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Paper Title : Fraudulent Credit Card Transactions Classification using Randomized Search CV with XGB Classifier

ISSN : 2395-1303
Year of Publication : 2020
10.29126/23951303/IJET-V6I5P3

Mr. Kapil Dev Tripathi,Mr.Vikash Singh Rajput

         


Abstract
- The amount of credit card transactions (CCTs) is increasing exponentially with the rapid development of electronic retail. When the most common type of transaction is shopping online, purchase fraud is growing as well. Fraudulent CCTs regularly cause companies & consumers large financial costs so fraudsters are constantly trying to discover innovative techniques or solutions to fraudulent purchases. The prevention of fraudulent transactions has been an significant element in increasing the usage of online payments.Effective & efficient solutions to fraud identification in CCTs are also required. Fraudulent transactions can take place in various forms and can be categorized as being. This research work has done by Randomized Search CV with XGB Classifier for accurate prediction of fraudulent transactions. The large volume of CCF data is applied for the experiment which is taken from UCI repository. The simulation is done by Jupiter notebook of Python. The significance of proposed model is measured by different performance parameters those are accuracy, precision, recall, F1 score, MCC and ROC. From the results we achieved 83.02% accuracy.

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Keywords
Machine Learning, Fraud, Fraudulent Transactions, Credit Card Fraud,Randomized Search CV, XGB Classifier.