商业银行信号卡业务潜在客户识别的研究

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摘要

对于国内银行业来说，飞速增长的信用卡业务将成为银行利润的重要来源，信用卡

客户的营销工作也受到了越来越多的重视。由于银行营销工作面对的客户众多，竞争日益

激烈等方面原因，数据挖掘技术越来越多地被应用到信用卡营销领域，并将成为支持银

行信用卡市场分析和提高营销效率的重要工具。而经过十多年的研究，数据挖掘技术已较

为成熟，因此近年来研究的重点转为挖掘技术的应用，商务作为数据挖掘的主要应用领

域，对知识的需求尤为显著。面对巨大的市场压力，竞争状态主要表现为企业间对最有利

客户的激烈争夺上。因此潜在客户识别的研究具有重要的现实意义。

本文采用数据挖掘技术，旨在利用数据挖掘技术对商业银行进行客户挖掘，依据历

史交易数据发现潜在的信用卡客户，并为银行发展信用卡营销指出了方向，本文的研究

背景是招商银行广东分行。本文首先指出目前银行业务所面临的困难，提出本文研究的意

义。然后对国内外潜在客户识别理论进行了详细的研究，并针对银行信用卡业务的特点提

出商业银行潜在客户识别的基本方法，提出全文的研究框架。之后，利用数据挖掘的工具

（SAS）来对已有信用卡客户进行挖掘，找出影响信用卡用户使用信用卡的重要因素，之

后使用层次分析法(AHP)对各个权重权重的计算，计算出影响客户信用卡的各个重要因素

的权重。为了提高客户识别的命中率和效率，运用客户价值评价体系和客户稳定性体系测

量得到客户当前价值、客户潜在价值评价值，建立 2维的客户细分模型。运用该模型对银

行个人客户进行细分，得到 4种类型的客户，然后按照本文的研究目的把细分好的客户进

行筛选，整理出潜在价值客户和有价值客户作为客户识别的数据源。最后，前面分析基础

上，通过对已有信用卡客户的基本属性进行分析后，得出与信用卡相关度最大的因素和

通过对银行客户的识别，得出有获得价值客户和潜在客户的方法，运用数据挖掘的方法，

找到在有价值和潜在价值客户中的进行潜在信用卡客户的挖掘。

关键词：商业银行；信用卡；潜在客户；数据挖掘

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Abstract

For the domestic banking, the sharply increasing credit card service will be a great source

o f b a n k p r o f i t . T h e m a r k e t i n g w o r k t o c r e d i t c a r d c u s t o m e r s a l s o g e t s m o r e a n d m o r e

recognition. As the marketing work face lots of customers, and the competition becomes more

and more drastic, the data mine technology is put to use in credit card marketing field, and will

be an important tool of supporting market analysis and improving marketing efficiency.Data

m i n e t e c h n o l o g y h a s b e e n r e l a t i v e l y m a t u r e a f t e r m o r e t h a n t e n y e a rs ’ r e s e a r c h , s o t h e

a p p l i c a t i o n o f d a t a m i n e b e c o m e s t h e r e s e a r c h s t r e s s , a n d t h e k n o w l e d g e r e q u i r e m e n t o f

b u s i n e s s —t h e m a i n a p p l i c a t i o n f i e l d o f d a t a m i n e , i s e s p e c i a l l y d i s t i n c t . F a c i n g w i t h h u g e

market pressure, the state of competition is mainly in fighting for the advantaged customers, so

the research on recognizing potential customers has an significant real meaning.

The purpose of this thesis is mining potential customers of commercial bank by using data

mine technology indicating direction of developing credit card marketing for banks. The research

background of this paper is China Merchants Bank Guangdong Branch. The paper, at first,

p o i n t s o u t t h e d i ff i c u l t i e s o f b a n k a f f a i r a n d b r i n g s f o r w a r d t h e r e s e a r c h m e a n i n g . S e c o n d , i t

researches the potential customer recognition theory in China, puts forward the basic methods of

recognizing potential customers in commercial banks and the paper’s frame. After that, it mines

c u r r e n t c r e d i t c a r d c u s t o m e r s w i t h S A S , f i n d s o u t t h e f a c t o r s i n f l u e n c i n g

customers’ using credit card. Then it calculates each proportion by using AHP, figures out every

factor’s proportion influencing customers’ using credit card. In order to improve the hit ratio and

