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Total Number of Subscribers: 1626 |
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Date: 30th March 2010 |
Compiled by: M Sathya Kumar |
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Using CAATS in Preliminary
Analytical Review to Enhance the Auditor’s Risk Assessment Risk-assessment standards are requiring
businesses to adjust their audit approach to a risk-based methodology. This
can be a daunting challenge for auditors who have become accustomed to
traditional substantive audit approaches for small businesses. Developing a
basis for making a risk assessment becomes paramount to performing a
high-quality risk-based financial statement audit. The risk-assessment
standards require that auditors perform risk- assessment procedures during
planning, such as a preliminary analytical review and obtaining an
understanding of the entity and its internal controls. Computer-assisted
audit techniques and tools (CAATT) can play a role in enhancing the effectiveness
and efficiency of risk-assessment procedures. The key to effectively and
efficiently leveraging software applications when assessing risk is to use
the software to improve the quality of the audit evidence that forms the
basis of the auditor’s judgments about the financial statement risk. Using Business Analytics Software Traditional CAATTs have largely been the
realm of data-extraction software that allows an auditor to efficiently
manages large sets of data and effectively stratify it for testing. These
CAATTs are primarily used in performing substantive tests, performing tests
of details, and responding to specific risks. Business analytics software,
however, can play a significant role in the audit engagement when it is used
to assist the auditor in performing the preliminary analytical reviews in the
risk-assessment process. Comprehensive analytics can provide one of
the best sources of audit evidence to support an auditor’s risk
assessment. Ultimately, the result of the risk-assessment process will drive
the overall audit approach, so effective risk-assessment procedures are the
foundation for a high-quality financial statement audit. Effective analytics
will not only help identify audit areas that present higher risks, they can
also be the basis for assessing certain audit assertions as lower risk. The availability of business analytics
software tools has grown over the past several years. ProfitCents, iLumen,
and ProSystem fx Profit Driver are examples of business analytics software
tools. The features, pricing, and support for these different applications
can vary widely. “Tools for Financial Analysis: Boost Your Consulting
Practice to a Higher Level,” by James Estes, Richard S. Savich and Maya
Ivanova, in the November 2007 Journal of Accountancy, included a survey of
business analytics tools and is a good starting point for potential buyers. Comprehensive analytics typically include
developing expectations from multiple sources to help identify unusual or
unexpected relationships. These expectations may include period-on-period
variance analysis, regression analysis, ratio analysis, industry comparisons,
as well as budget-to-actual and other predictive tests. A good analytics
software tool should make it easy for an auditor to develop these
expectations by automating the calculations and comparisons so that the
auditor can focus on evaluating the relationships. These analytics are used
for identifying both inherent and control risks in the engagement. For
example, if a company’s actual sales are significantly greater than the
calculated trend and its gross margin percentage exceeds the typical industry
range, then an auditor would likely identify these as flags for an inherent
revenue- recognition risk, such as a bill-and-hold scheme, and as a risk of
ineffective internal controls over cutoff procedures. Most of the analytical review techniques
that auditors can apply during the planning stage are simple when compared to
the more-complex procedures performed when using data extraction and analysis
software. With data-extraction software, the objective of the analysis is to
parse volumes of data to identify records that meet specific criteria, such
as stratification of accounts-receivable aging balances, and transactions
meeting certain authorization thresholds. When applying CAATTs to preliminary
analytics, however, we are looking for relationships that can be expressed as
a simple ratio or a quantifiable trend. These relationships, although
expressed in simple terms, can still be quite complex, depending upon how
pervasive the relationship is within the financial statements or in relation
to other key metrics. Following are examples of the types of
preliminary analytical review procedures that auditors can apply using
business analytics software:
The last point above merits further
discussion, because a regression analysis can be a powerful tool in
understanding what factors drive a business. The goal of this type of
procedure is to perform a one-year forecast on the financial statements using
a sales growth–driven model. This allows the financial statements to be
prepared pro forma based on actual sales growth trends. Sales growth tends to
be one of the most pervasive drivers in most companies’ financial
statements, so this approach can highlight various relationships that may not
be present in the financial statements but should be. This is similar in some respects to the
concept of a “virtual” year-end close. The projection is used to
estimate what the balances would be under the trend assumptions, and creates
a baseline for making comparisons and judgments of the business’s
actual performance. Business analytics software provides a tool
that can automate the type of procedure described above. It is initially used
to develop an auditor’s expectations. Software can greatly enhance this
process by removing much of the subjectivity and bias that can be introduced
when performing a financial analysis. It can also take the complexity out of
the statistical calculations used in performing a trend analysis. Auditors
can save time on engagements by using software to automate the calculation of
historical trends, using statistical methods such as regression analysis.
