數(shù)據(jù)挖掘技術(shù)在保險公司客戶關(guān)系管理中的應用研究
發(fā)布時間：2018-10-17 12:00
【摘要】：研究客戶關(guān)系管理在保險公司中應用，對與保險公司自身競爭力的提升是十分重要的。大量學者用不同的方法、從不同角度研究了客戶關(guān)系管理在保險業(yè)中的應用，但是并沒有形成絕對的共識。值得注意的是前人的研究大多是從定性的角度對客戶關(guān)系管理應用進行分析，而從定量的角度分析還比較少。隨著數(shù)據(jù)挖掘技術(shù)的發(fā)展，，人們逐漸意識到數(shù)據(jù)挖掘技術(shù)應用到保險公司客戶關(guān)系管理的重要性。本文將數(shù)據(jù)挖掘技術(shù)中決策樹算法和傳統(tǒng)的客戶關(guān)系管理相結(jié)合來研究兩者在保險公司中的應用。 本文第1章主要介紹選題背景和意義，國內(nèi)外文獻綜述及論文的結(jié)構(gòu)安排和研究方法。第2章本章是本文的理論基礎，本章論述了客戶關(guān)系管理理論，分析客戶關(guān)系管理應用到保險公司的必要性，并結(jié)合我國實際情況，分析了我國保險公司目前應用客戶關(guān)系管理系統(tǒng)的現(xiàn)狀。第3章為本文的模型構(gòu)建及方法介紹部分，闡述了數(shù)據(jù)挖掘技術(shù)的相關(guān)理論，并對決策樹算法進行了重點闡述，綜合比較了決策樹技術(shù)的幾種算法。根據(jù)第2章及第3章的相關(guān)理論與方法，本文第4章進行了實證分析，首先選取了一個保險公司樣本的大量數(shù)據(jù)，然后按照數(shù)據(jù)挖掘技術(shù)的過程，對數(shù)據(jù)中隱含的信息進行了實證分析，分析結(jié)果顯示保費是影響保險公司客戶流失的最主要因素。過于理想的準確率是由于所選擇數(shù)據(jù)的屬性值較少，但從另一方面也說明了保費的重要性。第5章為政策建議部分，根據(jù)實證分析結(jié)果，提出了一些相對應的政策措施。 本文采用的決策樹算法能夠定量的分析影響企業(yè)客戶流失的因素，定量分析與定性分析相結(jié)合，具有很強的理論及現(xiàn)實意義，本文結(jié)論具有一定參考作用。
[Abstract]:It is very important to study the application of CRM in insurance companies. A large number of scholars have studied the application of CRM in the insurance industry from different angles with different methods, but there is no absolute consensus. It is worth noting that most of the previous studies are qualitative analysis of the application of customer relationship management, but from the point of view of quantitative analysis is relatively small. With the development of data mining technology, people gradually realize the importance of applying data mining technology to customer relationship management of insurance companies. In this paper, the decision tree algorithm in data mining technology and the traditional customer relationship management (CRM) are combined to study their application in insurance companies. The first chapter mainly introduces the background and significance of the topic, literature review at home and abroad, the structure of the paper and research methods. Chapter 2 is the theoretical basis of this paper. This chapter discusses the theory of customer relationship management, analyzes the necessity of the application of customer relationship management to insurance companies, and combines the actual situation of our country. This paper analyzes the current situation of the application of customer relationship management system in Chinese insurance companies. Chapter 3 is the part of model construction and method introduction in this paper. The related theory of data mining technology is expounded, and the algorithm of decision tree is expounded emphatically, and several algorithms of decision tree technology are compared synthetically. According to the relevant theories and methods in Chapter 2 and Chapter 3, the fourth chapter of this paper carries on the empirical analysis, first selects a large number of data of the insurance company sample, then according to the data mining technology process, The results show that the premium is the most important factor affecting the customer turnover of insurance companies. The over-ideal accuracy is due to the fact that the selected data has fewer attribute values, but on the other hand, it also shows the importance of the premium. The fifth chapter is the policy suggestion part, according to the empirical analysis result, has proposed some corresponding policy measures. The decision tree algorithm used in this paper can quantitatively analyze the factors that affect the customer turnover of enterprises. The combination of quantitative analysis and qualitative analysis has a strong theoretical and practical significance. The conclusion of this paper has a certain reference role.
【學位授予單位】：湖南大學
【學位級別】：碩士
【學位授予年份】：2013
【分類號】：TP311.13
[Abstract]:It is very important to study the application of CRM in insurance companies. A large number of scholars have studied the application of CRM in the insurance industry from different angles with different methods, but there is no absolute consensus. It is worth noting that most of the previous studies are qualitative analysis of the application of customer relationship management, but from the point of view of quantitative analysis is relatively small. With the development of data mining technology, people gradually realize the importance of applying data mining technology to customer relationship management of insurance companies. In this paper, the decision tree algorithm in data mining technology and the traditional customer relationship management (CRM) are combined to study their application in insurance companies. The first chapter mainly introduces the background and significance of the topic, literature review at home and abroad, the structure of the paper and research methods. Chapter 2 is the theoretical basis of this paper. This chapter discusses the theory of customer relationship management, analyzes the necessity of the application of customer relationship management to insurance companies, and combines the actual situation of our country. This paper analyzes the current situation of the application of customer relationship management system in Chinese insurance companies. Chapter 3 is the part of model construction and method introduction in this paper. The related theory of data mining technology is expounded, and the algorithm of decision tree is expounded emphatically, and several algorithms of decision tree technology are compared synthetically. According to the relevant theories and methods in Chapter 2 and Chapter 3, the fourth chapter of this paper carries on the empirical analysis, first selects a large number of data of the insurance company sample, then according to the data mining technology process, The results show that the premium is the most important factor affecting the customer turnover of insurance companies. The over-ideal accuracy is due to the fact that the selected data has fewer attribute values, but on the other hand, it also shows the importance of the premium. The fifth chapter is the policy suggestion part, according to the empirical analysis result, has proposed some corresponding policy measures. The decision tree algorithm used in this paper can quantitatively analyze the factors that affect the customer turnover of enterprises. The combination of quantitative analysis and qualitative analysis has a strong theoretical and practical significance. The conclusion of this paper has a certain reference role.
【學位授予單位】：湖南大學
【學位級別】：碩士
【學位授予年份】：2013
【分類號】：TP311.13
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