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DOI: 10.14569/IJACSA.2012.030825
PDF

Prevention and Detection of Financial Statement Fraud – An Implementation of Data Mining Framework

Author 1: Rajan Gupta
Author 2: Nasib Singh Gill

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 3 Issue 8, 2012.

  • Abstract and Keywords
  • How to Cite this Article
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Abstract: Every day, news of financial statement fraud is adversely affecting the economy worldwide. Considering the influence of the loss incurred due to fraud, effective measures and methods should be employed for prevention and detection of financial statement fraud. Data mining methods could possibly assist auditors in prevention and detection of fraud because data mining can use past cases of fraud to build models to identify and detect the risk of fraud and can design new techniques for preventing fraudulent financial reporting. In this study we implement a data mining methodology for preventing fraudulent financial reporting at the first place and for detection if fraud has been perpetrated. The association rules generated in this study are going to be of great importance for both researchers and practitioners in preventing fraudulent financial reporting. Decision rules produced in this research complements the prevention mechanism by detecting financial statement fraud.

Keywords: Data mining framework; Rule engine; Rule monitor.

Rajan Gupta and Nasib Singh Gill, “Prevention and Detection of Financial Statement Fraud – An Implementation of Data Mining Framework” International Journal of Advanced Computer Science and Applications(IJACSA), 3(8), 2012. http://dx.doi.org/10.14569/IJACSA.2012.030825

@article{Gupta2012,
title = {Prevention and Detection of Financial Statement Fraud – An Implementation of Data Mining Framework},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2012.030825},
url = {http://dx.doi.org/10.14569/IJACSA.2012.030825},
year = {2012},
publisher = {The Science and Information Organization},
volume = {3},
number = {8},
author = {Rajan Gupta and Nasib Singh Gill}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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