Financial Statement Irregularities: Evidence from the Distributional Properties of Financial Statement Numbers

Anecdotal evidence suggests that a significant portion of financial statement irregularities are ignored or missed by reporting firms, their auditors, and the SEC. Motivated by a method used by forensic investigators and auditors to detect irregularities in a variety of settings, we create a composite, red-flag financial statement measure to estimate the degree of financial reporting irregularities for a given firm-year. The measure, which has several significant conceptual and statistical advantages over available alternatives, assesses the extent to which features of the distribution of a firm's financial statement numbers diverge from a theoretical distribution posited by Benford's Law, or the law of first digits. We find that whether in aggregate, by year, or by industry, the empirical distribution of the numbers in firms' financial reports generally conforms to the theoretical distribution specified by Benford's Law. In a battery of construct validity tests, we show that i) manipulating revenue for a typical conforming firm will induce an increase in the deviation from the theoretical distribution 87% of the time, ii) the divergence measure is positively associated with commonly used accruals-based earnings management proxies, yet is not associated with real activities earnings management proxies, iii) the restated financial reports of misstating firms exhibit greater conformity, and iv) divergence decreases in the years following restatements. Turning to the informational implications of Benford's Law, we provide evidence that as divergence increases, information asymmetry increases and earnings persistence decreases after the disclosure of the financial statements. Finally, we show that our measure predicts material misstatements as identified by SEC Accounting and Auditing Enforcement Releases (AAERs) and can be used as a leading indicator to identify misstatements.