Bibliographic record
Abstract
Analytical Procedures (APs) provide a means for auditors to evaluate the reasonableness of financial disclosures by comparing a clients reported performance to expectations gained through knowledge of the client based on past experience and developments within the company and its industry. Thus, APs are fundamentally different than other audit tests in taking a broader perspective of an entitys performance vis-a-vis its environment. As such, APs have been found to be a cost-effective means to detect misstatements, and many have argued that a number of prior financial frauds would have been detected had auditors employed effective APs. With several dramatic and far-reaching developments over the past decade, the current study examines whether and how APs have changed during this period. In particular, we focus on the impact of significant enablers and drivers of change such as technological advancements and the enactment of the Sarbanes-Oxley Act. We also compare our findings to an influential study of the practices of APs by Hirst and Koonce (1996) that was conducted over 10 years ago. We interview 36 auditors (11 seniors, 13 managers, and 12 partners) from all of the Big 4 firms using a structured questionnaire. The data reveal some similarities in findings when compared to prior research (e.g., auditors continue to use fairly simple analytical procedures). However, there are a number of significant differences reflecting changes in AP practices. For instance, as a result of technology auditors now rely more extensively on industry and analyst data than previously. Further, auditors report that they develop more precise quantitative expectations and use more nonfinancial information. They also appear to rely more on lower level audit staff to perform APs, conduct greater inquiry of non-accounting personnel, and are willing to reduce substantive testing to a greater extent as a result of APs conducted in the planning phase. Finally, the Sarbanes-Oxley Act has had an impact in greater consideration and knowledge of internal controls, which is seen as the most important factor driving the use and reliance on APs. © 2010 CAAA.
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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 | 0.010 | 0.081 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.000 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 0.002 |
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".