The Influence of Audit Risk and Materiality Guidelines on Auditors’ Planning Materiality Assessment
Bibliographic record
Abstract
At present, methods to improve auditquality and auditing decisions are being debated by standard setters andresearchers worldwide. Materiality has been and continues to be a topic ofimportance for auditors.Audit quality is primarilyinfluenced by two factors: the requirements of standard setters and theprofessional judgment of auditors. Materiality judgment is primarily determinedby the subjective judgment of the auditor because there is a lack of clear, standardizedguidelines for such judgments. Thus, the same materiality issue could be judgeddifferently by different auditors. Auditors’ materiality judgments areimportant because they significantly influence what information is recorded inthe accounts, disclosed in financial statements and made available to externalparties for decision-making. The objective of this study is to examine theinfluence that audit risk and quantitative guidelines have on the assessment ofplanning materiality and on the adjustment of material misstatements. We use acase study and conduct an experiment. The study results provide evidence thatthe standardization and implementation of quantitative materiality guidelinesresult in a smaller range of planning materiality judgments. This paperdiscusses the implications of those findings.
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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 | 0.009 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".