Credit Card Fraud Detection Using State-of-the-Art Machine Learning and Deep Learning Algorithms

Author(s)	M.Shraddha, K. Sumedha, V.Veda Samhitha
Country	India
Abstract	This research study aims to detect credit card frauds, such as accessibility of public data, high-class imbalance data, changes in fraud nature, and high rates of false alarm. Machine learning and deep learning algorithms have been used to detect frauds, but there is still a need to apply state-of-the-art deep learning algorithms to reduce fraud losses. Comparative analysis of both machine learning and deep learning algorithms was performed to find efficient outcomes. The European card benchmark dataset was used to evaluate the proposed model, which outperformed the state-of-the-art machine learning and deep learning algorithms.
Keywords	Fraud detection, deep learning, machine learning, online fraud, credit card frauds, transaction data analysis.
Field	Engineering
Published In	Volume 5, Issue 3, May-June 2023
Published On	2023-05-12
Cite This	Credit Card Fraud Detection Using State-of-the-Art Machine Learning and Deep Learning Algorithms - M.Shraddha, K. Sumedha, V.Veda Samhitha - IJFMR Volume 5, Issue 3, May-June 2023. DOI 10.36948/ijfmr.2023.v05i03.2926
DOI	https://doi.org/10.36948/ijfmr.2023.v05i03.2926
Short DOI	https://doi.org/gr77qc

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International Journal For Multidisciplinary Research