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International Journal of Advanced Research in Computer and Communication Engineering A monthly Peer-reviewed & Refereed journal
ISSN Online 2278-1021ISSN Print 2319-5940Since 2012
IJARCCE adheres to the suggestive parameters outlined by the University Grants Commission (UGC) for peer-reviewed journals, upholding high standards of research quality, ethical publishing, and academic excellence.
← Back to VOLUME 12, ISSUE 6, JUNE 2023

Credit Card Fraud Detection using Machine Learning and Deep Learning

Shrushti Deshmukh , Ayodhya Patil , Diksha Sonawane , Mayuri Hirnawale ,Dr.(Mrs) S. S. Raskar

DOI: 10.17148/IJARCCE.2023.12632

Abstract: This paper discusses how machine learning techniques can be used to detect credit card fraud. It covers the types of fraud, challenges, and various ML algorithms used. The steps for building an ML-based fraud detection system are explained, and current and future trends are examined. Overall, ML-based fraud detection systems can significantly improve accuracy and efficiency, leading to better customer protection and reduced financial losses.

Keywords: Machine Learning, Deep Learning, Logistic Regression, CNN.

How to Cite:

[1] Shrushti Deshmukh , Ayodhya Patil , Diksha Sonawane , Mayuri Hirnawale ,Dr.(Mrs) S. S. Raskar, “Credit Card Fraud Detection using Machine Learning and Deep Learning,” International Journal of Advanced Research in Computer and Communication Engineering (IJARCCE), DOI: 10.17148/IJARCCE.2023.12632