Predicting Risk of and Motives behind Fraud in Financial Statements of Jordanian Industrial Firms Using Hexagon Theory
Bibliographic record
Abstract
This study intends to identify the motives that lead to increasing or fighting the fraud risk in the Financial Statements (FSs) of industrial companies whose shares are traded in regulated and unregulated markets at the Amman Stock Exchange (ASE) based on the Hexagon theory, which divides the motives for fraud into six factors. The study relied on secondary data to collect and measure the study variables by extracting them from the annual reports that were published by those companies on the website of the ASE during the period of 2012–2017. The collected data were analyzed using the logistic regression model on the SPSS program. The results confirmed that the return on assets (ROA), percentage of independent members in audit committees, and tone-related party transactions had a statistically significant relationship with predicted fraudulent FSs, where these three variables belong to pressure, opportunity, and collusion fraud motives, respectively. Thus, it is worth mentioning that this study is distinguished from previous studies that examined the issue of fraud in Jordanian companies by detecting the motives of fraud according to the Fraud Hexagon theory. Moreover, some of the fraud motives were measured using new variables such as a change in inventory, the age of auditing committee’s members, and tone-related party transactions.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".