Financial Statement Fraud Detection using Text Mining
N. Rajan Gupta.
International Journal of Advanced Computer Science and Applications(IJACSA) (2012)

Data mining techniques have been used enormously by the researchers’ community in detecting financial statement fraud. Most of the research in this direction has used the numbers (quantitative information) i.e. financial ratios present in the financial statements for detecting fraud. There is very little or no research on the analysis of text such as auditor’s comments or notes present in published reports. In this study we propose a text mining approach for detecting financial statement fraud by analyzing the hidden clues in the qualitative information (text) present in financial statements.

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@article{IJACSA.2012.031230,
  abstract = {Data mining techniques have been used enormously by the researchers’ community in detecting financial statement fraud. Most of the research in this direction has used the numbers (quantitative information) i.e. financial ratios present in the financial statements for detecting fraud. There is very little or no research on the analysis of text such as auditor’s comments or notes present in published reports. In this study we propose a text mining approach for detecting financial statement fraud by analyzing the hidden clues in the qualitative information (text) present in financial statements. },
  added-at = {2014-02-21T08:00:08.000+0100},
  author = {{Rajan Gupta}, Nasib Singh Gill},
  biburl = {https://www.bibsonomy.org/bibtex/2e121c9b6aed1502331191bfaa09fb285/thesaiorg},
  interhash = {f4aec6f514e4aa162dc01563c5338148},
  intrahash = {e121c9b6aed1502331191bfaa09fb285},
  journal = {International Journal of Advanced Computer Science and Applications(IJACSA)},
  keywords = {Bag Machines. Mining; Support Text Vector of words;},
  number = 12,
  timestamp = {2014-02-21T08:00:08.000+0100},
  title = {{Financial Statement Fraud Detection using Text Mining}},
  url = {http://ijacsa.thesai.org/},
  volume = 3,
  year = 2012
}

%0 Journal Article
%1 IJACSA.2012.031230
%A Rajan Gupta, Nasib Singh Gill
%D 2012
%J International Journal of Advanced Computer Science and Applications(IJACSA)
%K Bag Machines. Mining; Support Text Vector of words;
%N 12
%T Financial Statement Fraud Detection using Text Mining
%U http://ijacsa.thesai.org/
%V 3
%X Data mining techniques have been used enormously by the researchers’ community in detecting financial statement fraud. Most of the research in this direction has used the numbers (quantitative information) i.e. financial ratios present in the financial statements for detecting fraud. There is very little or no research on the analysis of text such as auditor’s comments or notes present in published reports. In this study we propose a text mining approach for detecting financial statement fraud by analyzing the hidden clues in the qualitative information (text) present in financial statements.

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Financial Statement Fraud Detection using Text Mining
N. Rajan Gupta.
International Journal of Advanced Computer Science and Applications(IJACSA) (2012)

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Financial Statement Fraud Detection using Text MiningN. Rajan Gupta. International Journal of Advanced Computer Science and Applications(IJACSA) (2012)

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Financial Statement Fraud Detection using Text Mining
N. Rajan Gupta.
International Journal of Advanced Computer Science and Applications(IJACSA) (2012)