has not yet been established. The lack of loss data leads to less research on quantitative analysis. By collecting and analyzing the fraudulent operational risk loss events of property insurance enterprises in the past 15 years, it is found that the data have the characteristics of "high frequency and low loss" and "low frequency and high loss". Therefore, the two-stage loss distribution method (PSD-LDA) is used to fit the data. Considering the attribute of operational risk events and the incompleteness of data collection, the composite Poisson-Geometric distribution is used to fit the loss frequency to measure the operational risk loss of fraud class. The corresponding economic capital is taken to resist the unexpected operational risk loss. The results show that the loss frequency is homogeneous Poisson distribution relative to the set loss frequency. The PSD-LDA model based on the compound PG distribution can better fit the operational risk loss of the property insurance enterprises, which provides a new idea for the measurement and management of the operational risk of the property insurance enterprises in China.
【作者單位】： 湖南大學(xué)金融與統(tǒng)計(jì)學(xué)院;
【基金】：中國人保財(cái)險(xiǎn)災(zāi)害基金資助
【分類號】：F842.61;D924.35
，

本文編號：1581722