Paper Key : IRJ************462
Author: Pooja Balu Wankhede,Dr Dinesh D. Patil,Dr. Priti Subramanium
Date Published: 06 Nov 2023
Abstract
Credit Cards can be used in online transactions due to the convenience and ease of use. Credit card fraud is one of the leading causes of financial losses for credit card issuers and finance companies. Card fraud has cost credit card companies money. Currently, card fraud detection is the most common problem facing credit card companies. Credit card companies are searching for good systems and technologies to identify and reduce fraudulent transactions. There are a number of credit card detection techniques in machine learning. There are a number of credit card fraud detection techniques that have been examined and highlighted in this paper and have been compared in terms of their drawbacks and benefits. Credit cards are the most popular way to pay online because there are more and more people making electronic transactions susceptible to fraud. Credit cards have been a growing issue in recent years. It has caused a huge financial loss for individuals using credit cards as well as for books and merchants. Machine learning is one of the most effective techniques for detecting fraud. This paper surveys various fraud detection techniques and methods using machine learning and compares them using performance metrics, such as accuracy, precision and specificity. Keywords: Credit Card Fraud, Random Forest, Deep Machine Learning, Online Transactions, Fraudulent Transactions.
DOI LINK : 10.56726/IRJMETS45811 https://www.doi.org/10.56726/IRJMETS45811