Paper Title :Intelligent Credit Card Fraud Detection Using Machine Learning and Deep Learning Techniques

Author :Deepa. J, Srinivasan. S, Sethu Mohan Raj. R, Shrihari. S

Article Citation :Deepa. J ,Srinivasan. S ,Sethu Mohan Raj. R ,Shrihari. S , (2024 ) " Intelligent Credit Card Fraud Detection Using Machine Learning and Deep Learning Techniques " , International Journal of Advance Computational Engineering and Networking (IJACEN) , pp. 8-14, Volume-12,Issue-3

Abstract : Credit card fraud is the illicit act of misleading someone who is the legitimate credit card holder. Machine learning techniques can assist in detecting and stopping these fraudulent transactions. Different types of credit card fraud include simple theft, scam involving applications and bankruptcy fraud, internal fraud as well as fake or behavioral fraud. Experimental studies have shown that ANN (Artificial Neural Network) and random forest algorithm provide good results in detecting credit card fraud. To Develop a model that forecasts whether a transaction will be fraudulent or not. Several predictive models, including Decision Trees, K-neighbors, SVM’s, ANN’s, Gaussian Naive Bayes, and Logistic Regression are employed. A superior model is identified by comparing the accuracy of each of these models' outputs. Keywords - Machine Learning, Deep Learning, Artificial Neural Networks, Random Forest, XG Boost, Rectified Linear Unit, Support Vector Machines.

Type : Research paper

Published : Volume-12,Issue-3

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