本文選題：廣義線性模型 + 車險(xiǎn)費(fèi)率　； 參考：《天津商業(yè)大學(xué)》2017年碩士論文

【摘要】：當(dāng)前中國的汽車產(chǎn)業(yè)處在一個(gè)高速發(fā)展的階段,中國的汽車銷量已經(jīng)連續(xù)多年位居全球第一。近年來,中國汽車保有量持續(xù)增長,成為僅次于美國的世界第二大汽車保有國[1],預(yù)計(jì)2019年將超越美國成為世界第一大汽車保有國。由于我國汽車產(chǎn)業(yè)和汽車保有量的高速發(fā)展,與之相對(duì)應(yīng)的車險(xiǎn)市場也呈現(xiàn)出快速發(fā)展的態(tài)勢。然而,隨著車聯(lián)網(wǎng)和大數(shù)據(jù)等新技術(shù)的出現(xiàn),新型的車險(xiǎn)費(fèi)率厘定模式在技術(shù)上得到突破,繼而相應(yīng)的創(chuàng)新也得以實(shí)現(xiàn);加之,隨著我國車險(xiǎn)費(fèi)率市場化改革的發(fā)展,我國現(xiàn)有的車險(xiǎn)費(fèi)率厘定模式已難以滿足新形勢的要求,加快實(shí)現(xiàn)車險(xiǎn)費(fèi)率差異化和個(gè)性化己經(jīng)成為車險(xiǎn)市場發(fā)展的必然趨勢[2]。近年來國內(nèi)外保險(xiǎn)公司都在積極推進(jìn)新型的機(jī)動(dòng)車輛保險(xiǎn)產(chǎn)品UBI(Usage-Based Insurance),依據(jù)駕駛行為、行駛里程等分析確定出駕駛行為風(fēng)險(xiǎn)等級(jí),為車險(xiǎn)投保人提供公平合理的車險(xiǎn)費(fèi)率、差異化和個(gè)性化的車險(xiǎn)策略以及車險(xiǎn)增值服務(wù)[3]。本文嘗試采用廣義線性模型對(duì)UBI車險(xiǎn)的風(fēng)險(xiǎn)等級(jí)進(jìn)行確定并且對(duì)駕駛員的駕駛行為進(jìn)行評(píng)分,然后在此基礎(chǔ)上厘定得出最終的車險(xiǎn)費(fèi)率。本文的主要工作內(nèi)容如下:(1)首先對(duì)當(dāng)前已有的費(fèi)率厘定模式及其優(yōu)缺點(diǎn)進(jìn)行說明和分析,并著重分析了傳統(tǒng)費(fèi)率厘定的各種方法所存在的不足。然后介紹了車聯(lián)網(wǎng)技術(shù)和車聯(lián)網(wǎng)理論的發(fā)展情況以及應(yīng)用情況,并介紹了車聯(lián)網(wǎng)保險(xiǎn)UBI的研究現(xiàn)狀和發(fā)展趨勢。在此基礎(chǔ)上著重介紹了駕駛員駕駛行為對(duì)駕駛安全或者風(fēng)險(xiǎn)影響的內(nèi)容和方式。(2)在車聯(lián)網(wǎng)環(huán)境下,在對(duì)駕駛行為對(duì)風(fēng)險(xiǎn)水平的影響進(jìn)行分析的基礎(chǔ)上,采用廣義線性模型,建立了基于駕駛行為數(shù)據(jù)和保單數(shù)據(jù)的風(fēng)險(xiǎn)評(píng)分模型,從而得到每種駕駛行為類型的評(píng)分結(jié)果。以此為基礎(chǔ),將駕駛行為評(píng)分作為新的定價(jià)因子,并與傳統(tǒng)的從人從車定價(jià)因子相結(jié)合,建立廣義線性模型進(jìn)行費(fèi)率厘定,最終得到折扣系數(shù),進(jìn)而計(jì)算得到保費(fèi)。
[Abstract]:At present, China's auto industry is in a stage of rapid development, China's auto sales have been ranked first in the world for many years.In recent years, China's auto ownership has continued to grow, becoming the world's second largest car holder after the United States, and is expected to overtake the United States as the world's largest car holder in 2019.Due to the rapid development of automobile industry and vehicle ownership in China, the corresponding auto insurance market is also showing a rapid development trend.However, with the emergence of new technologies such as car networking and big data, the new model of vehicle insurance rate determination has made a breakthrough in technology, and the corresponding innovation has also been realized; in addition, with the development of market-oriented reform of car insurance rate in China,It is difficult to meet the requirements of the new situation in the existing car insurance rate determination model in our country. Speeding up the realization of the difference and individualization of vehicle insurance rates has become an inevitable trend in the development of the auto insurance market [2].In recent years, insurance companies at home and abroad are actively promoting the new type of motor vehicle insurance product UBI(Usage-Based Insurance, according to driving behavior, driving mileage and other analysis to determine the risk of driving behavior, to provide a fair and reasonable car insurance rate for vehicle insurance policy holders.Differentiated and personalized auto insurance strategy and auto insurance value-added service [3].This paper attempts to use the generalized linear model to determine the risk level of UBI vehicle insurance and to score the driver's driving behavior, and then determine the final vehicle insurance rate on this basis.The main work of this paper is as follows: (1) first of all, this paper explains and analyzes the existing models of rate determination and their advantages and disadvantages, and emphatically analyzes the shortcomings of the traditional methods of rate determination.Then it introduces the development and application of vehicle networking technology and vehicle networking theory, and introduces the research status and development trend of vehicle networking insurance UBI.On this basis, the content and method of driver's driving behavior influence on driving safety or risk are introduced emphatically. In the environment of vehicle network, the influence of driving behavior on risk level is analyzed, and then the generalized linear model is adopted.A risk rating model based on driving behavior data and policy data is established, and the results of each driving behavior type are obtained.On this basis, the driving behavior score is taken as a new pricing factor, and combined with the traditional slave car pricing factor, a generalized linear model is established to determine the rate, and finally the discount coefficient is obtained, and then the premium is calculated.
【學(xué)位授予單位】：天津商業(yè)大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：F842.634

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本文編號(hào)：1759513