TY - JOUR
AU - 
AB - 10 V May 2022 https://doi.org/10.22214/ijraset.2022.42920 International Journal for Research in Applied Science & Engineering Technology (IJRASET) ISSN: 2321-9653; IC Value: 45.98; SJ Impact Factor: 7.538 Volume 10 Issue V May 2022- Available at www.ijraset.com Credit Card Fraud Detection 1 2 3 4 Prof. R .B. Gurav , Mrs. Shraavani Mandar Badhe , Mr. Sarthak Pandit Sonawane ,Mr. Siddhant Agarwal , Mrs. Sakshi Nagtilak Teacher, Department of Information Technology, AISSMS's Polytechnic, Pune, Maharashtra, India 2, 3, 4, 5 Student, Department of Information Technology, AISSMS's Polytechnic, Pune, Maharashtra, India Abstract: Now a day’s online transactions have become an important and necessary part of our lives. It is vital that credit card companies are able to identify fraudulent credit card transactions so that customers are not charged for items that they did not purchase. As frequency of transactions is increasing, number of fraudulent transactions are also increasing rapidly. Such problems can be tackled with Machine Learning with its algorithms. This project intends to illustrate the modelling of a data set using machine learning with Credit Card Fraud Detection. The Credit Card Fraud Detection Problem includes modelling past credit card transactions with the data of the ones that turned out to be fraud. 
TI - Credit Card Fraud Detection System
JF - International Journal for Research in Applied Science and Engineering Technology
DO - 10.22214/ijraset.2022.40744
DA - 2022-03-31
UR - https://www.deepdyve.com/lp/unpaywall/credit-card-fraud-detection-system-UEsgpcU0x0
DP - DeepDyve
ER -