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

Author:

Shokrgozar Neda,Sobhani Farzad Movahedi

Abstract

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.

Publisher

Canadian Center of Science and Education

Subject

Multidisciplinary

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Diagnosis of Breast Cancer by K-Mean Clustering and Otsu Thresholding Segmentation Methods;Osmaniye Korkut Ata Üniversitesi Fen Bilimleri Enstitüsü Dergisi;2022-03-08

2. Integration K-Means Clustering Method and Elbow Method For Identification of The Best Customer Profile Cluster;IOP Conference Series: Materials Science and Engineering;2018-04

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