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Standardizing analytical procedures to bolster audit compliance, efficiency

Sageworks
May 6, 2015
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By Michael Sferratore, Vice President of ProfitCents

 

One of the unintended consequences of auditing changes in the wake of accounting scandals since Enron and WorldCom is that some investors and regulators have come to believe that accounting can be an exact discipline – where objective practitioners uncover “the truth” by simply following prescribed steps that leave little room for subjectivity.
The problem with that view is that the best accounting and auditing still require plenty of professional judgment and estimation. Accounting is not a science but is instead, a discipline that gives financial information a structure that makes sense. Certainly, most times that structure and discipline works, yielding what it is intended to yield – a true and fair view of a company’s financial condition and confidence in the accuracy of the financial statements.
Even so, there are many judgment calls to be made throughout an audit, including deciding which analytical procedures to perform and which pieces of data among the mountains of data provided are the most important and most vulnerable to misrepresentation. Indeed, professional skepticism is a fundamental component of the audit process, and it requires critical assessments combined with accounting and auditing expertise. The best auditors are those who combine a thorough knowledge of auditing, financial statements and industry acumen with an ability to apply common sense and judgment to the process of an audit or review.
Time for qualitative review 
Applying common sense and judgment, however, takes time. If auditors are spending much of their time on the “routine” aspects of an audit (planning the audit engagement, calculating expected values and reporting), they could be left with little if any time for reviewing and analyzing data so that they can provide a broader and more global picture and analysis of the business. In addition, the more efficient and organized auditors are early in the process, the more able they may be to reduce the time required for the overall engagement, thus creating more opportunities to boost revenue from other clients.
Technology can standardize and speed up certain aspects of the audit process to leave the accountant more time to focus on aspects requiring thoughtful judgment and to make the entire engagement more efficient. For example, technology makes possible a quicker and more reliable method for calculating and documenting expected values in cases where auditors are either using both trend (two periods of data) or regression analysis (three or more periods of data). Applying automated mathematical models to this part of analytical procedures standardizes this process and can speed it up so the accountant has time to concentrate on values that are out of line and on the overall condition of the company being audited or reviewed. A standardized process that is well documented also makes this aspect of the audit more transparent. 

Download a Guide to Audit & Review Best Practices and Pain Points

In other words, a reduction in the time it takes to calculate the rote statistical part of the process will allow for more time and research into other components that can make the difference between a good audit/review and a bad one. For example, more time can be devoted to interviewing management to understand how financial and economic conditions are changing the company. Or time can be used for performing industry research or evaluating trends.

Of course, using good statistical modeling does not eliminate the need for high-quality analysis of the data and for considering other methods to determine expected values. This is where the process becomes more “art” and less “science.” It’s important to provide time for these qualitative aspects, and audit technologies that incorporate industry best practices while helping to automate some of the more routine tasks can help do this.
Find more information here on how to standardize analytical procedures for audits and reviews of for-profit, nonprofit and government organizations, and for financial institutions.
About the Author

Sageworks

Raleigh, N.C.-based Sageworks, a leading provider of lending, credit risk, and portfolio risk software that enables banks and credit unions to efficiently grow and improve the borrower experience, was founded in 1998. Using its platform, Sageworks analyzed over 11.5 million loans, aggregated the corresponding loan data, and created the largest

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