本文選題：數(shù)據(jù)挖掘 + 決策樹�。� 參考：《天津大學》2016年碩士論文

【摘要】：隨著國內(nèi)經(jīng)濟體制改革的推進,越來越多的外資銀行加入到中國市場中來,國內(nèi)銀行業(yè)的競爭愈來愈激烈,傳統(tǒng)的以產(chǎn)品為中心的經(jīng)營管理模式逐漸被以客戶為中心的模式所取代。為了提升客戶對銀行服務的滿意度,客戶關(guān)系管理(Client Relation Management,CRM)正被越來越多的銀行企業(yè)所關(guān)注。本文主要選取了某地方銀行的CRM系統(tǒng)作為研究對象。首先明確了該銀行在數(shù)據(jù)分析和處理方面存在的問題和不足,分析了該銀行的客戶現(xiàn)狀,完成了系統(tǒng)整體架構(gòu)的設計,確立了系統(tǒng)的主要功能模塊。然后使用數(shù)據(jù)挖掘技術(shù)中的決策樹算法,從信息技術(shù)和客戶關(guān)系管理相結(jié)合的角度出發(fā),將該銀行的客戶分為高價值客戶、中價值客戶、低價值客戶三類,找出不同類型客戶的行為特征,并依此對不同類別的客戶制定相關(guān)的客戶關(guān)系管理策略。最后完成了系統(tǒng)的部署,測試了客戶識別、個性化推薦等功能,并提供有針對性的差異化個性服務。從測試的結(jié)果可以看出,基于數(shù)據(jù)挖掘技術(shù)的客戶關(guān)系管理系統(tǒng)在客戶價值細分、明確客戶需求方面起到了非常重要的作用,為商業(yè)銀行制定合理決策、提高工作效率、提升服務質(zhì)量、科學分配資源提供了有力的支持。當然,整個系統(tǒng)還有一些有待提升的地方,如數(shù)據(jù)挖掘算法的效率還有待優(yōu)化,系統(tǒng)的數(shù)據(jù)收集的時間過長,采用的數(shù)據(jù)挖掘技術(shù)過于單一等,這些問題都將在以后的升級版本中得到進一步的改進和完善。對銀行的管理層和決策層而言,通過使用這套系統(tǒng),可以降低客戶關(guān)系管理的成本,提高銀行客戶關(guān)系管理的執(zhí)行力;對具體的操作者來說,這樣一套交互界面良好的現(xiàn)代化系統(tǒng)的實施,能夠在短時間內(nèi)獲取到大量與客戶相關(guān)的商業(yè)信息,可以大大提升工作效率,減少工作時間。
[Abstract]:With the development of domestic economic system reform, more and more foreign banks have joined the Chinese market, and the competition of domestic banks is becoming more and more fierce. The traditional product-centered management model is gradually replaced by the customer-centered mode. In order to enhance the customer's satisfaction with the bank service, CRM (customer Relation Management) is being paid more and more attention by the bank enterprises. This paper mainly selects the CRM system of a local bank as the research object. Firstly, the problems and shortcomings of the bank in data analysis and processing are clarified, the customer status of the bank is analyzed, the overall architecture of the system is designed, and the main functional modules of the system are established. Then using the decision tree algorithm in the data mining technology, from the angle of the combination of information technology and customer relationship management, the customers of the bank are divided into three categories: high value customer, middle value customer and low value customer. Identify the behavior characteristics of different types of customers, and develop customer relationship management strategies for different types of customers. Finally, the system is deployed, the functions of customer identification and personalized recommendation are tested, and the differentiated personality service is provided. From the test results, we can see that the customer relationship management system based on data mining technology plays a very important role in customer value segmentation and customer demand determination. Improve the quality of service, scientific allocation of resources to provide a strong support. Of course, there are still some things to be improved in the whole system, such as the efficiency of the data mining algorithm needs to be optimized, the data collection time of the system is too long, the data mining technology is too single, and so on. These issues will be further improved and improved in future updates. For the management and decision makers of the bank, by using this system, the cost of customer relationship management can be reduced and the execution of customer relationship management can be improved. Such a good interactive interface of the implementation of a modern system, in a short time to obtain a large number of customer related business information, can greatly improve work efficiency and reduce working time.
【學位授予單位】：天津大學
【學位級別】：碩士
【學位授予年份】：2016
【分類號】：TP311.52

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