In previous articles, we looked at cases of asset misappropriation and corruption. This month I will examine the third type of fraud—fraudulent financial statements. These are the fraud cases that are highly publicized (think Enron and Madoff!).  I’ll discuss some data analytics tests that auditors can use to discover suspicious activity in financial statements.

The fraud scheme that occurred at a subsidiary of Celadon Group, formerly one of the ten largest trucking companies in North America, provides a strong argument for applying data analytics. Executives from both Celadon and the subsidiary, Quality Companies LLC (Quality), overstated assets and concealed impairment losses.

In 2016, Quality was unable to lease a significant number of its used trucks, and management was faced with the problem of over-inflated inventory. Recognition of these impairment losses would have decreased Celadon’s 2016 pre-tax income by two-thirds!

Management’s solution was to create a series of transactions with a third party. Quality sold their aging inventory to a third party who then sold newer, but still used, trucks to Celadon. Both sides of the sale used inflated invoice amounts. Celadon represented these activities as fair value transactions.

The third party also loaned Celadon several million dollars in a clandestine agreement, which Celadon used to pay bank debt before the close of the third quarter of 2016. This transaction violated loan covenants with Celadon’s bank, but Celadon was able to avoid showing losses on its income statement as well as to present a strong financial condition to its investors. After the end of the quarter, Celadon repaid the loan.

Data analytics tools could have revealed several red flags to investigate. Ratio analysis (involving inventory—inventory turnover, days in inventory, inventory to sales), coupled with other tools (horizontal and vertical analyses), as well as analyzing the economic conditions of the industry could have identified the red flag of rapidly growing inventory in spite of the economic downturn in the trucking industry. Additionally, benchmarking with competitors’ information could have revealed Quality was adding to inventory while competitors were streamlining their inventories. Examination and investigation of large or unique/unusual transactions (the inventory trade with the third party; the large loan from the same third party) could have alerted auditors to the fraudulent nature of these transactions sooner, minimizing losses to investors.

In the Celadon case, the auditors accidentally discovered the fraud (confirming the ACFE’s contention that most frauds are discovered by accident or by tips). However, their discovery of the fraud did not occur until after Celadon’s third and fourth quarter 2016 financial statements had been transmitted to the SEC (U.S. v. Meek & Peavler, 2019).

SEC (2019) SEC charges truckload freight company with accounting fraud. Litigation Release No. 24459. Retrieved April 19, 2021 from https://www.sec.gov/litigation/litreleases/2019/lr24459.htm

U. S. v. Meek, W. E. and Peavler, B. L. (2019). Case Number 1:19-cr-00378, U. S. District Court, Southern District of Indiana, Indianapolis Division.

Cynthia Waddell, PhD, CPA, CFE

cwaddell@purdueglobal.edu