Financial fraud: Data mining application and detection
This paper reviews the data mining application and detection on financial fraud. This study also discuss the fundamental idea of financial fraud and the application of data mining in financial fraud detection. Moreover this study also provides a deep understanding on the merits and drawbacks of the...
| Published in: | Recent Trends in Social and Behaviour Sciences - Proceedings of the 2nd International Congress on Interdisciplinary Behavior and Social Sciences 2013, ICIBSoS 2013 |
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| Format: | Conference paper |
| Language: | English |
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Taylor and Francis - Balkema
2014
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| Online Access: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-84894843992&partnerID=40&md5=b013798211e34bf30d2358588935cbef |
| Summary: | This paper reviews the data mining application and detection on financial fraud. This study also discuss the fundamental idea of financial fraud and the application of data mining in financial fraud detection. Moreover this study also provides a deep understanding on the merits and drawbacks of the data mining application in detecting financial fraud. The sources of data collected include documents and text specifically from journals, authors review and a comparison analysis on merits and drawbacks of data mining. Data mining is proven to be reliable with high accuracy. Nonetheless the issues of privacy and security are the two main concerns in data mining application. © 2014 Taylor & Francis Group. |
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