Abstract: This project mainly focuses on credit card fraud detection in real world scenarios. Nowadays credit card frauds are increasing in number as compared to previous years. Criminals are using various methods like identity theft, fraudulent phone calls or messages, site cloning etc to trap the users and get the money out of them and also few bank personnel cheats bank by entering wrong data like wrong card number and amount etc. Therefore, it is very essential to find a solution to these types of frauds. In this proposed project we designed a model to detect the fraud activity in credit card transactions. Many techniques based on Artificial Intelligence, Neural Networks, Decision Trees, Genetic Algorithm etc were developed to detect fraudulent transactions. This paper presents kmeans_smote oversampling technique, Random Forest Algorithm (RFA) along with Luhn Algorithm for credit card fraud detection

Keywords: Credit Card fraud, Random Forest Algorithm, kmeans_SMOTE, Luhn Algorithm

PDF | DOI: 10.17148/IJARCCE.2020.9428

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