Before we dive into what Reasonableness Test is in audit, we must first understand what analytical procedures are. The analytical procedures are essentially a method for an auditor to analyze the available financial or non-financial data and identify certain trends, patterns, or relationships.
However, the results of such analysis are only useful when they are benchmarked against a set expectation. The auditor commonly uses analytical procedures to perform an analytical review or substantive analytical procedures.
Reasonableness Test is a type of analytical procedure. To further elaborate on Reasonableness Test, let us use the audit of rental expense as an example. We will first analyze the financial information recorded in the financial statements, the rental expense, and the non-financial information, which is available in the rental agreement.
The analysis formed in this case is that the rental expense recorded was a product of the rental paid per month and tenure stated in the rental agreement. Our pre-set expectation would be the relationship between these two pieces of information.
How to apply Reasonableness Test
Let go into more details on how to apply the Reasonableness Test in Audit properly. The first and the most important step in applying the Reasonableness Test is setting a precise and objective expectation.
This is because analyses made will be irrelevant or inaccurate if the expectation set is wrong from the start. Expectation can be a financial ratio, a trend you expect the financials to behave, or a relationship between two different accounts.
An example would be expecting the revenue to increase year on year as, through inquiry, it has been noticed that the entity has secured new customers during the accounting period. Another example is expecting the entity to record a significantly lower payroll cost as the entity has reduced its employee headcount.
After setting an expectation, the next step in applying the Reasonableness Test is to set an objective threshold where any deviation from this threshold requires further audit investigation.
Usually, such threshold is the materiality set early in the audit, but other types of the threshold may be applied depending on the audit risk we are addressing. A threshold is needed as a guideline in deciding whether the deviation of the Reasonableness Test result from the set expectation has an impact on the audit.
After an expectation and threshold are set, the auditor has to identify the difference between the result from the analysis and the set expectation, investigate the differences and draw a conclusion. Let us further elaborate based on the example above on payroll cost.
Let’s say the threshold set is $100,000. The auditor’s expectation is the same, where he expects the payroll cost to reduce, specifically by 30% or $1,200,000 based on the information provided by the client.
The payroll cost has decreased by $1,150,000. In this case, the auditor may decide not to investigate further and conclude that the analysis is reasonable as the difference has not exceeded the $100,000 ($1,200,000 – $1,150,000 = $50,000).
Another scenario would be the payroll cost has only dropped by $800,000. Given the deviation has exceeded the threshold of $100,000 ($1,200,000 – $800,000 = $400,000), the auditor will need to investigate further.
After investigating, the auditor found out that an employee who resigned was not removed from the payroll system, resulting in the payroll cost for such employee being recorded in the current accounting period. This will then allow the auditor to conclude that an error has occurred, and an audit adjustment will be required.
Key factors affecting the precision of the Reasonableness Test
Although Reasonableness Test greatly assists an auditor in performing an analytical review or substantive analytical procedures, he must always consider the level of reliance placed on the result of the Reasonableness Test to support the audit conclusion.
The key factors affecting the precision of the Reasonableness Test are as follows:
1) Disaggregation level
The auditor can achieve disaggregation level from a set of data that was applied to the Reasonableness Test. The higher the disaggregation level, the greater the precision level. Disaggregation essentially means how detailed the data can be further broken down.
To illustrate, having a set of revenue data showing only a one-year trend does little to support our Reasonableness Test. However, if we can disaggregate the revenue data to a shorter period, for example, by customer or by quarter, this will help support a more precise Reasonableness Test.
2) Data reliability
With higher reliability, the Reasonableness Test will be more precise. Reliability refers to the source of the data and the subjectivity of the data to manipulation. If the data used in the Reasonableness Test is externally sourced, the reliability will be higher as such data are generally more objective. A strong internal control can also indicate that the management cannot easily manipulate the data making the data much more reliable.
Lastly, we have predictability. The more predictable a certain trend or relationship is, the more precise the Reasonableness Test is. Predictability is crucial if the auditor cannot reasonably predict how a set of data or financials will behave as he will not be able to form any audit conclusion using the Reasonableness Test.
An example is that an entity’s year-on-year revenue fluctuation is affected by many factors such as competition, economic factors, and changes in the customer spending trend. In such a situation, the auditor cannot pinpoint exactly which factor has caused the fluctuation in the revenue.
Reasonableness Test can greatly assist the auditor by reducing his workload to check supporting documents. It also provides stronger audit evidence than just checking supporting documents for a few selected samples.
This is especially the case for entities with a high volume of transactions. However, as an auditor, we need to always remind ourselves of the level of reliance we intend to place on the Reasonableness Test, as a higher reliance level requires a similar level of precision.