Fraud Power Laws

• DOI: 10.1111/1475-679x.12520
• Publication Date: 2023-12-30T19:28:07Z
• Authors: EDWIGE CHEYNEL; DAVIDE CIANCIARUSO; FRANK S. ZHOU
• Keywords: Materiality; Punishment (psychology); Earnings Management

ABSTRACT Using misstatement data, we find that the distribution of detected fraud features a heavy tail. We propose theoretical mechanism explains such relatively high frequency extreme frauds. In our dynamic model, manager manipulates earnings for personal gain. A monitor uncertain quality can detect and punish manager. As fails to fraud, manager's posterior belief about monitor's effectiveness decreases. Over time, learning leads slippery slope, in which size frauds grows steeply, power law fraud. Empirical analyses corroborate slope channel. policy implication, establish higher detection intensity increase by enabling identify an ineffective more quickly. Further, nondetection below materiality threshold, paired with sufficiently steep punishment scheme, prevent large