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International Journal of Innovative Research in Electrical, Electronics, Instrumentation and Control Engineering
International Journal of Innovative Research in Electrical, Electronics, Instrumentation and Control Engineering A monthly Peer-reviewed & Refereed journal
ISSN Online 2321-2004ISSN Print 2321-5526Since 2013
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← Back to VOLUME 9, ISSUE 12, DECEMBER 2021

Credit Card Fraud Detection Using Machine Learning

Mrs. Prof. Lakshmipraba Balaji, Mr. Janardhan umale,Ms. Prajakta Tembare, Mr. Prasnna Kerutagi

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Abstract: Credit card fraud is the most serious problem in today's world, and there is an urgent need to combat it. "Credit card fraud is the process of cleaning dirty money, making the source of funds untraceable." On a daily basis, huge amounts of money are exchanged in the global market, making detecting credit card fraud activity a difficult task. As previously stated, (Anti-credit card fraud Suite) is introduced to detect suspicious activities, but it is only applicable to individual transactions and not to other bank account transactions. To address these issues, we propose a machine learning method based on 'Structural Similarity.' This method identifies common attributes and behaviour with other bank account transactions. It is difficult to detect credit card fraud transactions from large datasets, so we propose case reduction methods to reduce the input dataset and then find pairs of transactions with other bank accounts that share common attributes and behaviour.

Keywords: Machine learning ,SVM algorithm

How to Cite:

[1] Mrs. Prof. Lakshmipraba Balaji, Mr. Janardhan umale,Ms. Prajakta Tembare, Mr. Prasnna Kerutagi, β€œCredit Card Fraud Detection Using Machine Learning,” International Journal of Innovative Research in Electrical, Electronics, Instrumentation and Control Engineering (IJIREEICE), DOI: 10.17148/IJIREEICE.2021.91209

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