本文選題：數(shù)據(jù)挖掘 + 個人客戶��； 參考：《大連理工大學》2012年碩士論文

【摘要】：在當今銀行業(yè)競爭白熱化、經(jīng)營客戶精細化的大環(huán)境下,洞悉客戶變化、捕捉客戶需求、制定經(jīng)營對策成為各家銀行最迫切最重要的工作。因此,如何將數(shù)據(jù)挖掘這樣的新興技術(shù)與國內(nèi)銀行長期積累下來的海量數(shù)據(jù)有效結(jié)合,來改善個人客戶關(guān)系管理水平成為國內(nèi)銀行客戶關(guān)系管理研究的焦點。 本論文對基于數(shù)據(jù)挖掘的商業(yè)銀行個人客戶關(guān)系管理方面的現(xiàn)狀及應用模式進行了探討,并以J銀行為例,就建立基于數(shù)據(jù)挖掘的客戶關(guān)系管理模式中涉及的技術(shù)、系統(tǒng)、管理、后續(xù)跟蹤服務等問題進行了分析,并將實際工作情況結(jié)合一定的理論研究結(jié)果,對面臨的問題提出了適當?shù)母倪M措施和具體實施方法。 本論文共分為六章。首先,介紹選題的背景、研究意義、國內(nèi)外研究現(xiàn)狀；第二章,概述數(shù)據(jù)挖掘的定義、數(shù)據(jù)挖掘與數(shù)據(jù)倉庫之間的關(guān)系和J銀行運用的數(shù)據(jù)挖掘方法,介紹了客戶關(guān)系管理的基本概念、核心價值觀、商業(yè)銀行客戶關(guān)系管理項目的分類及構(gòu)成等內(nèi)容；第三章,以J銀行為例,從數(shù)據(jù)倉庫建設、系統(tǒng)配套、制度環(huán)境三個方面介紹了其將數(shù)據(jù)挖掘運用到個人客戶關(guān)系管理項目的模型和方案；第四章,以產(chǎn)品響應預測模型為案例,介紹J銀行依托數(shù)據(jù)挖掘提升基金產(chǎn)品銷售的具體實施流程；第五章,從業(yè)務流程改造、管理變革、數(shù)據(jù)質(zhì)量提升等方面提出目前將數(shù)據(jù)挖掘應用于客戶關(guān)系管理中存在的問題,并提出了相應的改進措施；第六章,總結(jié)全文。 本文以J銀行為例,從商業(yè)銀行客戶關(guān)系管理的實踐情況為出發(fā)點,闡述了商業(yè)銀行實施依托數(shù)據(jù)挖掘具體方法提升客戶關(guān)系管理的必要性和重要性,通過對產(chǎn)品預測模型應用于產(chǎn)品銷售的具體案例分析,對商業(yè)銀行實施數(shù)據(jù)挖掘提升產(chǎn)品銷售的關(guān)鍵環(huán)節(jié)進行了探討。
[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.
【學位授予單位】：大連理工大學
【學位級別】：碩士
【學位授予年份】：2012
【分類號】：F832.2;F224

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