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IJSTR >> Volume 9 - Issue 3, March 2020 Edition

International Journal of Scientific & Technology Research  
International Journal of Scientific & Technology Research

Website: http://www.ijstr.org

ISSN 2277-8616

A Survey To Detect Financial Fraud Using Deep Learning Approaches

[Full Text]



Pooja Singh, Subhash Chandra Jat



Intrusion Detection System, Fraud Detection, Financial Fraud, Online Transaction, Deep Learning, Security Challenges.



The more financial transactions have now emerged throughout the Big Data era, with numerous opportunities, threats and possibility of information theft in the face of possible fraud. This is due to the massive use of electronic paying instruments aimed at stealing confidential information and performing fraudulent transactions by attackers. While smart fraud detection systems have been established to deal with this problem, the imbalances of the data are still associated with some famous problems. This paper uses a fabricated identity to benefit financially or otherwise from identity fraud. When society moves further into a digital economy, the number of fraudulent transactions is increasingly rising. Here the emphasis is on the approaches that use profound learning and timely analysis of existing methods for the detection of payment fraud. The aim of the survey is to regularly benchmark methods for detecting fraud in online transaction volumes for industry. This test demonstrates that, in spite of the study, different methods for detecting fraud have a realistic performance in the industry. The underlying difficulties in applying a deep understanding of fraud are discerned.



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