Fraud-Fighting with data analysis tools

Detecting fraud risk with strong methodology


By Richard B. Lanza, CFE, CPA-CITP, PMP

Fear Not the Software

During a recent meeting, I was looking at a whiteboard on which an accounting malpractice attorney had mapped out a defense case for an auditor who had failed to detect a large billing scheme fraud. It was a classic combination of non-segregation of duties coupled with the misguided perception that a trusted employee would never steal from the organization. Unfortunately for the company and the auditor, the "trusted employee" had walked off with close to a million dollars from a credit card account; that loss was very material to the financial statements.

The attorney asked me how the auditor, if he had had the skills to complete the computerized test, would have been able to analyze data to detect the fraud. I explained that the auditor could have easily exported data to Excel. And then by running a quick vendor trend report, which would have compared this year's purchases to last, he would have seen that the credit card vendor account had ballooned to close to a million dollars in expenses in the current year.

The fraudster had simply written checks for her credit card bills. She had easily committed and hid the fraud because she had the authority to process invoices, write checks, and maintain the bank statement.

Because the attorney was defending the auditor and saw how quickly the auditor could have found the fraud with the computer tool, he asked me to not continue the discussion because of his sudden onset of heartburn.

This meeting forced me to realize that there's a definite methodology to data analysis in proactively detecting fraud. Even if the auditor had downloaded the company's accounts payable data, he still wouldn't have known how to manipulate it to find the questionable trends pointing to the misappropriation. Though the process I discuss in this column isn't perfect by any stretch, it's also not difficult and presents a consistent way to minimize fraud risk.

 

 

 


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