Bibliographic record
Abstract
Purpose The purpose of this paper is to formulate and propose a fraud investigation plan that forensic accountants can use to investigate financial frauds. In particular, the paper sets out the structure and rationale of the fraud investigation plan that both forensic accountants and fraud examiners can use in their investigation of false accounting and theft charges. Design/methodology/approach The paper uses the material facts from the Polly Peck International fraud as a prototype case upon which to build an investigation plan and detail potential areas of investigation to establish evidence for a criminal trial. Findings The findings revealed that the case can be used to provide insights on evidence gathering techniques and test particular models of fraud detection. The concealment and conversion evidence gathering techniques provide fodder on how to gather and triangulate both direct and circumstantial evidence that can be used to avoid mistrials in courts. Practical implications The case is of interest to practitioners and forensic and fraud examination students who would like to build on their existing knowledge and obtain insights into the steps to follow to conduct an investigation and gather evidence to build a case. The paper makes specific recommendations to enhance the effectiveness and efficiency of investigations. Originality/value The paper is among one of the few to propose a fraud investigation plan designed to investigate cases involving false accounting and theft charges. More importantly, the paper uses a real case to illustrate how to examine documentation/data and how such documentation will be analysed in a trial.
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 | 0.001 | 0.005 |
| 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 | 0.001 |
| 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".