商业银行基于CRM系统的数据分析研究
发布时间：2019-05-19 08:25
【摘要】：改革开放之后,我国的经济迅猛发展,市场竞争也越来越激烈。竞争的焦点也不断地在改变,由之前的产品竞争逐渐转变为以客户为中心的服务竞争。而企业和客户的关系是以客户为中心的服务竞争的重点。商业银行作为一个向广大群众提供各种金融服务的服务性行业,客户关系管理对它来说尤为重要。在大数据时代当中,客户信息数据以爆炸性的趋势增长,面对空前巨大的数据量,只有通过更深层次的挖掘才能完全体现其潜在价值。因此,商业银行有必要在客户关系管理系统之上进行大数据分析。通过深层次的挖掘和综合分析这些客户信息,商业银行才能真正了解客户的个性化行为和需求。而不同客户对于银行的价值是不同的,本文的工作就是分析在大数据时代的背景下商业银行的发展道路,以客户信息数据作为数据库,为商业银行建立大数据客户关系管理系统,并主要介绍客户关系管理系统中的客户分类。运用MapReduce聚类大数据处理方法成功将客户进行分类。本人从事的是金融行业,在商业银行负责高端客户的经营管理工作。在不断变化的环境中,客户的需求也在不断的变化:从基础的存贷款、结算业务到现在的财富管理、财富保全、传承规划。如何深入了解客户,发现客户的需求,从而提供个性化的定制化产品和服务;如何运用数据分析,获取目标价值客户实现精准营销,提高管理效率;这些都是值得我们研究和探讨的课题。
[Abstract]:After the reform and opening up, China's economy is developing rapidly, and the market competition is becoming more and more fierce. The focus of competition is also constantly changing, from the previous product competition to customer-centered service competition. The relationship between enterprises and customers is the focus of customer-centered service competition. As a service industry to provide all kinds of financial services to the masses, customer relationship management is particularly important to commercial banks. In big data era, customer information data with explosive trend of growth, in the face of unprecedented huge amount of data, only through deeper mining can fully reflect its potential value. Therefore, it is necessary for commercial banks to carry out big data analysis on the customer relationship management system. Through deep mining and comprehensive analysis of these customer information, commercial banks can really understand the personalized behavior and needs of customers. The value of different customers to the bank is different. The work of this paper is to analyze the development road of commercial banks under the background of big data's era, taking customer information data as the database. Establish big data customer relationship management system for commercial banks, and mainly introduce the customer classification in customer relationship management system. MapReduce clustering big data processing method was used to successfully classify customers. I am engaged in the financial industry, in the commercial bank responsible for the management of high-end customers. In the changing environment, the needs of customers are also constantly changing: from the basic deposit and loan, settlement business to the current wealth management, wealth preservation, inheritance planning. How to deeply understand the customers, discover the needs of the customers, so as to provide personalized customized products and services, how to use data analysis, obtain the target value customers to achieve accurate marketing, improve management efficiency; These are topics worthy of our study and discussion.
【学位授予单位】：江西财经大学
【学位级别】：硕士
【学位授予年份】：2016
【分类号】：TP311.13
本文编号：2480563
[Abstract]:After the reform and opening up, China's economy is developing rapidly, and the market competition is becoming more and more fierce. The focus of competition is also constantly changing, from the previous product competition to customer-centered service competition. The relationship between enterprises and customers is the focus of customer-centered service competition. As a service industry to provide all kinds of financial services to the masses, customer relationship management is particularly important to commercial banks. In big data era, customer information data with explosive trend of growth, in the face of unprecedented huge amount of data, only through deeper mining can fully reflect its potential value. Therefore, it is necessary for commercial banks to carry out big data analysis on the customer relationship management system. Through deep mining and comprehensive analysis of these customer information, commercial banks can really understand the personalized behavior and needs of customers. The value of different customers to the bank is different. The work of this paper is to analyze the development road of commercial banks under the background of big data's era, taking customer information data as the database. Establish big data customer relationship management system for commercial banks, and mainly introduce the customer classification in customer relationship management system. MapReduce clustering big data processing method was used to successfully classify customers. I am engaged in the financial industry, in the commercial bank responsible for the management of high-end customers. In the changing environment, the needs of customers are also constantly changing: from the basic deposit and loan, settlement business to the current wealth management, wealth preservation, inheritance planning. How to deeply understand the customers, discover the needs of the customers, so as to provide personalized customized products and services, how to use data analysis, obtain the target value customers to achieve accurate marketing, improve management efficiency; These are topics worthy of our study and discussion.
【学位授予单位】：江西财经大学
【学位级别】：硕士
【学位授予年份】：2016
【分类号】：TP311.13
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