期刊名称：International Journal of Advances in Engineering and Management
电子版ISSN：2395-5252
出版年度：2021
卷号：3
期号：6
页码：1179-1183
DOI：10.35629/5252-030610481053
语种：English
出版社：IJAEM JOURNAL
摘要：In the financial services industry, credit card fraud is a serious problem. Every year, credit card theft results in the loss of billions of dollars. The scarcity of studies on the examination of real-time credit score card records is due to data sensitivity. In this work, we employed technology to learn about algorithms for detecting credit card fraud. To begin with, there are standard fashions. After that, hybrid strategies combining AdaBoost and majority balloting procedures are used. Credit cards that are widely available with credit score card collections is utilised to examine the version efficiency. Then a set of real-world foreign credit card data from a monetary organisation is analysed. Furthermore, noise is applied to the recorded samples in order to analyse the algorithms; energy. It’s worth noting that the test findings show that using the majority balloting methodology leads to accurate accuracy rates in credit card fraud detection cases.
