Revisiting the Fraud Triangle in Corporate Frauds: Towards a Polygon of Elements
Bibliographic record
Abstract
The fraud triangle has long served as a fundamental model for understanding corporate fraud, emphasizing opportunity, pressure, and rationalization. Over time, this framework evolved with the fraud diamond, which introduced capability; the fraud pentagon, which added arrogance; and the fraud hexagon, which incorporated collusion and reshaped arrogance. Building on these developments, this study proposes a seventh dimension: the pleasure and thrill of risk-taking. This psychological factor highlights the gratification that some individuals derive from engaging in fraud as a high-stakes game. Through a qualitative analysis of five major corporate fraud cases—Société Générale, Enron, Wirecard, Parmalat, and Theranos—this study highlights the presence of this additional motivational factor. By introducing the fraud polygon, this research provides a more comprehensive framework for understanding corporate fraud’s multifaceted nature. This model has significant implications for both academic research and practical fraud prevention, offering insights into the interplay between systemic vulnerabilities and intrinsic motivations.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".