数据挖掘在J银行个人CRM中的应用研究

发布时间：2018-05-09 20:09

本文选题：数据挖掘 + 个人客户　；参考：《大连理工大学》2012年硕士论文

【摘要】：在当今银行业竞争白热化、经营客户精细化的大环境下,洞悉客户变化、捕捉客户需求、制定经营对策成为各家银行最迫切最重要的工作。因此,如何将数据挖掘这样的新兴技术与国内银行长期积累下来的海量数据有效结合,来改善个人客户关系管理水平成为国内银行客户关系管理研究的焦点。本论文对基于数据挖掘的商业银行个人客户关系管理方面的现状及应用模式进行了探讨,并以J银行为例,就建立基于数据挖掘的客户关系管理模式中涉及的技术、系统、管理、后续跟踪服务等问题进行了分析,并将实际工作情况结合一定的理论研究结果,对面临的问题提出了适当的改进措施和具体实施方法。本论文共分为六章。首先,介绍选题的背景、研究意义、国内外研究现状；第二章,概述数据挖掘的定义、数据挖掘与数据仓库之间的关系和J银行运用的数据挖掘方法,介绍了客户关系管理的基本概念、核心价值观、商业银行客户关系管理项目的分类及构成等内容；第三章,以J银行为例,从数据仓库建设、系统配套、制度环境三个方面介绍了其将数据挖掘运用到个人客户关系管理项目的模型和方案；第四章,以产品响应预测模型为案例,介绍J银行依托数据挖掘提升基金产品销售的具体实施流程；第五章,从业务流程改造、管理变革、数据质量提升等方面提出目前将数据挖掘应用于客户关系管理中存在的问题,并提出了相应的改进措施；第六章,总结全文。本文以J银行为例,从商业银行客户关系管理的实践情况为出发点,阐述了商业银行实施依托数据挖掘具体方法提升客户关系管理的必要性和重要性,通过对产品预测模型应用于产品销售的具体案例分析,对商业银行实施数据挖掘提升产品销售的关键环节进行了探讨。
[Abstract]:In today's banking industry where competition is intense and business customers are refined, it is the most urgent and important work for banks to understand customer changes, capture customer needs, and formulate management strategies. Therefore, how to effectively combine the emerging technology of data mining with the massive data accumulated by domestic banks for a long time to improve the level of personal customer relationship management has become the focus of the research on customer relationship management in domestic banks. This paper discusses the current situation and application mode of personal customer relationship management in commercial banks based on data mining, and takes J Bank as an example to discuss the technology and system involved in the establishment of customer relationship management model based on data mining. This paper analyzes the problems of management and follow-up service, and puts forward the appropriate improvement measures and concrete implementation methods for the problems faced by combining the actual work situation with certain theoretical research results. This thesis is divided into six chapters. Firstly, it introduces the background, significance and current situation of the research at home and abroad. The second chapter summarizes the definition of data mining, the relationship between data mining and data warehouse, and the data mining methods used by J Bank. This paper introduces the basic concept of customer relationship management, the core values, the classification and composition of customer relationship management projects in commercial banks, and the third chapter, taking J Bank as an example, from the data warehouse construction, the system matching, This paper introduces the model and scheme of applying data mining to personal customer relationship management project from three aspects of system environment. Chapter four takes the product response prediction model as an example. This paper introduces the specific implementation process of J Bank to promote fund product sales based on data mining. Chapter five, from the business process transformation, management reform, The problems existing in the application of data mining in customer relationship management are put forward in the aspects of data quality improvement and the corresponding improvement measures are put forward. Chapter 6 summarizes the full text. This paper takes J Bank as an example, from the commercial bank customer relationship management practice as the starting point, elaborated the commercial bank to rely on the data mining concrete method to enhance the customer relationship management the necessity and the importance, Based on the case study of the application of product prediction model to product sales, this paper discusses the key links for commercial banks to implement data mining to promote product sales.
【学位授予单位】：大连理工大学
【学位级别】：硕士
【学位授予年份】：2012
【分类号】：F832.2;F224

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