數(shù)據(jù)挖掘在我國(guó)保險(xiǎn)業(yè)中的應(yīng)用

1、數(shù)據(jù)挖掘在我國(guó)保險(xiǎn)業(yè)中的應(yīng)用 摘要數(shù)據(jù)挖掘是一項(xiàng)較新的數(shù)據(jù)庫(kù)技術(shù)，它基于大量數(shù)據(jù)所構(gòu)成的數(shù)據(jù)庫(kù)，從中發(fā)現(xiàn)潛在的、有價(jià)值的信息稱為知識(shí)，用于支持決策。數(shù)據(jù)挖掘是一項(xiàng)數(shù)據(jù)庫(kù)應(yīng)用技術(shù)，存在廣泛的實(shí)際應(yīng)用需求，因此，無(wú)論數(shù)據(jù)挖掘的理論研究，還是數(shù)據(jù)挖掘的應(yīng)用實(shí)踐，都是有意義的。本文首先分析了我國(guó)保險(xiǎn)業(yè)中數(shù)據(jù)挖掘技術(shù)應(yīng)用的現(xiàn)狀，介紹數(shù)據(jù)挖掘理論，接著重點(diǎn)研究保險(xiǎn)業(yè)中數(shù)據(jù)挖掘主題的選擇與設(shè)計(jì)上。在國(guó)外已有研究基礎(chǔ)上，結(jié)合我國(guó)保險(xiǎn)業(yè)的實(shí)際需要，提出了我國(guó)保險(xiǎn)業(yè)中的客戶細(xì)分、客戶流失、購(gòu)物籃分析和交叉銷售、客戶滿意度分析、客戶忠誠(chéng)度分析和客戶響應(yīng)度分析六個(gè)挖掘主題。通過(guò)醫(yī)療保險(xiǎn)數(shù)據(jù)的實(shí)證分析，建立醫(yī)療保險(xiǎn)業(yè)的

2、客戶 RC 細(xì)分模型、個(gè)人和團(tuán)體客戶理賠特征模型，利用 SPSS 公司的 Clementine 數(shù)據(jù)挖掘工具建立模型并進(jìn)行驗(yàn)證與評(píng)價(jià)。關(guān)鍵詞：保險(xiǎn)，數(shù)據(jù)挖掘，醫(yī)療保險(xiǎn)，模型AbstractTHE RESEARCH AND APPLICATION OFDATA MINING IN INSURANCEAbstractData Mining is a newer database technique which aims atdiscovering potential and valuable pattern that is called as knowledge.Theknowledge disc

3、overed can be used for decision-making. Data Mining iswidely needed in practical field, therefor; either the theorical research orthe practice of Data Mining is significative.Firstly, we analyze application of data mining technology in domesticinsurance and introduce the theory of data mining techno

4、logy. Secondly, Welay stress on the selection and design of the model of data mining in insuranceindustry. Six data mining pattern of domestic insurance operation are puttedforward: Customer Segmentation, Customer Churn Analysis, Market Basketand Cross-sell Analysis, Customer Satisfaction Analysis,

5、Customer fidelityAnalysis, Customer responsibility Analysis on foreign research and thedomestic practice needs. Medical insurance is given as a demonstration todevelop a customer RC segment model、individual and group claim charactermodel of medical insurance operation and make use of Clementine data

6、mining tools of SPSS, establish the model and then verify and appraise it.Key words: insurance, data mining, medical insurance, model數(shù)據(jù)挖掘技術(shù)在我國(guó)保險(xiǎn)業(yè)中的應(yīng)用研究 III目 錄 第一章 緒論1一、研究的背景和意義1（一）研究的背景1（二）研究的意義2二、國(guó)內(nèi)外應(yīng)用現(xiàn)狀2（一）國(guó)內(nèi)應(yīng)用現(xiàn)狀3（二）國(guó)外應(yīng)用現(xiàn)狀3三、研究的重點(diǎn)、難點(diǎn)及其創(chuàng)新點(diǎn)3四、本文的研究方法和內(nèi)容4第二章 數(shù)據(jù)挖掘理論6一、數(shù)據(jù)挖掘概念6（一）技術(shù)上的定義6（二）商業(yè)上的定義6（三）數(shù)據(jù)挖

7、掘與統(tǒng)計(jì)方法區(qū)別7二、數(shù)據(jù)挖掘分類9（一）描述型數(shù)據(jù)挖掘9（二）預(yù)言型數(shù)據(jù)挖掘 11三、數(shù)據(jù)挖掘算法 12（一）神經(jīng)網(wǎng)絡(luò) 12（二）決策樹 12（三）關(guān)聯(lián)規(guī)則 15（四）聚類算法 15（五）遺傳算法 17（六）粗集方法 17四、數(shù)據(jù)挖掘流程 17（一）目標(biāo)定義 19（二）創(chuàng)建目標(biāo)數(shù)據(jù)集 20數(shù)據(jù)挖掘技術(shù)在我國(guó)保險(xiǎn)業(yè)中的應(yīng)用研究 IV（三）數(shù)據(jù)預(yù)處理 20（四）數(shù)據(jù)轉(zhuǎn)換 21（五）建立數(shù)據(jù)挖掘模型 23（六）評(píng)估與解釋 23（七）采取行動(dòng) 23五、數(shù)據(jù)挖掘的發(fā)展趨勢(shì) 24第三章 保險(xiǎn)業(yè)數(shù)據(jù)挖掘主題的設(shè)計(jì) 27一、客戶細(xì)分 27（一）基于客戶當(dāng)前價(jià)值和潛在價(jià)值的細(xì)分 27（二）基于客戶風(fēng)險(xiǎn)和貢獻(xiàn)的

