Sensitivity analysis in accounting
Financial statements and other financial information may include uncertainties. Impact of such uncertainties may be assessed using sensitivity analysis. In this article, we will describe the nature of sensitivity analysis and how it can be performed.
1. Financial statements involve judgment and uncertainties
Financial statements evolve some degree of professional judgment. Financial managers should make assumptions in a number of areas such as:
- Assessing the recoverable amount for a group of impaired loans;
- Calculating the value in use of fixed assets for impairment tests based on budgeted cash flows;
- Making an assessment of warranty provisions on the basis of past experience;
- Calculating an environmental provision;
- Valuating allowances for deferred tax assets based on future taxable income; and
- Determining what discount rate to apply for a goodwill impairment test.
If assumptions are driven by forecasts, results can fluctuate with the underlying risks and uncertainties. Risks are considered to show the quantitative characteristics (i.e., possible outcomes have associated probabilities), while uncertainties are seen as unquantifiable, therefore they could only be described narratively. Although two terms are used interchangeably in financial managements, the distinction between them is an important one.
As actual results could differ from estimates, sensitivity analysis informs financial statement users about the inherent uncertainties in measuring related assets, liabilities, revenue and expenses, and consequently explains uncertainties associated with financial statement items as of a reporting date.
Aside from external financial reporting, sensitivity analysis can be used for internal reporting. Would sales increase if we decrease the price of Product A? With the increased sales, if we can utilize economies of scale and reduce our unit cost, will we get the same gross margin per unit sold? These and other similar questions may be answered with the assistance of sensitivity analysis.