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Application of data mining techniques in the financial sector for profitable customer relationship management

机译:数据挖掘技术在金融领域的应用,以实现可盈利的客户关系管理

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摘要

The paper presents the benefits of applying data mining (DM) techniques in customer relationship management (CRM) of the financial sectors like banking, forecasting stock market, currency exchange rate and bank bankruptcies. The competition in the financial sector of the business is growing and the firms find it very difficult to sustain the ever-changing behaviour of the customer. To sustain in the competitive world, firms are taking the advantage of the CRM, the new emerging concept in the business world. DM is helping the firms to achieve profitable and efficient CRM by providing them with advance techniques to analyse the already existing data in the databases of the firms using the complex modelling algorithms The paper demonstrates the ability of the data mining to automate the process of searching the mountain of customer's related data to find patterns that are good predictors of the behaviours of the customer which help achieve successful CRM. The paper gives an idea of how data mining capabilities can provide the increased customer retention and minimises the risk involved in the financial sectors to achieve competitive advantage and concludes by providing the limitations and opportunities in this field.
机译:本文介绍了在银行,预测股票市场,货币汇率和银行破产等金融部门的客户关系管理(CRM)中应用数据挖掘(DM)技术的好处。企业金融部门的竞争日益加剧,企业发现很难维持客户不断变化的行为。为了在竞争激烈的世界中持续发展,公司正在利用CRM(商业世界中新兴的概念)的优势。 DM通过使用复杂的建模算法为公司提供先进的技术来分析公司数据库中已经存在的数据,从而帮助他们实现盈利和高效的CRM。本文演示了数据挖掘能够自动搜索企业的能力。大量的客户相关数据,以找到可以很好地预测客户行为的模式,从而有助于成功实现CRM。本文给出了一个想法,即数据挖掘功能如何可以提高客户保留率并最大程度地降低金融部门获得竞争优势所涉及的风险,并通过提供该领域的局限性和机遇来得出结论。

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