基于数据挖掘的银行客户分析系统设计与实现

发布时间：2018-07-03 21:46

本文选题：客户关系管理 + 数据挖掘　；参考：《电子科技大学》2013年硕士论文

【摘要】：随着经济全球化、网络化以及金融自由化浪潮的展开,银行间的竞争日趋激烈。各商业银行已经认识到,银行要在竞争中保持优势,必须注重对客户资源的竞争,而要竞争客户资源,必须通过建立客户关系管理系统来获得实时的客户信息,而数据挖掘技术是实施客户关系管理的关键技术之一。通过数据挖掘技术可以过客户信息进行多维度的分析,从大量客户数据中挖掘出隐含的、对银行决策有帮助的知识和规则。这样才能为不同需求的客户提供差别化的金融服务,从而达到保留现有客户、发掘潜在客户并最终提高银行盈利能力的目的。本课题通过对客户关系管理和数据挖掘技术相关理论和方法的介绍,分析银行客户关系管理如何将信息技术与营销战略决策充分结合,开发一套银行客户分析管理软件,通过该软件银行可以实现对客户的自动管理,并寻找出潜在的高端客户,从而提高银行盈利水平,并为银行决策者提供可靠的数据支撑。本课题使用C4.5算法实现客户分析系统的设计和开发以及通过对银行客户分析系统的各个模块的详细论述,展现出一套科学的、完整的实施流程,但鉴于主客观条件的限制,很多方面的探讨还不太深入。根据实际业务需求,本课题开发的系统能够分析客户数据信息和账务信息,进行较为复杂的数据挖掘,作出分析后提供给银行管理人员使用。目前,该系统已投入到实际业务工作中。通过实践,证明该系统设计能有效的发掘目标客户,提高了银行风险防范能力,促进银行业务发展。
[Abstract]:With the development of economic globalization, networking and financial liberalization, the competition between banks is becoming increasingly fierce. Commercial banks have realized that in order to maintain an advantage in competition, banks must pay attention to the competition for customer resources, and to compete for customer resources, they must establish a customer relationship management system to obtain real-time customer information. Data mining technology is one of the key technologies to implement customer relationship management. Through the technology of data mining, we can analyze the customer information in many dimensions, and find out the hidden knowledge and rules from a large number of customer data, which are helpful to the bank decision. Only in this way can the customers with different needs be provided with differential financial services, and the purpose of retaining existing customers, exploring potential customers and ultimately improving the profitability of the bank can be achieved. By introducing the theories and methods of customer relationship management and data mining technology, this paper analyzes how to combine information technology with marketing strategy decision, and develops a set of bank customer analysis management software. Through this software bank can realize the automatic management to the customer and find out the potential high end customer thus raise the bank profit level and provide the reliable data support for the bank decision maker. This subject uses C4.5 algorithm to realize the design and development of customer analysis system, and through the detailed discussion of each module of bank customer analysis system, it shows a set of scientific and complete implementation flow, but in view of the limitation of subjective and objective conditions, Many aspects of the discussion are not very deep. According to the actual business requirements, the system developed in this paper can analyze customer data and account information, carry out more complex data mining, and provide the bank manager with the analysis. At present, the system has been put into actual business work. Through practice, it is proved that the system design can effectively excavate the target customers, improve the ability of bank risk prevention and promote the development of banking business.
【学位授予单位】：电子科技大学
【学位级别】：硕士
【学位授予年份】：2013
【分类号】：TP311.13;TP311.52

【参考文献】