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A Data Mining Framework for Prevention and Detection of Financial Statement Fraud

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International Journal of Computer Applications
© 2012 by IJCA Journal
Volume 50 - Number 8
Year of Publication: 2012
Authors:
Rajan Gupta
Nasib Singh Gill
10.5120/7789-0889

Rajan Gupta and Nasib Singh Gill and. Article: A Data Mining Framework for Prevention and Detection of Financial Statement Fraud. International Journal of Computer Applications 50(8):7-14, July 2012. Full text available. BibTeX

@article{key:article,
	author = {Rajan Gupta and Nasib Singh Gill and},
	title = {Article: A Data Mining Framework for Prevention and Detection of Financial Statement Fraud},
	journal = {International Journal of Computer Applications},
	year = {2012},
	volume = {50},
	number = {8},
	pages = {7-14},
	month = {July},
	note = {Full text available}
}

Abstract

Financial statement fraud has reached the epidemic proportion globally. Recently, financial statement fraud has dominated the corporate news causing debacle at number of companies worldwide. In the wake of failure of many organisations, there is a dire need of prevention and detection of financial statement fraud. Prevention of financial statement fraud is a measure to stop its occurrence initially whereas detection means the identification of such fraud as soon as possible. Fraud detection is required only if prevention has failed. Therefore, a continuous fraud detection mechanism should be in place because management may be unaware about the failure of prevention mechanism. In this paper we propose a data mining framework for prevention and detection of financial statement fraud.

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