Financial Ratios in Fraud Analytics
Ratio analysis is a means of measuring the relationship between two different financial statement amounts. This form of financial statement analysis can be very useful in detecting red flags for a fraud examination.
As the financial ratios present a significant change from one year to the next, or over a period of years, it becomes obvious that there may a problem. As in all other analyses, specific changes are often explained by changes in the business operations. When a change in a specific ratio or several related ratios is detected, the appropriate source accounts should be researched and examined in detail to determine if fraud has occurred. For instance, a significant decrease in a company’s current ratio may point to an increase in current liabilities or a reduction in assets, both of which could be used to cover fraud. The analysis of ratios is limited by its inability to detect fraud on a smaller, immaterial scale.
These ratios may also reveal frauds other than accounting frauds. If an employee is embezzling from the company’s accounts, for instance, the amount of cash will decrease disproportionately and the current ratio will decline. Liability concealment will cause a more favourable ratio. In fact, these frauds may be more easily detected with ratio analysis because employees other than management would not have access to accounting cover-ups of non-accounting frauds. Anomalies in ratios could point directly to the existence of fraudulent actions.
The common financial ratios are:
• Cash ratio• Quick Ratio• Current Ratio• Working Capital to Total Assets• Debt to Equity• Debt to Fixed Assets• Inventory Turnover• Average Number of Days Inventory is in Stock• Account/Debtor Turnover• Account/Debtor Collection Period• Asset Turnover• Profit Margin
You can download the Excel template here. In the template you can also do vertical and horizontal analysis of financial statement.
Edit 1 – I have updated the template to also calculate Beneish M-Score. You can find my latest post here, Beneish M-Score: Identifying Financial Statement Manipulations.