Bibliographic record
Abstract
Purpose The purpose of this paper is to show to the public in general and auditors in particular that the money deposited to the banks that operate in an uncontrolled medium can be misused by owners of the banks. Design/methodology/approach The paper has been designed based on a fraud theory. The theory has been developed on financial analysis and audit tests. The theory then revised and the existence of a bogus company and its intermediary role in the fraud scheme has been proven. Findings The paper explores that banks controlled by unreliable owners can lead to misuse of public's funds in accordance with the directives of the owner. Public's money can be transferred to other group companies in an illegal manner‐in excessive amounts and never returned to the bank by means of applying different accounting techniques. Practical implications Auditors, who may audit group companies that include a bank or banks with deposit receiving and lending rights should pay attention to the transactions between the group's bank and the other group companies. The lending may be excessive in amount and/or never paid back and various accounting malpractices may exist. Originality/value The case that the paper covers reflects the author's own audit experiences. The names of the companies have been changed but not the essence of the events. From this perspective it sheds light onto the path of an auditor who happens to be in a similar situation.
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.005 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".