REVIEW on FRAUD DETECTION in CREDIT CARD TRANSACTIONS USING MACHINE LEARNING TECHNIQUES

Abstract

Due to the rapid improvement in the e-commerce technology, the utilization of the credit cards has augmented to the maximum. Usage of credit card has become the trendiest style of payment for an individual online as well as habitual acquisition, luggage of credit card fraud also growing linearly. Economic fraud is increasing highly with the development of modern technology, consequential in the loss of billions of dollars worldwide each year. The fraud transactions have been happening very much lately, such that the simple pattern corresponding techniques is not sufficient to find. Implementation of efficient fraud detection systems based on machine learning techniques has thus become effective for all credit card issuing banks to minimize their loss. Many techniques based on Artificial Intelligence, Data mining, Machine learning, Genetic Programming etc., has evolved in detecting various credit card fraudulent transactions. The details of the credit card transactions undergo a scrutiny process to allow a modeled credit card fraud detection system to be tested. This method gives an accurate and fraud score and tries to classify a transaction between a genuine one and a fraud one, the probability of fraud transactions can also be determined.