8、細(xì)分 30二、客戶流失分析 33（一）客戶的流失預(yù)測(cè) 34（二）建立和維持客戶關(guān)系、長(zhǎng)期留住客戶的關(guān)鍵點(diǎn) 35三、購(gòu)物籃分析和交叉銷售 36（一）購(gòu)物籃分析 36（二）交叉銷售分析 36四、客戶忠誠(chéng)度分析 37（一）保險(xiǎn)客戶忠誠(chéng)度分類 37（二）保險(xiǎn)客戶忠誠(chéng)度度量 38五、客戶滿意度分析 41六、客戶響應(yīng)度分析 42第四章 實(shí)證研究 44一、SPSS 公司的 Clementine 工具介紹44（一）性能概述 44（二）產(chǎn)品特點(diǎn) 46二、醫(yī)療保險(xiǎn)數(shù)據(jù)處理流程 48（一）目標(biāo)定義 48（二）創(chuàng)建目標(biāo)數(shù)據(jù)集 48（三）數(shù)據(jù)預(yù)處理 49數(shù)據(jù)挖掘技術(shù)在我國(guó)保險(xiǎn)業(yè)中的應(yīng)用研究 V（四）數(shù)據(jù)轉(zhuǎn)換 49三、團(tuán)

9、體客戶RC細(xì)分模型 51四、團(tuán)體客戶理賠特征分析GR2模型54五、個(gè)人理賠風(fēng)險(xiǎn)特征分析IR2模型57六、采取行動(dòng) 61第五章 結(jié)束語(yǔ)：總結(jié)與展望62致謝 63參考文獻(xiàn) 64附錄一 團(tuán)單客戶細(xì)分模型66附錄二 團(tuán)單客戶理賠風(fēng)險(xiǎn)特征模型69附錄三 個(gè)人客戶理賠風(fēng)險(xiǎn)特征模型72個(gè)人簡(jiǎn)歷 75在學(xué)期間的研究成果及發(fā)表的學(xué)術(shù)論文 75數(shù)據(jù)挖掘技術(shù)在我國(guó)保險(xiǎn)業(yè)中的應(yīng)用研究 VICatalogueChapter 1 Preface.11.1 Background and Meaning of Research11.1.1 Background of Research.11.1.2 Meaning of Re

10、search .21.2 Domestic and Foreign Current Situation of Application.21.2.1 Domestic Current Situation of Application21.2.2 Foreign Current Situation of Application.31.3 Focal point , Difficult Point and Innovation of Research.31.4 Method and Content of Research.4Chapter 2 Theory of Data Mining 52.1 C

11、oncept of Data Mining52.1.1 Concept in the Technology.52.1.2 Concept in the Business.52.1.3 Differentiation of Data Mining and Statistical Method.62.2 Classification of Data Mining.72.2.1 Descriptive Data Dining .82.2.2 Predicative Data Mining92.3 Algorithms of Data Mining .102.3.1 Kohonen Networks.

12、112.3.2 Decision Trees112.3.3 Association Rules.132.3.4 Clustering Algorithms .142.3.5 Genetic Algorithms.152.3.6 Rough Set Theory.162.4 Process of Data Mining.162.4.1 Definition of Target.172.4.2 Construct Data Set of Target18數(shù)據(jù)挖掘技術(shù)在我國(guó)保險(xiǎn)業(yè)中的應(yīng)用研究 VII2.4.3 Handling Data Set182.4.4 Transformation of Da

13、ta192.4.5 Construct Model of Data Mining.202.4.6 Evaluation and Explanation.212.4.7 Deployment212.5 Developing Trends of Data Mining.22Chapter 3 Thematic Design of Data Mining in the Insurance.243.1 Customer Segmentation.243.1.1 Customer Segmentation Based on Current Value andPotential Value243.1.2

14、Customer Segmentation Based on Risk and Contribution273.2 Customer Churn Analysis293.2.1 Predication of Customer Churn.303.2.2 Keypoint of Establishing and Maintaining CustomerRelationship and Retention.313.3 Market Basket and Cross-sell Analysis323.3.1 Market Basket Analysis.323.3.2 Cross-sell Anal

15、ysis.323.4 Customer Fidelity Analysis.333.4.1 Classification of Customer Fidelity in the Insurance.333.4.2 measurement of Customer fidelity in the insurance.343.5 Customer Satisfaction Analysis.373.6 Customer responsibility Analysis.38Chapter 4 Empirical Research404.1 Introduction of Spsss Clementin

16、e Implement.404.1.1 Overview of Performance404.1.2 Characteristic of Product424.2 Process of Handling Data of Medical Insurance434.2.1 Definition of Target.434.2.2 Construct Data Set of Target.44數(shù)據(jù)挖掘技術(shù)在我國(guó)保險(xiǎn)業(yè)中的應(yīng)用研究 VIII4.2.3 Handling Data Set.454.2.4 Transformation of Data.454.3 RC Segmentation Model of Group Customer.464.4 Claim Character Analysis of Group CustomerGR2 Model.504.5 Claim Character Analysis of Group CustomerIR2