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基于數(shù)據(jù)挖掘的郵儲(chǔ)銀行卡客戶(hù)細(xì)分研究

發(fā)布時(shí)間:2018-06-28 02:15

  本文選題:銀行卡 + 客戶(hù)細(xì)分; 參考:《浙江工業(yè)大學(xué)》2012年碩士論文


【摘要】:隨著信貸等傳統(tǒng)業(yè)務(wù)的利潤(rùn)空間逐漸萎縮,現(xiàn)代商業(yè)銀行開(kāi)始更加注重發(fā)展中間業(yè)務(wù)。銀行卡業(yè)務(wù)是中間業(yè)務(wù)的重要組成部分,它已成為各個(gè)商業(yè)銀行新的競(jìng)爭(zhēng)焦點(diǎn),使得各銀行均將銀行卡業(yè)務(wù)逐漸向以客戶(hù)、數(shù)據(jù)、信息為中心的經(jīng)營(yíng)和服務(wù)模式轉(zhuǎn)變,而這種模式的基礎(chǔ)即是客戶(hù)細(xì)分。由于數(shù)據(jù)量巨大和數(shù)據(jù)的動(dòng)態(tài)性更強(qiáng),使得傳統(tǒng)的基于經(jīng)驗(yàn)或者統(tǒng)計(jì)學(xué)方法來(lái)細(xì)分客戶(hù)的方法,已經(jīng)遠(yuǎn)遠(yuǎn)不能滿(mǎn)足對(duì)客戶(hù)細(xì)分工作的需要,而開(kāi)始采用更自動(dòng)化和精確的數(shù)據(jù)挖掘方法來(lái)實(shí)現(xiàn)對(duì)卡客戶(hù)的細(xì)分和管理。 本文以溫州市郵政儲(chǔ)蓄銀行卡客戶(hù)細(xì)分工作為背景,針對(duì)該郵儲(chǔ)銀行保存的大量卡用戶(hù)數(shù)據(jù),使用數(shù)據(jù)挖掘技術(shù)來(lái)細(xì)分客戶(hù),以幫助郵儲(chǔ)銀行設(shè)計(jì)相對(duì)有針對(duì)性的卡產(chǎn)品和服務(wù),創(chuàng)建以客戶(hù)為中心的營(yíng)銷(xiāo)策略,增加客戶(hù)滿(mǎn)意度,增大客戶(hù)價(jià)值。 本論文的主要工作是: ①首先簡(jiǎn)要分析了我國(guó)銀行卡業(yè)務(wù)的現(xiàn)狀和存在的問(wèn)題,提出本論文要解決的主要問(wèn)題是對(duì)郵儲(chǔ)銀行的卡客戶(hù)進(jìn)行客戶(hù)細(xì)分研究。 ②簡(jiǎn)單介紹了客戶(hù)細(xì)分的概念和理論,以及國(guó)內(nèi)外商業(yè)銀行在客戶(hù)細(xì)分方面工作現(xiàn)狀,提出我國(guó)商業(yè)銀行大多還是使用傳統(tǒng)的細(xì)分方法,存在不足之處。 ③介紹了數(shù)據(jù)挖掘技術(shù)的概念和常用的基于數(shù)據(jù)挖掘的客戶(hù)細(xì)分技術(shù)。 ④具體闡述了筆者運(yùn)用SAS的數(shù)據(jù)挖掘工具Enterprise Miner,對(duì)溫州市郵儲(chǔ)銀行卡客戶(hù)數(shù)據(jù)進(jìn)行分類(lèi)分析的過(guò)程,并對(duì)分析結(jié)果進(jìn)行簡(jiǎn)單評(píng)價(jià)。 ⑤簡(jiǎn)單總結(jié)了本論文工作的貢獻(xiàn)、局限性和對(duì)未來(lái)的展望。 本文提出使用Entcrprisc Miner運(yùn)用CHAID決策樹(shù)方法對(duì)客戶(hù)信息進(jìn)行分類(lèi)分析,構(gòu)建一個(gè)分類(lèi)模型,分析各個(gè)分類(lèi)群眾客戶(hù)的特征,以實(shí)現(xiàn)根據(jù)未來(lái)新客戶(hù)的基本信息預(yù)測(cè)其可能的客戶(hù)類(lèi)別。通過(guò)這種方法為輔助郵儲(chǔ)銀行經(jīng)營(yíng)決策的制定,提高郵儲(chǔ)銀行的市場(chǎng)競(jìng)爭(zhēng)力,作出了一定的貢獻(xiàn)。
[Abstract]:As the profit space of traditional business such as credit gradually shrinks, modern commercial banks begin to pay more attention to the development of intermediary business. Bank card business is an important part of intermediate business. It has become the new competition focus of each commercial bank, which makes the bank card business gradually change to the customer, data, information as the center of management and service mode. This model is based on customer segmentation. Because of the huge amount of data and the more dynamic nature of the data, the traditional method of customer segmentation based on experience or statistics can not meet the needs of customer segmentation. More automatic and accurate data mining methods are used to realize the segmentation and management of card customers. Based on the customer segmentation work of Wenzhou Postal savings Bank Card, this paper uses data mining technology to segment customers, aiming at a large number of card user data saved by the Postal savings Bank. In order to help Postal savings Bank design relatively targeted card products and services, create a customer-centered marketing strategy, increase customer satisfaction, increase customer value. The main work of this paper is as follows: 1. Firstly, the paper briefly analyzes the present situation and existing problems of bank card business in China. The main problem to be solved in this paper is to study the customer segmentation of card customers of Postal savings Bank. 2 the concept and theory of customer segmentation and the current situation of domestic and foreign commercial banks in customer segmentation are briefly introduced. It is pointed out that most commercial banks in our country still use traditional subdivision methods. This paper introduces the concept of data mining technology and the common customer segmentation technology based on data mining. 4. The author uses SAS data mining tool Enterprise Miner to analyze Wenzhou City. The process of classifying and analyzing customer data of Postal savings Bank Card, The contributions, limitations and future prospects of this paper are briefly summarized. In this paper, Entcrprisc Miner is used to classify and analyze customer information by using the chaid decision tree method, and a classification model is constructed to analyze the characteristics of each classified mass customer, so as to predict the possible customer categories according to the basic information of new customers in the future. This method can help the Postal savings Bank to make operational decisions and improve the market competitiveness of the Postal savings Bank.
【學(xué)位授予單位】:浙江工業(yè)大學(xué)
【學(xué)位級(jí)別】:碩士
【學(xué)位授予年份】:2012
【分類(lèi)號(hào)】:TP311.13;F830.49

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