This study examines audit partners' predictions of the ability of managers and seniors to detect financial statement errors. If partners are unable to predict the ability of their subordinates to detect errors, audit effectiveness may be affected. Audit partners are asked to predict which members of the audit team (managers or seniors) are able to detect specific types of errors. These predictions are then compared to errors detected by managers and seniors that are seeded in working papers. The results show that partners (1) exhibit significant overconfidence in the ability of subordinates to detect errors, (2) are more accurate in predicting managers' performance than seniors, (3) are more accurate at predicting subordinates' ability to detect mechanical (simple) errors than conceptual (complex) errors, and (4) are not better at predicting subordinates' ability to detect more frequent and more important errors than less frequent and less important errors.

To improve audit effectiveness, public accounting firms have organized their practices to include hierarchical review by teams organized along industry lines. We examine how industry specialized auditor teams detect errors, using a sophisticated experimental design. Our analysis of nominal teams created from seniors and managers working individually shows that seniors add value to the team by detecting more mechanical errors while managers detect more conceptual errors. Working within specialization, managers and seniors both contribute in a nonredundant way to the team’s overall effectiveness. We also find that the nominal teams outperform real teams in the detection of mechanical but not conceptual errors. These results only hold when the auditors work within in their industry specialization. Out of specialization the auditors are not effective at detecting errors, and real teams perform below the nominal team benchmark in the detection of both mechanical and conceptual errors.

One hundred and fifty auditors participated in a study that examines whether auditors’ probabilistic judgments are closer to a Bayesian benchmark when auditors make judgments using a frequency response mode versus a probability response mode. We test a series of hypotheses that examine the effect of using a frequency response mode by professional auditors both within and outside their knowledge domain (fraud or medical case context) on assessing the likelihood of rare events. The results show that the auditors’ responses across the two case contexts (fraud and medical case) using a frequency response mode are closer to the Bayesian benchmark. In addition, we find that (1) the deviations in the auditors’ responses from the Bayesian benchmark across both response modes are significantly smaller for the fraud case in the low base rate condition only and (2) the deviations in the auditors’ responses from Bayesian benchmark for the fraud case using a frequency response mode relative to the probability response mode are smaller in the low base rate condition than the other two base rate conditions. These findings contribute to research on auditor judgment and decision-making, and demonstrate how the use of a frequency response mode can improve auditors’ assessment of fraud.