Credit Card Fraud Detection using Deep Learning Techniques

Credit Card Fraud Detection using Deep Learning Techniques

R.Shailaj , P.Soumya, B.Soumya , Y.Sravya Reddy , P.Sravya Reddy , Dr P Anjaiah

School of Engineering
MallaReddy University

ABSTRACT

People can use credit cards for online transactions as it provides an efficient and easy-to-usefacility.With the increase in usage of credit cards, the capacity of credit card misuse has also enhanced. Creditcard frauds cause significant financial losses for both credit card holders and financial companies. In this research study, the main aim is to detect such frauds, including the accessibility of public data, high-class imbalance data, the changes in fraud nature, and high rates of false alarm. The relevant literature presents many machines learning based approaches for credit card detection, such as Extreme Learning Method,Decision Tree, Random Forest, Support Vector Machine, Logistic Regression and XG Boost. However, dueto low accuracy, there is still a need to apply state of the art deep learning algorithms to reduce fraudlosses. 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.. Later, three architectures based on a convolutional neural network are applied to improve fraud detection performance. Further addition of layers further increased the accuracy of detection.