Paper Key : IRJ************899
Author: Hariom Sharma
Date Published: 13 Oct 2023
Abstract
In todays socio-economic scenario, people rely heavily on credit cards. Moreover, credit cards are a requisite financial tool that enables its holders to make assets. It is true that credit cards, as a new method of payment, have become socially amenable to the masses. But nowadays, improvements in technology lead to growth in illegal activities. During credit card transactions many fraudsters can breach security and make fraudulent transactions to withdraw or transfer funds from ones account or e-wallets. The relevant literature presents many machine learning-based approaches for credit card detection, such as Logistic Regression, Decision Tree, CatBoost, Random Forest, Support Vector Machine, KNN, RNN, and CNN. The main focus has been to apply the recent development of deep learning algorithms for this purpose. Comparative analysis of both machine learning and deep learning algorithms was performed to find efficient outcomes. A machine learning algorithm was first applied to the dataset, which improved the accuracy of detection of the fraud to some extent. The proposed approaches can be implemented effectively for the real-world detection of credit card fraud.
DOI LINK : 10.56726/IRJMETS45225 https://www.doi.org/10.56726/IRJMETS45225