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Customer Segmentation of Bank Based on Discovering of Their Transactional Relation by Using Data ?Mining Algorithms?

机译:基于数据挖掘算法发现交易关系的银行客户细分

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In this research, based on financial transactions between bank customers which extracted from bank’s databases we have developed the relational transaction graph and customer’s transactional communication network has been created. Furthermore, using data mining algorithms and evaluation parameters in social network concepts lead us for segmenting of bank customers. The main goal in this research is bank customer’s segmentation by discovering the transactional relationship between them in order to deliver some specified solutions in benefit of some policy about customers equality in banking system; in other words improvement of customer relationship management to determination of strategies and business risk management are the main concept of this research. By evaluation of Customer segments, banking system will consider more efficient and crucial factors in decision process to estimate more accurate credential of each group of customers and will grant more appropriate types and amount of loan services to them therefore it is expected these solutions will reduce the risk of loan service in banks.
机译:在这项研究中,基于从银行数据库中提取的银行客户之间的金融交易,我们开发了关系交易图,并创建了客户的交易通信网络。此外,在社交网络概念中使用数据挖掘算法和评估参数使我们能够细分银行客户。这项研究的主要目标是通过发现银行客户之间的交易关系来对其进行细分,以便提供一些特定的解决方案,从而受益于有关银行系统中客户平等的某些政策;换句话说,改进客户关系管理以决定策略和业务风险管理是本研究的主要概念。通过评估客户群,银行系统将在决策过程中考虑更有效和关键的因素,以评估每组客户的更准确的信用凭证,并将向他们提供更适当的类型和数量的贷款服务,因此,预计这些解决方案将减少银行贷款服务的风险。

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