Sometimes a fraud examination appears daunting because of an extensive amount of data that needs to be sifted to identify exceptions. In one instance, a company was at risk for overreporting revenue on its financial statements. Because this was a new audit engagement, these overstatements may have existed in the prior year as well as the current year. As usual, we had limited time to complete the audit so everyone involved wanted answers fast. What added to the pressure was the fact that there were more than 5,700 customer accounts and any one of them could have been a fraudulent reporting of revenue.
In this situation, some fraud examiners would select samples of customer invoices to confirm through positive and negative confirmation with customers. Others would ask credit managers and accounting personnel if they saw any unusual activity while others would conduct high-level analytical review of financial statements. While effective at times, these procedures are all flawed because customer confirmations may not detect prior-year issues, inquiries of management who may be involved in the fraud may not provide the desired results, and high-level analysis of anything is simply that - high-level - and may not go deep enough to detect fraud.
Another more effective approach (that should be used in conjunction with these audit procedures) is data analysis and in this particular case, graphing. Through the graphing of customer account changes, material swings in invoice amounts and counts can be readily seen at a level that has a better chance of detecting material fraud in the financial statements. What's best is such a technique doesn't require expensive tools but rather the standard graphing abilities of Microsoft Excel.