Getting Comfortable on Audits: Understanding Firms’ Usage of Forensic Specialists
Bibliographic record
Abstract
ABSTRACT Increasing financial statement complexity along with an intense focus on audit quality has created challenges for today's auditors. As a result, audit firms are increasingly relying on various specialists to help them perform their audits. To better understand why and how audit firms are using forensic specialists on their audits, we conduct an exploratory survey of experienced audit and forensic professionals. Our results suggest auditors are largely relying on forensic specialists to provide them with additional comfort beyond that obtained from traditional audit procedures. Furthermore, our results demonstrate that the usage of forensic specialists occurs primarily on riskier engagements, such as those involving restatements, initial public offerings, and investigations by regulators or law enforcement agencies. Although their involvement varies, forensic specialists assist audit teams by providing both guidance and direct assistance across the audit in areas including fraud brainstorming, design of procedures to test for fraud, and review of results of fraud‐related testing. In addition, our findings indicate forensic specialist involvement may lead to greater comfort as evidenced by the perceived identification by forensic specialists of additional audit findings related to material misstatements, financial reporting fraud, misappropriation of assets, and internal control deficiencies. Our results also reveal the majority of auditor and forensic specialist participants believe the value of forensic involvement on audits outweighs the associated costs, even in the absence of such additional audit findings. We conclude our paper by offering a theoretical discussion of our findings based on the audit comfort framework and suggestions for future research. In summary, our findings suggest that the discomfort some auditors feel in the contemporary auditing environment is leading to changes in the rituals that underlie traditional audits such that they seek comfort afforded them through forensic specialist involvement.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".