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Credit Card Fraud Detection using Deep Learning

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dc.contributor.author Muhammad Qasim, 01-134182-115
dc.contributor.author M Sarib Manzoor, 01-134182-114
dc.date.accessioned 2022-11-15T07:03:52Z
dc.date.available 2022-11-15T07:03:52Z
dc.date.issued 2022
dc.identifier.uri http://hdl.handle.net/123456789/13985
dc.description Supervised by Mr. Abdul Hannan en_US
dc.description.abstract Credit card fraud is becoming increasingly widespread as more of us use credit cards for payment. This is owing to technological advancements and a surge in online transactions, which has resulted in scams incurring massive financial losses. Every year, credit card firms and banks lose billions of dollars to such fraudulent actions, costing them a significant portion of their revenue and affecting the jobs of several people. As a result, we must examine and distinguish between fraudulent and nonfraudulent transactions. This article focuses on identifying fraud detection. This research proposes a Deep Learning model ANN Artificial Neural Network for monitoring and detecting fraudulent activity. The proposed method is capable to detect fraud transactions with an average accuracy of 97 percent and F1-Score of 0.97 of both 0 and 1 cases. en_US
dc.language.iso en en_US
dc.publisher Computer Sciences en_US
dc.relation.ispartofseries BS (CS);P-1488
dc.subject Credit Card en_US
dc.subject Fraud Detection en_US
dc.title Credit Card Fraud Detection using Deep Learning en_US
dc.type Project Reports en_US


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