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Using
CAATTs in Preliminary Analytical Review to Enhance the Auditor’s
Risk Assessment
By
Alex Vuchnich
MAY 2008 - 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:
- A comparison
on a common-size basis of a company’s asset mix to that
of its industry peers to identify heightened risks, such as
inventory obsolescence and uncollectible accounts.
- A comparison
of common-size financial statements from one period to the next
and from one company to industry peers, in order to identify
trends in the debt-to-equity structure that may indicate an
eroding capital base or a heightened risk of insolvency.
- A period-on-period
trend analysis applied to various expense lines to identify
patterns, such as special events held on a biannual basis or
surges in sales at the quarter- or year-end.
- A regression
analysis to project the current-year expected values for financial
account balances, based on historical trends that can be compared
to the actual balances.
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 (see the Exhibit),
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.
Alex
Vuchnich, CPA, CFE, is the manager of enterprise accounting
markets for Sageworks, Inc., the developer of ProfitCents (www.profitcents.com).
He can be reached at alex.vuchnich@sageworksinc.com.
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