Neural Network and Classification Approach in Identifying Customer Behavior in the Banking Sector: a Case Study of an International Bank

dc.contributor.author Ogwueleka, Francisca Nonyelum
dc.contributor.author Misra, Sanjay
dc.contributor.author Colomo-Palacios, Ricardo
dc.contributor.author Fernandez, Luis
dc.contributor.other Computer Engineering
dc.date.accessioned 2024-07-05T14:31:45Z
dc.date.available 2024-07-05T14:31:45Z
dc.date.issued 2015
dc.description Misra, Sanjay/0000-0002-3556-9331; Colomo-Palacios, Ricardo/0000-0002-1555-9726; Fernandez Sanz, Luis/0000-0003-0778-0073 en_US
dc.description.abstract The customer relationship focus for banks is in development of main competencies and strategies of building strong profitable customer relationships through considering and managing the customer impression, influence on the culture of the bank, satisfactory treatment, and assessment of valued relationship building. Artificial neural networks (ANNs) are used after data segmentation and classification, where the designed model register records into two class sets, that is, the training and testing sets. ANN predicts new customer behavior from previously observed customer behavior after executing the process of learning from existing data. This article proposes an ANN model, which is developed using a six-step procedure. The back-propagation algorithm is used to train the ANN by adjusting its weights to minimize the difference between the current ANN output and the desired output. An evaluation process is conducted to determine whether the ANN has learned how to perform. The training process is halted periodically, and its performance is tested until an acceptable result is obtained. The principles underlying detection software are grounded in classical statistical decision theory. en_US
dc.identifier.doi 10.1002/hfm.20398
dc.identifier.issn 1090-8471
dc.identifier.issn 1520-6564
dc.identifier.scopus 2-s2.0-84916223113
dc.identifier.uri https://doi.org/10.1002/hfm.20398
dc.identifier.uri https://hdl.handle.net/20.500.14411/730
dc.language.iso en en_US
dc.publisher Wiley en_US
dc.rights info:eu-repo/semantics/closedAccess en_US
dc.subject Customer relationship management (CRM) en_US
dc.subject Artificial neural network (ANN) en_US
dc.subject Classification en_US
dc.subject Banks en_US
dc.subject Back-propagation algorithm en_US
dc.title Neural Network and Classification Approach in Identifying Customer Behavior in the Banking Sector: a Case Study of an International Bank en_US
dc.type Article en_US
dspace.entity.type Publication
gdc.author.id Misra, Sanjay/0000-0002-3556-9331
gdc.author.id Colomo-Palacios, Ricardo/0000-0002-1555-9726
gdc.author.id Fernandez Sanz, Luis/0000-0003-0778-0073
gdc.author.institutional Mısra, Sanjay
gdc.author.scopusid 35264573100
gdc.author.scopusid 56962766700
gdc.author.scopusid 25653963200
gdc.author.scopusid 25630384100
gdc.author.wosid Misra, Sanjay/K-2203-2014
gdc.author.wosid Colomo-Palacios, Ricardo/E-5139-2010
gdc.coar.access metadata only access
gdc.coar.type text::journal::journal article
gdc.description.department Atılım University en_US
gdc.description.departmenttemp [Ogwueleka, Francisca Nonyelum] Fed Univ Technol, Dept Comp Sci, Minna, Niger State, Nigeria; [Misra, Sanjay] Atilim Univ, Dept Comp Engn, Ankara, Turkey; [Colomo-Palacios, Ricardo] Univ Carlos III Madrid, E-28903 Getafe, Spain; [Fernandez, Luis] Univ Alcala de Henares, Dept Ciencias Comp, Alcala De Henares 28400, Spain en_US
gdc.description.endpage 42 en_US
gdc.description.issue 1 en_US
gdc.description.publicationcategory Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı en_US
gdc.description.scopusquality Q2
gdc.description.startpage 28 en_US
gdc.description.volume 25 en_US
gdc.identifier.wos WOS:000346034900003
gdc.scopus.citedcount 45
gdc.wos.citedcount 29
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