DC Field | Value | Language |
dc.contributor.author | KINIOUAR, CHaima | - |
dc.contributor.author | BOUAMRA, YOusra | - |
dc.date.accessioned | 2023-10-15T10:18:47Z | - |
dc.date.available | 2023-10-15T10:18:47Z | - |
dc.date.issued | 2023 | - |
dc.identifier.uri | https://repository.esi-sba.dz/jspui/handle/123456789/496 | - |
dc.description | Encadrant : Saidi Iméne / Co-encadrant : Mahammed Nadir | en_US |
dc.description.abstract | Abstract :
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.iso | en | en_US |
dc.subject | Credit Card Frauds | en_US |
dc.subject | Machine Learning | en_US |
dc.subject | Classification Technique | en_US |
dc.subject | Fraud Detection | en_US |
dc.title | Credit card fraud detection using machine learning | en_US |
dc.type | Thesis | en_US |
Appears in Collections: | Master
|