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Please use this identifier to cite or link to this item: https://repository.esi-sba.dz/jspui/handle/123456789/496
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dc.contributor.authorKINIOUAR, CHaima-
dc.contributor.authorBOUAMRA, YOusra-
dc.date.accessioned2023-10-15T10:18:47Z-
dc.date.available2023-10-15T10:18:47Z-
dc.date.issued2023-
dc.identifier.urihttps://repository.esi-sba.dz/jspui/handle/123456789/496-
dc.descriptionEncadrant : Saidi Iméne / Co-encadrant : Mahammed Nadiren_US
dc.description.abstractAbstract : The use of credit cards in financial transactions has brought about changes in global operations. Despite being a cash-based society, Algeria is increasingly embracing digital payment methods. However, the country faces obstacles such as the low level of financial literacy, cultural norms surrounding cash, and limited digital infrastructure in some areas. Although credit cards offer various advantages, they also pose a risk of fraudulent activities. To protect their clients, financial institutions, banks, and businesses have devised methods to detect unusual transactions. To this end, credit cards fraud detection models based on machine learning are being developed to counter illegal activities. In this work, we aimed to comprehensively explore and synthesize various methodologies employed in credit card fraud detection using machine learning. Our objective was to offer a comprehensive overview of the advancements made in this field. *** Résumé : L’utilisation des cartes de cr´edit dans les transactions financi`eres a engendr´e des changements dans les op´erations mondiales. Malgr´e le fait que l’Alg´erie soit une soci´et´e `a base de cash, elle adopte de plus en plus les m´ethodes de paiement num´eriques. Cependant, le pays est confront´e `a des obstacles tels que le faible niveau de litt´eratie financi`ere, les normes culturelles entourant l’argent liquide et l’infrastructure num´erique limit´ee dans certaines r´egions. Bien que les cartes de cr´edit offrent divers avantages, elles pr´esentent ´egalement un risque d’activit´es frauduleuses. Pour prot´eger leurs clients, les institutions financi`eres, les banques et les entreprises ont ´elabor´e des m´ethodes pour d´etecter les transactions inhabituelles. Dans notre travail, nous avons essay´e d’´etudier et de synth´etiser diff´erentes approches afin de fournir une vue d’ensemble de ce qui est r´ealis´e dans le domaine de la d´etection de la fraude par carte de cr´edit `a l’aide de l’apprentissage automatique. Notre objectif ´etait de proposer une vue d’ensemble compl`ete des avanc´ees r´ealis´ees dans ce domaine.en_US
dc.language.isoenen_US
dc.subjectCredit Card Fraudsen_US
dc.subjectMachine Learningen_US
dc.subjectClassification Techniqueen_US
dc.subjectFraud Detectionen_US
dc.titleCredit card fraud detection using machine learningen_US
dc.typeThesisen_US
Appears in Collections:Master

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