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Financial Statement Fraud Detection by Data Mining


Affiliations
1 GITAM University, India
2 Magadh University, India
3 Govt. Polytechnic College for Women, Bhimunipatnam, India
 

Financial losses due to financial statement frauds (FSF) are increasing day by day in the world. The industry recognizes the problem and is just now starting to act. Although prevention is the best way to reduce frauds, fraudsters are adaptive and will usually find ways to circumvent such measures. Detecting fraud is essential once prevention mechanism has failed. Several data mining algorithms have been developed that allow one to extract relevant knowledge from a large amount of data like fraudulent financial statements to detect FSF. It is an attempt to detect FSF; We present a generic framework to do our analysis.

Keywords

Financial Fraud Detection, Fraudulent Financial Statements, Data Mining, Management Fraud.
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  • Financial Statement Fraud Detection by Data Mining

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Authors

G. Apparao
GITAM University, India
Arun Singh
Magadh University, India
G. S. Rao
GITAM University, India
B. Lalitha Bhavani
GITAM University, India
K. Eswar
GITAM University, India
D. Rajani
Govt. Polytechnic College for Women, Bhimunipatnam, India

Abstract


Financial losses due to financial statement frauds (FSF) are increasing day by day in the world. The industry recognizes the problem and is just now starting to act. Although prevention is the best way to reduce frauds, fraudsters are adaptive and will usually find ways to circumvent such measures. Detecting fraud is essential once prevention mechanism has failed. Several data mining algorithms have been developed that allow one to extract relevant knowledge from a large amount of data like fraudulent financial statements to detect FSF. It is an attempt to detect FSF; We present a generic framework to do our analysis.

Keywords


Financial Fraud Detection, Fraudulent Financial Statements, Data Mining, Management Fraud.