Credit Card Fraud Detection Using Machine Learning

Credit Card Fraud Detection Using Machine Learning

Madhuri R. Gangwe1, Dr Smita S Ponde2

1Department of Computer Engineering, DIEMS, BATU University, Lonere (M. S) India

1Department of Computer Engineering, DIEMS, BATU University, Lonere (M. S) India

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Abstract -The aim of the project is to restrict fraudsters from using consumers' accounts for unauthorised purposes by using machine learning algorithms to detect fraudulent credit card transactions. Because credit card fraud is becoming more and more commonplace globally, steps need to be done to put an end to those who commit fraud. Setting a restriction on those activities will benefit the clients since the project's primary objective will be achieved—their money will be recovered and refunded into their accounts, and they won't be charged for goods or services that they did not acquire. Three machine learning techniques—KNN, SVM, and Logistic Regression—will be used to detect fraudulent transactions. The models are going to be applied to a dataset of credit card transactions.

Key Words: Credit Card Fraud Detection, Fraud Detection, Fraudulent Transactions, K-Nearest Neighbors, Support Vector Machine, Logistic Regression, NaïveBayes.