Prevention and Detection of Financial Statement Fraud : A Data Mining Approach

The business of fraud presents a substantial cost to our economy worldwide. Measures to stop fraud from occurring, in the first place, are termed as fraud prevention, whereas identifying fraud as quickly as possible, once it has been perpetrated, is termed as fraud detection. Fraud detection comes into picture once fraud prevention fails. In practice, fraud detection must be done regularly, as one may not be aware of fraud prevention failure. This paper analyzes the generic data mining framework for the detection and identification of financial statement fraud, with an addition of fraud triangle, along with behavioral characteristics which may be helpful in preventing the fraud in the first place