INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2456-4184 | Impact factor: 8.76 | ESTD Year: 2016
Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.76 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)
This collaborative review paper amalgamates insights from various studies on real-time fraud detection using machine learning in the context of online transactions. Focusing on credit card fraud, it explores innovative approaches such as clustering cardholders based on transaction amounts and employing a sliding window strategy to extract behavioral patterns. Additionally, the review addresses the challenges of network transactions, proposing fraud detection algorithms with impressive AUC values.In the realm of online banking fraud, the paper introduces models extending classical machine learning methods, incorporating economic optimization and a risk model. Real-world testing demonstrates significant reductions in expected financial losses, surpassing benchmarks. This unified perspective underscores the complexities, ongoing challenges, and potential solutions in the dynamic landscape of fraud detection. The collaborative efforts presented herein provide a holistic understanding of the intricacies involved in combating fraud systematically and economically.
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"Realtime Fraud Detection Analysis Using Machine Learning.", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.8, Issue 12, page no.a495-a499, December-2023, Available :http://www.ijnrd.org/papers/IJNRD2312063.pdf
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2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
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