We develop the concept of auditor industry range as the extent to which an auditor has experiences in auditing clients from different industries, and we link this construct to auditor performance, drawing on prior research in psychology and cognitive science. We find that auditors with a wide range of industry experiences are more likely to require audit adjustments than auditors with a narrow range. We conduct an extensive set of analyses to mitigate the concern that our results are driven by endogenous matching between auditors and clients. The positive relation between auditor industry range and audit adjustments exists regardless of whether the industries covered by an auditor's portfolio exhibit strong or weak economic co-movement, and the relation is stronger for more complex clients, in more uncertain environments, and for auditors with more years of audit experience. Overall, our findings suggest that an auditor's diverse experiences in different industries can enhance audit quality.

In contrast to prior research that typically focuses on the characteristics of the audit committee (AC), we investigate how intergroup differences between the AC and the rest of the board (ROB) affect monitoring effectiveness. Drawing on group literature and the similarity attraction paradigm, we hypothesize that high intergroup differences between the AC and the ROB impede communication and information sharing. Poor “fit” between the AC and the ROB can lead to an “us versus them” mentality that reduces trust and hinders knowledge exchange, diminishing monitoring effectiveness. Using a sample of listed US firms, we find that intergroup differences between the AC and the ROB in terms of their respective characteristics are linked to a lower likelihood of reporting an existing or likely material weakness, higher discretionary accruals, and a lower likelihood of a going‐concern opinion among financially distressed firms. These negative effects are most pronounced when the AC and the ROB are very different (i.e., in the upper quartile and decile of the AC‐ROB distance distribution). Additional analyses show a higher probability of a Big R restatement, a lower likelihood of a Big R restatement when a material misstatement likely exists, and a lower likelihood of goodwill impairment when one is expected. Notably, the adverse impact of AC‐ROB dissimilarity is more prominent when the AC is less powerful or lacks group stability. Regulators and companies should be aware that AC composition decisions cannot be made in isolation because large intergroup differences in director profiles between the AC and the ROB reduce monitoring effectiveness.