The dark side of blockholder control: evidence from financial statement fraud cases
Bibliographic record
Abstract
Purpose The purpose of this study is to investigate whether large blockholders are associated with financial statement fraud at their companies. Although a substantial body of prior studies has focused on chief executive officers’ motivations to manipulate financial statements, the correlation between majority shareholders and financial statement fraud has received little attention. This paper aims to fill this gap by investigating whether the sample firms have controlling shareholders or executives (i.e. blockholders vs management) and whether financial statement fraud schemes, motivations and consequences differ between blockholder- and management-controlled firms. Design/methodology/approach Using a clinical approach, the authors Study 12 Canadian financial statement fraud cases uncovered by the Ontario Securities Commission between 1997 and 2020. Findings First, the authors find blockholder control in six cases. These findings infer that these large shareholders received private benefits at the expense of minority shareholders. The comparative analyzes suggest that fraudulent firms controlled by blockholders go bankrupt more often than those controlled by managers. The authors also find that improper disclosure is the most common fraud scheme in blockholder-controlled firms. Originality/value The authors conduct a deep analysis of financial statement fraud cases to examine the of blockholder control on the likelihood of financial statement fraud. This paper adds new insights to the research on financial crime by investigating whether large shareholders affect the probability of fraud and the extent to which they might do so.
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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 | 0.001 | 0.042 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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".