An analysis of mobile banking customers for a bank strategy and policy planning

Behrooz Noori ()
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Behrooz Noori: Department of Industrial Engineering, West Tehran Branch, Islamic Azad University

No 3104516, Proceedings of International Academic Conferences from International Institute of Social and Economic Sciences

Abstract: Online banking is increasingly common. Financial institutions deliver online services via various electronic channels, subsequently diminishing the importance of conventional branch networks. This study proposed an integrated data mining and customer behavior scoring model to manage existing mobile banking users in an Iranian bank. This segmentation model was developed to identify groups of customers based on transaction history, recency, frequency, monetary background. It classified mobile banking users into six groups. This study demonstrated that identifying customers by a behavioral scoring facilitates marketing strategy assignment. Then the bank can develop its marketing actions. Thus, the bank can attract more customers, maintain its customers, and keep high customers' satisfaction.

Keywords: Data mining; mobile data, mobile banking; customer segmentation (search for similar items in EconPapers)
JEL-codes: C52 C54 C88 (search for similar items in EconPapers)
Pages: 12 pages
Date: 2015-11
New Economics Papers: this item is included in nep-mkt
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Published in Proceedings of the Proceedings of the 20th International Academic Conference, Madrid, Nov 2015, pages 307-318

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Persistent link: https://EconPapers.repec.org/RePEc:sek:iacpro:3104516

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