ATM cash flow prediction and replenishment optimization with ANN

dc.authorid0000-0003-1250-5949en_US
dc.contributor.authorÖzpınar, Alper
dc.contributor.authorSerengil, Sefik Ilkin
dc.date.accessioned2019-08-08T12:43:54Z
dc.date.available2019-08-08T12:43:54Z
dc.date.issued2019en_US
dc.departmentFakülteler, Mühendislik Fakültesien_US
dc.description.abstractATMs are physical interaction points between financial institutions and real customers. Storing physical cash causes renouncing to get interested. On the other hand, customer satisfaction requires to store the necessary cash amount. This concern becomes even more critical for countries having high-interest rate and overnight interest rates are higher. In this paper, we will show that daily cash withdrawals are predictable and we will propose a cost function for replenishment optimization. Experiments show that proposed model decrease idle balance dramatically.en_US
dc.identifier.doi10.29137/umagd.484670en_US
dc.identifier.endpage408en_US
dc.identifier.issue1en_US
dc.identifier.startpage402en_US
dc.identifier.trdizinid494148en_US
dc.identifier.urihttps://hdl.handle.net/11467/2859
dc.identifier.urihttps://doi.org/10.29137/umagd.484670
dc.identifier.volume11en_US
dc.indekslendigikaynakTR-Dizinen_US
dc.language.isoenen_US
dc.publisherKırıkkale Üniversitesien_US
dc.relation.ispartofUluslararası Mühendislik Araştırma ve Geliştirme Dergisien_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectATM Replenishmenten_US
dc.subjectCash Optimizationen_US
dc.titleATM cash flow prediction and replenishment optimization with ANNen_US
dc.typeArticleen_US

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