A helping hand: using software to improve analytical procedures in audits & reviews.

One of the larger fallouts from the accounting scandals of the past several years is that the investing public has begun to believe that accounting and auditing can be an exact discipline. They can't be.

Because accounting and auditing require the use of judgment and accounting estimates, the most effective auditors are those who exercise professional skepticism and good judgment, gather sufficient and competent audit evidence, and assess that evidence adequately.

Of course, the quality of an audit can be found in the quality of an auditor's judgment. So, how can auditors adopt technology in their analytical procedures to make more time available for the softer and more difficult task of improving their judgment decisions?

WADING THROUGH DATA

One of the largest challenges that CPAs and auditors have is the amount of data they must work with, which can sometimes make it difficult to decide between the important and the unimportant. It is also difficult to recognize trends. In essence, there is a distinct difference between accounting and auditing and financial analysis, yet both are pivotal to the analytical process.

There are so many transactions that make the auditor's job challenging, especially in cases of fraud or near fraud where the client has every incentive to muddy the records. How can the profession deal with this?

Recent legislative and regulatory rulings give the appearance that the profession is dealing with problems. However, whether or not these reforms get to the heart of the real challenge--which is to minimize or make easy the technical or rote parts of an audit and allow more time for the judgment components--is another matter.

However, if the technical parts of an audit can be made easier through technology, then more time can be devoted to the qualitative parts. If auditors are spending so much time on the rote parts of an audit, such as calculating expected values, then little, if any, time is left for a broader analysis of the business.

Statement on Auditing Standards No. 99, which establishes standards and provides guidance on planning and performing an audit, requires the auditor to consider "the results of analytical procedures performed in planning the audit."

Using technology in performing analytical procedures will likely result in a more efficient process, but it's only one aspect of evidence-gathering. SAS 99 requires that the results of those analytical procedures "be considered along with other information gathered by the auditor in identifying the risks of material misstatement due to fraud." SAS 99 is available at www.aicpa.org/download/members/div/auditstd/AU-00316.pdf.

TECHNOLOGY STEPS IN

There are certain aspects to the estimation process that can be made more efficient through technology. One of these is setting expected values in the analytical procedures portion of an audit or review.

"Expected values" are the account values that might be anticipated, based on the past performance of a company. Setting expected values takes time and effort and some knowledge of statistics.

Why is this important? By identifying what general ledger account values should be, auditors can apply a "management by exception" basis for looking into values or accounts that are out of line with what they should or might be.

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Rather, if auditors have to pour through all income statement and balance sheet accounts with equal energy, it increases the chance of missing larger problems. While it is true that setting expected values can never be perfect, the methods of deriving values can be improved through the application of technologies.

Until recently, the task of deriving expected values has been time consuming. For example, say you were attempting to derive an expected value for sales/revenue for the following company:

 Example 1

YEAR  SALES/REVENUE

2002      $10M

2003      $20M

2004      $40M

2005        ?

What might an expected value or estimated value be for 2005? Many methods might be applied to determine the answer, but logically, it looks like an expected value for 2005 sales might be approximately $80 million. This is derived by recognizing that the sales trend in question seems to be increasing by approximately 100 percent each year.

The calculation to derive the trend from 2003 to 2004, would be $40 million (sales in 2004) less $20 million (sales in 2003)/$20 million (sales in 2003). The data in this example would be compelling as a starting point because it is clear and does not really deviate, and there is a clear trend that can be applied to 2005.

In other words, in looking at data like this to set values, you would tend to weigh the clear financial trend less than the externalities of the firm (the market or industry).

But other situations may not be as clear. Take Example 2.

 Example 2

YEAR  SALES/REVENUE

2002      $10M

2003      $20M

2004      $30M

2005        ?

The expected value for sales in this case is less clear because sales are increasing at a reduced rate, at least for the years being evaluated, as compared with Example 1.

How about Example 3:

 Example 3

YEAR  SALES/REVENUE

2002      $10M

2003      $10M

2004      $20M

2005        ?

Again, it would seem logical that the expected value of the company's sales would increase, but the calculation would be more difficult, given the uneven data.

Where a simple trend analysis might be a good starting point for Example 1, it seems like a different mathematical technique, such as regression analysis, might be more appropriate for Examples 2 and 3. Even though regression analysis cannot be a perfect solution for all parts of the process, it is a good methodology as a starting point for auditors.

Regression analysis is cryptic and time consuming, especially if it is applied to all accounts. For example, while it is possible and probable that you might apply regression analysis to a particular set of company data, think of how time consuming it would be to perform calculations manually against all accounts.

Technology makes possible a quicker and more reliable method for calculating expected values in cases where auditors are either using both trend (two periods of data) or regression analysis (three or more periods of data). Mathematical models can be easily applied to this part of analytical procedures to give CPAs time to look at overall conditions and values out of line, rather than having to devote time to rote calculation.

If setting expected values is achieved more quickly, how will this help increase the work done in analytical procedures? Using good statistical modeling does not eliminate the need for high quality analysis of the data and other methods to determine expected values. This is where the process of determining expected values becomes more art and less science.

We want to minimize the science by automating the calculations and increase the amount of time available for qualitative review and judgments.

A reduction in the time it takes to calculate the statistical rote part of the process will allow for more time and research into the following components that can make the difference between a good audit and a bad one:

Interviewing management. Understanding how financial and economic conditions are changing in the company.

Performing industry research. The company's financial performance is driven both by internal factors (good management, good products and services, etc) and external factors (industry changes, employment, industry averages/benchmarks).

Evaluating trends and looking more deeply at accounts that are unusual.

CONCLUSION

There are several software applications that speed up the process of setting expected values. Many auditors also create their own analytical frameworks using Excel. Macros can be developed that use statistical models that are generally accepted (An example would be the "times squared" calculation in regression techniques).

The idea is to have a set of algorithms that automatically calculate expected values using historical values as a basis.

There are several specific advantages to using technology to set expected values to ensure better analytical procedures, which will lead to better reviews and audits:

1. Calculations are quicker and more reliable. On balance, less chance for error is introduced through automation.

2. Data that is rough or uneven can be predicted with more accuracy.

3. More time can be devoted by auditors to reviewing data and less time to calculating it. As such, auditors can delve more deeply into accounts that are material and possibly more troublesome.

Integral to getting better audit practices is helping auditors with their day-to-day challenges. Using software and technology to reduce the time needed in analytical procedures will give CPAs time to devote to the full scope of an audit and review.

Brian Hamilton is CEO of ProfitCents, a web-based software program. You can reach him at [e-mail].