Can We Detect Fraud Earlier? A Technique Called Content Analysis Raises the Possibility
Churyk, Natalie Tatiana, Lee, Chih-Chen, Clinton, B. Douglas, Strategic Finance
Wouldn't it be helpful to be able to detect fraud earlier? The ability to do so would probably reduce the impact of any particular incident of fraud considerably because history shows us that most fraudulent events tend to start out slowly and build over time. Prior fraud-detection research based the likelihood of fraud on numbers and ratios, but this method is usually too late to be effective because it indicates fraud long after catastrophic financial results are irreversible.
Our study is different. We examined the words and grammatical cues used in business reporting for detection, focusing on the Management's Discussion and Analysis (MD&A) section of annual reports since this section contains the written assertions of management. We analyzed management's communication in this section for cues regarding deception that might be used to conceal fraudulent activity. By examining these written statements, we confirmed that early detection is possible. In this article we explain how.
To determine a company's likelihood of deception involved with misstating financial statements, we used a method called content analysis to focus on specific written content that might indicate that things in the annual report weren't likely to be what they seemed. These included characteristics in written communication that indicated lack of organization (i.e., apparently trying to be unclear as to disguise the truth), increased brevity (i.e., to decrease the risk of making mistakes), decreased expression of optimism, and less expression of certainty. These grammatical characteristics are potential indicators of deception that show up much earlier than when they are borne out in the financial results--thus providing the key to early detection. All of these items showed significance in detecting deception. These indicators are part of a method that could be used by management accounting professionals to reliably detect fraud in a timelier manner.
SEARCHING FOR FRAUD
There is a great amount of motivation for discovering reliable ways of detecting fraud after devastating financial results occur, but consider how much better it would be to detect fraud before this happens. Think for a moment about the damage that resulted in the major companies where fraud was detected in recent years. Think about WorldCom, Enron, HealthSouth, and Xerox. Consider the dissolution of Arthur Andersen and the victims of lost pension plans and ruined careers. Rather than looking for reasons why management overstated earnings or why the market reacts to overstatements, we hope to identify cues that assist in the detection of fraudulent information earlier, which could help to prevent catastrophe.
We know that the presence of financial irregularity is a huge problem that the accounting profession has suffered, especially recently. The number of incidents of violations has increased over the years as indicated by the increase in the number of Accounting and Auditing Enforcement Releases (AAERs) filed by the Securities & Exchange Commission (SEC). These are companies that the SEC required to restate their financial statements. (When the SEC formally charges a company with a violation, it issues an AAER.) The number of these required restatements has doubled recently and keeps climbing.
Many researchers are trying to find reliable fraud indicators, and some are working on building fraud-prediction models. In terms of fraud detection, auditors are required to assess the likelihood of fraudulent financial reporting throughout audits. The American Institute of Certified Public Accountants (AICPA) and the Committee of Sponsoring Organizations of the Treadway Commission (COSO) have issued standards and reports to aid auditors in detecting various types of fraud. For instance, Statement on Auditing Standards (SAS) No. 99, "Consideration of Fraud in a Financial Statement Audit," issued in 2002, provides auditors with a list of risk factors categorized into three areas: incentives/pressure, opportunities, and attitude/rationalization. …