ATM Cash Flow Prediction and Replenishment Optimization with ANN

dc.contributor.authorSerengil, Sefik İlkin
dc.contributor.authorOzpinar, Alper
dc.date.accessioned2025-01-21T14:21:05Z
dc.date.available2025-01-21T14:21:05Z
dc.date.issued2019
dc.description.abstractATMs are physical interaction points betweenfinancial institutions and real customers. Storing physical cash causesrenouncing to get interested. On the other hand, customer satisfaction requiresto store the necessary cash amount. This concern becomes even more critical forcountries having high-interest rate and overnight interest rates are higher. Inthis paper, we will show that daily cash withdrawals are predictable and wewill propose a cost function for replenishment optimization. Experiments showthat proposed model decrease idle balance dramatically.
dc.identifier.dergipark484670
dc.identifier.doi10.29137/umagd.484670
dc.identifier.issn1308-5514
dc.identifier.issue1-402
dc.identifier.startpage408
dc.identifier.urihttps://dergipark.org.tr/tr/download/article-file/650577
dc.identifier.urihttps://dergipark.org.tr/tr/pub/umagd/issue/39915/484670
dc.identifier.urihttps://doi.org/10.29137/umagd.484670
dc.identifier.urihttps://hdl.handle.net/20.500.12587/19319
dc.identifier.volume1
dc.language.isoen
dc.publisherKırıkkale Üniversitesi
dc.relation.ispartofUluslararası Mühendislik Araştırma ve Geliştirme Dergisi
dc.relation.publicationcategoryMakale - Ulusal Hakemli Dergi
dc.rightsinfo:eu-repo/semantics/openAccess
dc.snmzKA_20241229
dc.subjectATM Replenishment
dc.subjectCash Optimization
dc.titleATM Cash Flow Prediction and Replenishment Optimization with ANN
dc.typeArticle

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