e f f i c i e n c y o f c u s t o me r r e c o g n i t i o n, i t b e s t o w s c u s t o me r w o r t h i n e s s v a l u e s y s t e m a n d

customer stability system to get the evaluation of estimate of customer’s current worthiness and

potential worthiness and build up two-dimension customer’s classification model. Then it uses

t h i s m o d e l t o c l a s s i f y p e r s o n a l c u s t o me r s o f b a n k a n d g e t 4 t y p e s o f c u s t o me r s , a f t e r t h a t , i t

f i l t r a t es t h e c l a s s i f i e d c u s t o me r s a n d t i d y u p p o t e n t i a l v a l u a b l e c u s t o m e r a n d v a l u a b l e

customer as customer recognition data source. At last, on the basis of previous analysis, it educes

the factor having the biggest degree of association and methods of finding valuable customers

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广东工业大学管理学硕士学位论文

and potential customers and find out potential credit card customers from them with data mine

methods.

Key words: commercial bank; credit card; potential customers; data mine

目录
目录
摘要..........................................................................................................................................................................I
Abstract.................................................................................................................................................................III
第一章  绪论...........................................................................................................................................................1
1 课题研究背景..........................................................................................................................................1
2 课题的研究意义.....................................................................................................................................2
4 文献综述.................................................................................................................................................3
5 本文研究内容..........................................................................................................................................3
6 全文结构安排..........................................................................................................................................4
第二章 潜在客户识别理论基础...........................................................................................................................6
1 潜在客户基本概念..................................................................................................................................6
1.1 潜在客户的定义..........................................................................................................................6
1.2 客户价值的分类..........................................................................................................................7
2 商业银行客户价值理论..........................................................................................................................8
3 客户价值的管理....................................................................................................................................10
3.1 客户价值管理框架....................................................................................................................10
4 潜在客户识别方法................................................................................................................................12
4.1 基于客户统计学特征的客户识别............................................................................................13
4.2 基于客户交易行为的客户识别................................................................................................14
4.3 基于客户生命周期的客户识别................................................................................................16
4.4 因素组合评价法........................................................................................................................18
4.5 客户生命周期价值评价法........................................................................................................18
4.6 国内客户识别研究....................................................................................................................19
5 商业银行客户潜在客户识别方法........................................................................................................21
5.1 商业银行客户识别....................................................................................................................21
5.2 商业银行潜在客户识别过程....................................................................................................21
6 本章小结................................................................................................................................................22
第三章 信用卡客户的数据挖掘.........................................................................................................................23
1 本章的研究流程....................................................................................................................................23
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  广东工业大学管理学硕士学位论文                  
2 客户资料的收集与预处理方法............................................................................................................23
2.1 客户资料的收集........................................................................................................................23
2.2 资料的预处理方法....................................................................................................................25
3 信用卡客户评分数据选择....................................................................................................................26
3.1 信用卡客户特征变量的选择....................................................................................................27
3.2 构建客户分类所需变量............................................................................................................28
3.3 生成目标变量............................................................................................................................28
4 利用数据挖掘工具进行信用卡数据处理............................................................................................29
4.1 数据挖掘的主要工具介绍........................................................................................................29
4.2 信用卡数据分析........................................................................................................................30
4.3“SEMMA”方法数据挖掘分析过程..........................................................................................39
5 信用卡信用评分表的构建....................................................................................................................41
5.1 指标权重的确定........................................................................................................................41
5.2 层次分析法的步骤....................................................................................................................42
5.3 建立价值评估递阶层次结构....................................................................................................45
5.4 构造两两判别矩阵并计算各因素权重...................................................................................45
6 本章小结................................................................................................................................................49
第四章 商业银行客户价值评价体系的建立.....................................................................................................50
1 客户价值的客户细分概述....................................................................................................................50
2 按客户价值建模....................................................................................................................................51
2.1 客户价值的涵义........................................................................................................................51
2.2 客户当前价值的涵义与计算模型............................................................................................53
2.3 客户当前价值指标的量化........................................................................................................55
2.4 客户潜在价值的涵义与计算模型............................................................................................57
2.5 客户潜在价值的计算模型........................................................................................................58
2.6 指标的无量纲化........................................................................................................................61
3 细分模型的建立与客户细分的实现....................................................................................................61
3.1 数据来源与评价模型的确定....................................................................................................62
3.2 评价指标的量化........................................................................................................................62
3.3 权重的确定................................................................................................................................65
VI

