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How to detect manipulation in financial statements

On Behalf of | Apr 7, 2021 | Corporate Litigation

When you’re evaluating businesses in New York with the intent of choosing one to invest in, you need to know that financial statement manipulation sometimes occurs. Because accounting standards are flexible, financial statement manipulation is often difficult to catch.

Signs of financial statement manipulation

Watch out for increasing revenues that don’t come with increasing cash flows. If almost all of the company’s competitors are struggling, but it has steady sales growth, this could indicate manipulation.

Compare the company’s depreciation against others in the industry. If the numbers deviate significantly, this may be financial statement fraud. Some companies give themselves a boost in the last quarter. An unusual surge during the last quarter may indicate dishonesty in reporting the numbers.

Not all cases of financial statement manipulation involve inflating numbers. Companies sometimes worsen the numbers to ward off acquirers or to appear stronger in the future by adding in the subtracted stats.

Lawsuits over financial manipulation

Fudging the numbers on financial statements is a violation of the law. If you have good reason to believe a business has lied about any of its numbers, you could potentially file a lawsuit to seek compensation for your financial losses that resulted.

Vertical and horizontal analysis

You could use vertical and horizontal analyses to detect financial statement manipulation. To conduct vertical analysis, you convert each item on the income statement into a percentage of revenue and compare it to previous years’ numbers. You can use vertical analysis on a balance sheet too with the total assets as your benchmark. Horizontal analysis works in a similar way as vertical analysis but uses financial data as a percentage of the base years’ numbers.

Beneish model

Another method of detecting financial statement manipulation is the Beneish model, which involves evaluating eight ratios to determine how likely it is the numbers are false. An M-score greater than -2.22 is a red flag under this method.