【摘要】：隨著經(jīng)濟(jì)全球化的快速發(fā)展，信息化管理成為了銀行提升競(jìng)爭(zhēng)力的一項(xiàng)重要手段，而客戶價(jià)值作為銀行的重要組成部分，必然成為了競(jìng)爭(zhēng)的焦點(diǎn)。由于當(dāng)前的客戶信息軟件開(kāi)發(fā)激烈競(jìng)爭(zhēng)和分析需求多樣化的特點(diǎn)，對(duì)信息的挖掘帶來(lái)了極大的挑戰(zhàn)，尤其是在客戶關(guān)系管理中，其客戶價(jià)值預(yù)測(cè)標(biāo)準(zhǔn)高、需求變化頻繁和限制因素多等客觀條件，使客戶信息挖掘的難度越來(lái)越高。 一種基于客戶價(jià)值指標(biāo)體系與數(shù)據(jù)挖掘方法為解決日益增多的信息資源挖掘帶來(lái)了新的思路，其中模糊數(shù)據(jù)挖掘方法作為最為一種更精準(zhǔn)的挖掘方法以其高度的靈活性得到了極大的關(guān)注。本文基于模糊數(shù)據(jù)挖據(jù)的實(shí)用性對(duì)銀行客戶價(jià)值進(jìn)行分析與設(shè)計(jì)。 首先，研究銀行客戶現(xiàn)有問(wèn)題和特點(diǎn)，分析影響銀行客戶的因素，分析客戶價(jià)值的重要性，客戶價(jià)值指標(biāo)體系相對(duì)于傳統(tǒng)方法需求獲取的優(yōu)勢(shì)。并引入客戶細(xì)分思想，探求客戶價(jià)值。 然后，依據(jù)評(píng)價(jià)指標(biāo)的依據(jù)與原則，引入專家打分法，構(gòu)件客戶價(jià)值指標(biāo)設(shè)計(jì)總體框架。分析體系設(shè)計(jì)步驟，設(shè)計(jì)客戶價(jià)值指標(biāo)體系。 最后，分析模糊數(shù)據(jù)挖掘模式原理與目的，設(shè)計(jì)數(shù)據(jù)挖掘模式總體框架，利用模糊數(shù)據(jù)對(duì)客戶價(jià)值數(shù)據(jù)的分析，，得到實(shí)際劃分的結(jié)果與預(yù)測(cè)。針對(duì)需求進(jìn)行模塊化設(shè)計(jì)，并結(jié)合X銀行客戶信息進(jìn)行實(shí)證研究。
[Abstract]:With the rapid development of economic globalization, information management has become an important means for banks to enhance their competitiveness, and customer value, as an important part of banks, must become the focus of competition. Because of the fierce competition of the current customer information software development and the diversification of the analysis demand, it brings great challenge to the information mining, especially in the customer relationship management, its customer value prediction standard is high. It is more and more difficult to mine customer information because of the objective conditions such as frequent change of demand and many restrictive factors. A new method based on customer value index system and data mining has brought new ideas to solve the increasing number of information resources mining. As the most accurate mining method, fuzzy data mining method has been paid great attention to because of its high flexibility. This paper analyzes and designs the customer value of bank based on the practicability of fuzzy data mining. First of all, we study the existing problems and characteristics of bank customers, analyze the factors that affect bank customers, analyze the importance of customer value, and compare the advantages of customer value index system with traditional methods to obtain requirements. And introduce the idea of customer segmentation, explore customer value. Then, according to the basis and principle of evaluation index, the expert scoring method is introduced to design the overall frame of component customer value index. Analyze system design steps and design customer value index system. Finally, the principle and purpose of fuzzy data mining model are analyzed, the general framework of data mining pattern is designed, and the actual partition result and prediction are obtained by using fuzzy data to analyze customer value data. According to the demand of modular design, combined with X bank customer information for empirical research.
【學(xué)位授予單位】：哈爾濱理工大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2013
【分類號(hào)】：TP311.13;F832.3

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