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

2004· article· en· W926593226 sur OpenAlexaboutno aff
Joseph T. Wells

Notice bibliographique

RevueJournal of accountancy online/Journal of accountancy · 2004
Typearticle
Langueen
DomaineComputer Science
ThématiqueDiverse Research and Applications
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésAccounts receivableAuditCashSales journalBusinessPaymentSavings accountAccountingLiberian dollarFinanceActuarial scienceEconomicsMarketingSales management
DOInon disponible

Résumé

récupéré en direct d'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. …

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,003
score de la tête « metaresearch » (Gemma)0,014
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Autre · Signal consensuel: aucune
Score de désaccord entre enseignants0,045
Score d'incertitude au seuil0,114

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0030,014
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0010,001
Études des sciences et des technologies0,0210,006
Communication savante0,0140,007
Science ouverte0,0010,005
Intégrité de la recherche0,0050,010
Charge utile insuffisante (le modèle a refusé de juger)0,0340,012

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,016
Tête enseignante GPT0,291
Écart entre enseignants0,275 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreAutre

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2004
Routes d'admission1
Résumé présentoui

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