目录
4.3.4 客户价值与潜在价值综合评价结果......................................................................................67
4.3.5 客户细分结果............................................................................................................................68
4.6 本章小结................................................................................................................................................69
第五章 商业银行潜在信用卡客户识别实现.....................................................................................................70
5.1 本章分析方法........................................................................................................................................70
5.2 数据挖掘简介........................................................................................................................................70
5.2.1 数据挖掘过程描述....................................................................................................................70
5.2.2 数据挖掘的功能.......................................................................................................................71
5.2.3 数据挖掘算法-决策树..............................................................................................................72
5.3 按客户价值进行有价值分类................................................................................................................74
5.4 潜在客户识别........................................................................................................................................76
5.4.1 潜在客户识别过程....................................................................................................................76
5.3.4 决策树算法识别........................................................................................................................79
5.4 本章小结................................................................................................................................................82
第六章 结论..........................................................................................................................................................83
参考文献...............................................................................................................................................................84
攻读学位期间发表的学术论文...........................................................................................................................88
独创性声明...........................................................................................................................................................89
致谢.......................................................................................................................................................................90
- VII -

CONTXT

CONTEXT

Chart 1 Introduction......................................................................................................................7

1.1 Research background........................................................................................................7

1.2 Research implication.........................................................................................................8

1.4 Literature summarize........................................................................................................9

1.5 Research contents..............................................................................................................9

1.6 Research framework.......................................................................................................10

Chart2 The theory fundation of latent customer identification....................................................12

2.1 Basic Concept of latent customer...................................................................................12

2.1.1 Define of latent customer..............................................................................12

2.1.2 Classifation of customer value......................................................................13

2.2 Customer value theory of business bank........................................................................14

2.3Management means of customer value............................................................................16

2.3.1 Management sehema of customer value.......................................................16

2.4 Means of latent customer identification..........................................................................18

2.4.1 customer identification based on customer stastics......................................19

2.4.2 customer identification based on customer exchange...................................20

2.4.3 customer identification based on customer life time....................................22

2.4.4 Factor combination appraise.........................................................................24

2.4.5 customer life time appraise...................................................................................24

2.4.6Study of customer identification in home......................................................25

2.5 Means of latent customer identification in business bank..............................................27

2.5.1 customer identification in business bank......................................................27

2 . 5 . 2 S t e p s o f l a t e n t c u s t o m e r i d e n t i f i c a t i o n i n b u s i n e s s

bank................................................................................................................................27

2.6 Conclusion......................................................................................................................28

Chart 3 Creit card customer data mining.....................................................................................29

3.1Study steps in this chart...................................................................................................29

3.2Customer data collection and processing ........................................................................29

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广东工业大学硕士毕业论文

3.2.1 Customer data collection.......................................................................................29

3.2.2 Customer data pre-processing...............................................................................31

3.3Data Collection of Creit card customer data ...................................................................32

3.3.1 Creit card Customer character choose variable....................................................33

3.3.2Building up Customer dividing variable................................................................34

3.3.3Create object variable............................................................................................34

3.4 Using data mining tools to process data.........................................................................35

3.4.1Introduce of data mining tools...............................................................................35

3.4.2 Creit card data analyzing .....................................................................................36

3.4.3Data mining process using “SEMMA”..................................................................45

3.5 Building up of Creit card creit score..............................................................................47

3.5.1Define of Index......................................................................................................47

3.5.2 Steps of AHP.........................................................................................................48

3.5.3Building up of Value estimate hiberarchy.............................................................50

3.5.4 Building up of differentiate natrix and index.......................................................51

3.6 Conclusion......................................................................................................................55

Chart4 Building up of customer value apparise struct in business bank.....................................56

4.1Customer subsection of customer value..........................................................................56

4.2Modeling based on customer value..................................................................................57

4.2.1Meaning of customer value....................................................................................57

4.2.2 Meaning of customer value and calculte model...................................................59

4.2.3Index quantification of customer current value.....................................................60

4.2.4Means of potential value and computer model......................................................62

4.2.5 Customer potential value and computer model....................................................63

4.2.6Index un- quantification.........................................................................................67

4.3Building up of subsection model and customer subsection.............................................67

4.3.1Data source and model decision ...........................................................................67

4.3.2 Appraise index quantification ..............................................................................68

4.3.3weight decision......................................................................................................70

