Financial statement fraud

Financial statement fraud is the deliberate misstatement or omission of amounts or disclosures in financial statements in order to deceive users. It is the least common category of occupational fraud and by far the most costly per case, because it distorts the decisions of investors, lenders, suppliers and employees on a large scale and is usually committed by people at the top of the organization who can override controls. This lesson explains why and how financial statements are manipulated, the analytical signals that point to manipulation, and what several well-known cases teach. ACCT-331 covered the auditor's responsibilities for fraud risk in an audit; here the perspective is that of the investigator called in when manipulation is suspected.

Why statements are manipulated

The motives are usually about meeting expectations. Public companies face pressure to meet analysts' forecasts and guidance, because missing them can cut the share price sharply. Private companies face pressure from lenders' covenants, which may require minimum earnings or maximum leverage, and from owners who plan to sell or raise capital. Managers face pressure from bonuses and share-based compensation tied to revenue, earnings or share price. Some manipulation aims to understate results instead, to smooth earnings by building reserves in good years, to reduce taxes, or to depress the value of a business before a management buyout or a divorce settlement. Whatever the motive, financial statement fraud almost always involves senior people, because it requires authority over journal entries, estimates and disclosures, and often the cooperation or silence of others.

Common methods

Revenue is the most frequently manipulated area in enforcement cases in both countries, because it is the largest number in most income statements and because the judgments involved, about when control or risks and rewards pass to the customer, create room for abuse. Timing schemes are especially common: the sale is real, but it is recorded in the wrong period, often by shipping goods early, giving customers terms that make the sale reversible, or recording goods that the customer has not taken. Side letters, which are agreements outside the main contract that change its terms, are a classic device because the accounting department and the auditors never see them.

The revenue allegation at Saltmarsh Industrial Supply Ltd.

The first hotline report said that fourth-quarter shipments to two distributors were made with side letters allowing returns. Corbett Lane Forensic LLP obtains the shipping records, invoices and contracts for the last three weeks of 2025, interviews warehouse staff and, with counsel's authorization, searches the email accounts of the sales team. It finds that between December 15 and December 31, 2025, Saltmarsh Industrial Supply Ltd. shipped 2.4 million dollars of goods to two distributors, Ridgeback Industrial Distributors and Cormorant Supply Partners, about four times the normal volume for those customers. Signed letters from C. Varga, the vice-president of sales, gave each distributor the unconditional right to return any unsold goods within 120 days and deferred payment until the goods were resold. In February and March 2026, the distributors returned 1.9 million dollars of the goods.

Saltmarsh Industrial Supply Ltd. reports under Accounting Standards for Private Enterprises (ASPE). Section 3400 recognizes revenue from the sale of goods when the seller has transferred the significant risks and rewards of ownership, the amount can be measured reliably and collection is reasonably assured. With an unconditional right of return and payment due only on resale, the distributors had not taken on the risks of ownership; the arrangements were in substance consignments, and revenue should not have been recognized at shipment. The letters were not given to the accounting department or to the auditors.

The effect is significant: removing the 2.4 million dollars from fiscal 2025 reduces reported revenue from 91.2 million to 88.8 million and pre-tax income by about 610 thousand, the gross margin on the goods. The investigators also find a motive. Varga's annual bonus plan paid a large award if revenue exceeded 90 million, and the company's bank covenant required a minimum ratio of earnings before interest, taxes, depreciation and amortization to debt service. The analysis does not, by itself, show that Varga intended to deceive; that will depend on the documents, the interviews and, ultimately, the trier of fact. But the side letters, their concealment and the incentive together form the kind of pattern that boards, auditors and regulators treat seriously.

Analytical signals and the Beneish M-score

Long before an investigator sees a side letter, the financial statements themselves may show signs of manipulation. Horizontal analysis (changes over time) and vertical analysis (proportions within a year) show unusual movements. Ratios such as days sales outstanding, gross margin, inventory turnover and the relationship between net income and operating cash flow are sensitive to common schemes. Fictitious or premature revenue tends to raise receivables relative to sales; capitalizing expenses tends to raise assets and lower expense ratios; and most manipulations push accrual-based earnings away from cash flow.

