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VOL. 10, ISSUE 2 (2025)
Comparative analysis of approaches for credit card fraud detection: Insights from data science and machine learning
Authors
Paras Gera, Sachin Kumar Rai, Priyank Sharma, Dr. Meena Chaudhary, Dr. Narender Gautam
Abstract
An area of great importance
data-scientifically is that of credit card fraud detection, which focuses on an
ever-increasing demand for accurate and timely detection of fraudulent
transactions. The present study attempts to target advanced data-science techniques
to analyze and detect different patterns of fraud for large transaction
datasets, emphasizing the trade-off between model accuracy and minimization of
false positives. Our methodology brings together techniques from machine
learning and graph analysis to uncover concealed relationships and suspicious
transaction patterns among the accounts and merchants involved. This study
illustrates how data science can contribute to dynamic data-driven solutions
against ever-evolving threats of fraud.
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Pages:106-111
How to cite this article:
Paras Gera, Sachin Kumar Rai, Priyank Sharma, Dr. Meena Chaudhary, Dr. Narender Gautam "Comparative analysis of approaches for credit card fraud detection: Insights from data science and machine learning". International Journal of Advanced Education and Research, Vol 10, Issue 2, 2025, Pages 106-111
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