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Record W926593226

The Quarter-Million-Dollar Caper: A Fraudster Is Nipped in the Bud

2004· article· en· W926593226 on OpenAlex
Joseph T. Wells

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of accountancy online/Journal of accountancy · 2004
Typearticle
Languageen
FieldComputer Science
TopicDiverse Research and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsAccounts receivableAuditCashSales journalBusinessPaymentSavings accountAccountingLiberian dollarFinanceActuarial scienceEconomicsMarketingSales management
DOInot available

Abstract

fetched live from OpenAlex

Let's face it--conducting a routine audit of a good, stable client can be boring and repetitive. Every year seems much like the last: tracing and vouching, reconciling, ticking and footing, examining documents and ledgers, evaluating controls. But despite the humdrum, good auditors are always on the lookout for abnormalities. The following case study reveals how alert auditors uncovered a fraud and, by behaving with professional integrity, turned a potentially bad situation into a positive one. THIS DOESN'T COMPUTE An auditor for a Canadian firm in Westmont, Quebec, was performing an audit procedure at a client's business when she came across something that made no sense. involved comparing the aged accounts-receivable list with the current month's sales. Except for normal reconciling items such as cash sales, freight and insurance charges, the amount sold should equal that month's charges to accounts receivable. (Total sales for month + sales taxes + freight charges) - (Cash sales + payments on current accounts receivable during month + sales returns and allowances) = Current accounts receivable When she found the total reflected on current accounts receivable was higher than sales by nearly $250,000, she called the audit partner, Philip C. Levi, CPA, of Levi Katz, Montreal, who talked to us about his handling of the investigation. Levi, an experienced certified fraud examiner, quickly discovered entries that alerted him to a possible problem: charge-backs on two different delinquent customer accounts. The net effect of the two entries was to simultaneously debit and credit the accounts-receivable subsidiary ledgers, which removed the customer charges from the 90-day aging column and reinstated the amounts as current. That was the reason why there was a $250,000 discrepancy. DEVELOPING A FRAUD THEORY Levi was concerned. Why, he wondered, would the client be motivated to restate these two delinquent accounts as current? The business, an importer and distributor, was a closely held family enterprise. Using generally accepted fraud examination techniques, Levi applied the fraud theory approach to see whether he could solve the mystery. One possibility was that the charges in question were uncollectable. But he quickly discarded that theory; the amounts had been subsequently paid in full. Next, Levi reasoned that since the business was not public and the amounts involved did not affect profits or taxes, the overstatement of current receivables might have been done to satisfy the collateral requirements of a lender. Levi examined the client's bank loan documentation. Sure enough, the line of credit was limited to 80% of the company's receivables that were less than 90 days old. Had the accounts-receivable aging been stated correctly, the company probably would have been pressured by the bank to come up with money to correct the default. The client's cash position reflected that it did not have the funds to pay down the loan. A 1999 COSO study of 200 financial statement fraud cases found that the CEO and/or CFO were involved at least 83% of the time. In this case the charge-backs were actually made by a clerical employee, Levi said. However, it made sense the clerk was acting on orders from upper management. Because the CEO was on vacation at the time of the charge-backs, I theorized that Tim, the CFO, was the one who had authorized the transactions. The clerk confirmed this. When the CEO returned to the office, Levi interviewed him to determine whether he had any involvement in the scheme. It was clear he was shocked at what the CFO had done, Levi said. CONFRONTING THE SUSPECT Before interviewing the CFO, Levi consulted the client's legal representative to ensure both the company and he were on solid footing to avoid any exposure to legal action by the CFO. Experienced in fraud examination and interviewing techniques, Levi made sure he would violate no individual rights. …

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.193
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0010.003
Open science0.0050.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.016
GPT teacher head0.291
Teacher spread0.275 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it