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Bank Branch Network Optimization Based on Customers Geospatial Profiles

机译:基于客户地理空间轮廓的银行分行网络优化

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In this study, the bank branch network optimization problem is considered. The problem consists in choosing several branches for closure based on the overall expected level of dissatisfaction of bank customers with the location of remaining branches. This problem is considered as a black-box optimization problem. We propose a new algorithm for determining dissatisfaction of customers, based on their geospatial profiles. Namely, the following geospatial metrics are used for this purpose: Loyalty and Diversity. Also, a method for comparison of algorithms aimed at solving the mentioned problem is proposed. In this method, data on really dissatisfied customers is employed. Using the method, the proposed algorithm was compared with its competitor on a data set from one of the largest regional banks in Russia. It turned out, that the new algorithm usually shows better accuracy.
机译:在这项研究中,考虑了银行分行网络优化问题。问题在于,根据银行客户对其余分支机构所在地的总体不满意程度,选择关闭多个分支机构。此问题被视为黑盒优化问题。我们提出了一种新的算法,用于根据客户的地理空间分布来确定客户的不满意程度。即,以下地理空间度量用于此目的:忠诚度和多样性。此外,提出了一种用于解决上述问题的算法的比较方法。在这种方法中,使用了真正不满意的客户的数据。使用该方法,将所提出的算法与其竞争对手进行了比较,该数据来自俄罗斯最大的区域性银行之一。事实证明,新算法通常显示出更好的准确性。

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