Researchers have combined such signals into scoring models. The best known is the M-score developed by Messod Beneish and published in 1999, which uses eight indexes calculated from two years of financial statements, weighted by coefficients estimated from companies that were later found to have manipulated earnings. A score above about −1.78 (some users apply −2.22 with a five-variable version) suggests a higher likelihood of manipulation. The F-score of Patricia Dechow and colleagues, published in 2011, uses a different set of accrual, performance and market variables. Lesson 10 discusses Benford's law and other tests on transaction data, building on ACCT-341. The program below calculates the M-score for Saltmarsh Industrial Supply Ltd. from its fiscal 2024 and 2025 statements as originally reported.

# Beneish M-score for Saltmarsh Industrial Supply, FY2025 against FY2024 (invented statements, thousands).
# The eight-variable model of Beneish (1999); scores above about -1.78 suggest a higher likelihood of
# earnings manipulation. It is a screening tool: a high score calls for inquiry, not a conclusion.
y0 = dict(rev=84600, cogs=61760, rec=10150, ca=31400, ppe=14200, ta=52800, dep=1420,
          sga=15230, cl=13900, ltd=9600, ni=3180, cfo=3600)
y1 = dict(rev=91200, cogs=67950, rec=15480, ca=37900, ppe=14050, ta=59700, dep=1350,
          sga=15950, cl=16800, ltd=10400, ni=4420, cfo=1050)

def gm(y): return (y["rev"] - y["cogs"]) / y["rev"]
def aq(y): return 1 - (y["ca"] + y["ppe"]) / y["ta"]
def deprate(y): return y["dep"] / (y["dep"] + y["ppe"])
def lev(y): return (y["cl"] + y["ltd"]) / y["ta"]

idx = {
    "DSRI": (y1["rec"] / y1["rev"]) / (y0["rec"] / y0["rev"]),
    "GMI":  gm(y0) / gm(y1),
    "AQI":  aq(y1) / aq(y0),
    "SGI":  y1["rev"] / y0["rev"],
    "DEPI": deprate(y0) / deprate(y1),
    "SGAI": (y1["sga"] / y1["rev"]) / (y0["sga"] / y0["rev"]),
    "LVGI": lev(y1) / lev(y0),
    "TATA": (y1["ni"] - y1["cfo"]) / y1["ta"],
}
coef = {"DSRI": 0.920, "GMI": 0.528, "AQI": 0.404, "SGI": 0.892, "DEPI": 0.115,
        "SGAI": -0.172, "LVGI": -0.327, "TATA": 4.679}
m = -4.84 + sum(coef[k] * v for k, v in idx.items())
for k, v in idx.items():
    print(f"{k:<5}{v:>8.3f}   contribution {coef[k] * v:>7.3f}")
print(f"\nM-score: {m:.2f}   (screening threshold about -1.78)")
print(f"Days sales outstanding: {y0['rec'] / y0['rev'] * 365:.0f} days in FY2024, {y1['rec'] / y1['rev'] * 365:.0f} days in FY2025")
print(f"Net income {y1['ni']:,} vs operating cash flow {y1['cfo']:,}: accruals of {y1['ni'] - y1['cfo']:,}")

DSRI    1.415   contribution   1.302
GMI     1.059   contribution   0.559
AQI     0.952   contribution   0.385
SGI     1.078   contribution   0.962
DEPI    1.037   contribution   0.119
SGAI    0.971   contribution  -0.167
LVGI    1.024   contribution  -0.335
TATA    0.056   contribution   0.264

M-score: -1.75   (screening threshold about -1.78)
Days sales outstanding: 44 days in FY2024, 62 days in FY2025
Net income 4,420 vs operating cash flow 1,050: accruals of 3,370

Saltmarsh Industrial Supply Ltd.'s score of −1.75 sits just above the −1.78 threshold. The largest single driver is the days sales in receivables index of 1.415: receivables grew much faster than sales, from 44 days of sales to 62, which is what the 2.4 million dollars of unpaid year-end shipments would produce. The other strong signal is the gap between net income of 4.42 million and operating cash flow of 1.05 million. Neither proves manipulation; receivables can rise because of a new large customer or slower collections, and the M-score is a screening tool with many false positives. But a lender, auditor or board seeing these numbers would have had good reason to ask questions, and the investigator uses them to confirm where to look.

Lessons from well-known cases

Famous cases are useful because they have been documented by courts, regulators and investigators. They should be described carefully, using the findings of those bodies and the dates on which they were made.