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@article{151892,
        author = {Deepanshu Srivastava and Neera Chaudhary and Abhishek Verma  and Jagriti Varshney and Awanish Katiyar},
        title = {Credit card Fraud Detection System using Machine Learning},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {8},
        number = {1},
        pages = {1156-1160},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=151892},
        abstract = {Credit card use is not always beneficial for everyone, and it can result in significant financial losses in some cases.The frauds of credit cards are now increasing day by day. As the digitalization of internet purchasing grows, so does the use of credit cards for online transactions.Thus, most of the financial institutions and banks now prefer credit card fraud detection application. There are many types of fraudulent transactions which can happen in various ways with anyone, anywhere.Credit card firms must be able to recognize credit card fraud transactions in order to prevent or identify fraudulent transactions of products that the consumer did not purchase.Data science and machine are now helping to identify these fraud transactions. Fraud transactions are frequently mixed up with valid transactions, and simple recognition approaches that compare both the fraud and normal data are never enough to effectively detect fraud transactions. This study uses Credit Card Fraud Detection to demonstrate the modelling of a knowledge set using machine learning. The Credit Card Fraud Detection Problem entails credit card transaction modelling, which has previously been done with fraud transaction data.},
        keywords = {Credit Card, Machine learning, Detection, Random Forest},
        month = {},
        }