Real-time Credit Card Fraud Detection Using Machine Learning

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Aim:

To detect the real time credit card fraud transaction using machine learning algorithms.

Existing System:

The obtained results are compared with the results of existing models within the same domain and found to be improved. The data of credit card fraud transactions data collected from the kaggle is used to discover patterns with Neural Network, Decision Tree, Support Vector machines (SVM), and Naive Bayes. The results are compared for performance and accuracy with these algorithms. So, we will move to the proposed model.

Proposed System:

In this paper, we propose a novel credit-card fraud detection system by detecting three different patterns of fraudulent transactions using best Machine learning algorithms and by addressing the related problems identified by past researchers in credit card fraud detection.