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Advancement of management information system for discovering fraud in master card based intelligent supervised machine learning and deep learning during SARS-CoV2 by Banghua Wu; Xuebin Lv; Abdullah Alghamdi; Hamad Abosaq; Mesfer Alrizq is a Computer Science article available to read on EtoBox.

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During coronavirus (SARS-CoV2) the number of fraudulent transactions is expanding at a rate of alarming (7,352,421 online transaction records). Additionally, the Master Card (MC) usage is increasing. To avoid massive losses, companies of finance must constantly improve their management information systems for discovering fraud in MC. In this paper, an approach of advancement management information system for discovering of MC fraud was developed using sequential modeling of data depend on intelligent forecasting methods such as deep Learning and intelligent supervised machine learning (ISML). The Long Short-Term Memory Network (LSTM), Logistic Regression (LR), and Random Forest (RF) were used. The dataset is separated into two parts: the training and testing data, with a ratio of 8:2. Also, the advancement of management information system has been evaluated using 10-fold cross validation depend on recall, f1-score, precision, Mean Absolute Error (MAE), Receiver Operating Curve (ROC), and Root Mean Square Error (RMSE). Finally various techniques of resampling used to forecast if a transaction of MC is genuine/fraudulent. Performance for without re-sampling, with under-sampling, and

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Author

Banghua Wu; Xuebin Lv; Abdullah Alghamdi; Hamad Abosaq; Mesfer Alrizq

Publisher

Elsevier BV

Published

2023

Language

EN

Field

Computer Science (Physical Sciences)