Historical trend analysis provides an objective baseline for identifying
which financial statement line items warrant further investigation. Analytic
software can then be used to supplement the trend analysis with comparisons
to industry data from online databases to further support the preliminary
analytical review. Finally, budget expectations or other calculated
predictive tests, such as interest expense from an amortization schedule, can
be factored in and compared to the trend analysis and industry data. All of
these analytics can be brought together in one worksheet, providing an
auditor with a comprehensive analysis, resulting in a higher level of
confidence when relying on preliminary analytical review to support the risk
assessment. Limitations to Analytics The simplicity of many analytical review
procedures is both the greatest strength and the greatest weakness of such
approaches. The underlying assumptions in many of these procedures lend
themselves to some degree of generality, so at some point subjectivity and
professional judgment must enter into the analysis. The quality of any
analysis will be directly affected by the initial inputs. For many small
businesses, if significant audit adjustments are needed to adjust year-end financial
statements, then many relationships developed during preliminary analysis may
have little bearing except to reemphasize the necessity to adjust those
balances. Auditors must also be wary of the inherent limitations
of making comparisons to industry data. By their nature, most industry data
are subject to issues of timeliness, comparability (relevance to a specific
company), and a high degree of estimation (depending upon which accounting
methods, useful lives, and so forth, are selected by industry peers). Even
considering these limitations, industry data provide a context in which an
auditor can gauge a company’s financial performance. It is to be
expected that any company will have variances from industry trends. The value
of the comparison is in identifying those variances and understanding their
underlying causes. Business analytics software can also go
beyond the numbers, assisting an auditor in obtaining a deeper understanding
of a company and its environment. For financial statement analysis to be
effective, an auditor must be able to interpret multiple financial statement
relationships simultaneously. This can be challenging and time-consuming,
and, in many cases, it results in a financial analysis that consists only of
prior-year and current-year comparisons. Business analytics software aids the
auditor by providing multivariate financial analysis that can help an auditor
identify relationships between changes in financial ratios and multiple line items
in the financial statements. This can assist an auditor in seeing how changes
in liquidity, profitability, sales growth, and debt levels affect other
aspects of the financial statements. Once armed with this knowledge, an
auditor can better identify associated risks. A multivariate analysis
generated by business analytics software can also pinpoint areas where an
auditor must make further inquiries of management in order to gain an
understanding of the underlying transactions that resulted in the variance or
relationship. This ensures that the auditors are not only asking the required
questions but also asking the right questions. Based on this analysis, an
auditor can also better gauge management’s responses and possibly
corroborate those responses. It is widely believed that the new
risk-based approach will raise the cost of audit engagements due to an
increased emphasis on internal controls and the associated testing of those
controls. For that reason, it is important that auditors identify areas where
they can leverage software tools to assist in performing audit procedures to
enhance the efficiency and effectiveness of the audit. Effectiveness can come
from more-comprehensive analytics and multivariate financial analysis.
Efficiency is gained by automating the calculations and comparisons that go
into financial statement analysis. When used properly, business analytics
software tools can meet all of these requirements. Article
by Alex Vuchnich, CPA, CFE, is the manager of enterprise accounting
markets for Sageworks, Inc., the developer of ProfitCents |
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