4.3.4 Overall appraise result of Current and potential value.........................................73

- IX -

CONTXT

4.3.5 Customer subsection results..................................................................................74

4.6 Conclusion......................................................................................................................74

Chart 5 Realization of potential credit card customer ................................................................76

5.1Analyzing means..............................................................................................................76

5.2Intruduce of data mine ....................................................................................................76

5.2.1 Porcessor description of DM................................................................................76

5.2.2 Function of DM ....................................................................................................77

5.2.3 DM arithmetic-decision tree ................................................................................78

5.3 Class by customer value..................................................................................................80

5.4 potential customer identify.............................................................................................81

5.4.1Process of potential customer identify...................................................................81

5.3.4 decision tree identify arithmetic............................................................................84

5.4 Conclusion......................................................................................................................87

Chart 6Conclusion.......................................................................................................................88

Reference.....................................................................................................................................89

Article punlished..........................................................................................................................93

Unique Statement ........................................................................................................................94

Thanks..........................................................................................................................................95

第一章绪论

1.1 课题研究背景

信用卡是指由银行、非银行金融机构或专营公司向资信良好的单位、个人签发的可以

在指定的商店或场所进行直接消费，并可在发卡银行及联营机构的营业网点存取款、办理

转账结算的一种信用凭证和支付工具。信用卡是国际上广泛流行的、先进的、新型的支付手

段与信用工具，是产生于经济发达国家和地区的一种新型的消费信贷方式。信用卡于 1915

年起源于美国，随后发展异常迅猛。目前在国际主要有维萨国际组织(VISA International)及

万事达卡国际组织 (MasterCard International) 两大组织及美国运通国际股份有限公司

(America Express )、大来信用证有限公司(Diners Club)， JCB 日本国际信用卡公司(JCB )三

家专业信用卡公司。在各地区还有一些地区性的信用卡组织，如欧洲的EUROPAY、台湾地

区的联合信用卡中心等等。仅以 VISA 国际组织为例，VISA 目前有会员单位约2.2 万个，

发卡逾10 亿张，商户超过2000 多万家，联网 ATM 机约“万台。2001 年，VISA 处理了总

值逾2兆亿美元的交易，仅在亚太区 VISA 的签账额就比 2000 年增长了 44%，达到3100

亿美元。

我国开展信用卡业务比较晚，1986 年中国银行在国内率先成功地推出第一张信用卡，

经过 16 年的发展，我国的信用卡业务也取得了长足的进步。目前国内可以找到的和信用

卡最相关的是银行卡的统计数字。据统计，截至 6月末，全国银行卡发卡总量达到4.38 亿

张，比2001 年年末增长 14%；1月至 6月银行卡交易总额 6.1 万亿元，比去年同期增长

25%；银行卡账户人民币存款余额 5731 亿元，比2001 年年末增长 1211 亿元，增长

26.8%。随着中国银联公司的成立和跨行交易成功率的提高，银行卡跨行交易量得到了较

大幅度的增长。今年1月至 6月共完成跨行交易 2.5 亿笔，清算金额 713 亿元，分别比去年

同期增长 88.6%和74%，其中，通过银行卡总中心完成的异地跨行交易达到473 万笔，清

算金额 6.7 亿元，分别是去年全年交易总和的 1.6 倍和1.9 倍。上半年的各项联网通用任务

基本完成。

当今商业社会正在以不同寻常的速度在改变。垄断业务的解体、业务的多样化和全球

化等特性己在企业间的竞争中急剧增加。对客户本身而言，绝对忠实的客户已经不存在。

客户越了解市场，他们作为个体就越想被承认和理解，希望企业能提供个性化的服务，

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摘要：

摘要摘要对于国内银行业来说，飞速增长的信用卡业务将成为银行利润的重要来源，信用卡客户的营销工作也受到了越来越多的重视。由于银行营销工作面对的客户众多，竞争日益激烈等方面原因，数据挖掘技术越来越多地被应用到信用卡营销领域，并将成为支持银行信用卡市场分析和提高营销效率的重要工具。而经过十多年的研究，数据挖掘技术已较为成熟，因此近年来研究的重点转为挖掘技术的应用，商务作为数据挖掘的主要应用领域，对知识的需求尤为显著。面对巨大的市场压力，竞争状态主要表现为企业间对最有利客户的激烈争夺上。因此潜在客户识别的研究具有重要的现实意义。本文采用数据挖掘技术，旨在利用数据挖掘技术对商业银行进行客户挖掘，依据历史...

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