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Best practices for documenting analytical procedures

August 4, 2016
Read Time: 0 min

By Lana Richards, Contributing Writer, Sageworks

Documenting audit and review procedures often feels more like administrative than value-adding work. And some procedures—like analytics, for example—require more extensive documentation due to the amount of judgment applied in their selection, design and evaluation. While it can be quite tempting to skimp on documentation, doing so can further delay the audit process when work papers don’t pass internal reviews. Further, if those deficiencies slide past internal reviewers, they may get flagged in peer reviews. Applying some best practices for analytical procedures documentation can boost compliance and give auditors more time to focus on aspects of the audit process that require their critical-thinking skills.


Analytical procedures, defined

Analytical procedures are defined in the professional standards as studies of plausible relationships among both financial and nonfinancial data. They can involve a wide range of methods, from simple comparisons to the use of complex statistical models. The types of data used, the analysis of the relationships being evaluated and the conclusions reached all require auditor judgment.

Used in the planning, testing and review/reporting phases, analytical procedures boost audit efficiency because they typically take less time than detailed tests of transactions. They also boost audit effectiveness. By forcing auditors to look at client-reported data from different angles and think critically about underlying factors, analytical procedures help auditors better understand their clients’ businesses.

Examples of analytical procedures include comparing financial information to:

• Similar information from prior periods

• Anticipated results (e.g., client-prepared budgets or auditor-prepared expectations)

• Industry averages or other similar industry data

• Non-financial information (e.g., property square footage or number of employees)


Documentation requirements

For analytical procedures, auditors must clearly document:

• Expectations and how they were developed

• Evidence obtained

• Results and conclusions

• Additional audit procedures performed in response to significant differences

• Who performed the work and when

While these documentation requirements may seem obvious, in practice, complying with them is not always straightforward. Workload demands are the biggest impediment to producing compliant, effective documentation. When pressed for time, auditors may fail to document in sufficient detail the work they performed and the judgment they applied to reach their conclusions, leading to incomplete work papers, lengthy internal reviews and potentially deficiencies noted during peer reviews.


Documentation best practices

The following best practices can help audit teams improve efficiency, compliance and the value of their deliverables.

o Be clear and concise. To promote efficiency in both the internal and peer review processes, be as concise—but thorough—as possible, and make sure tick marks and other notations are logical. This will also be helpful for future audits potentially involving different staff.

o Document in a timely manner. Unnecessary time lapses between performance and documentation can cause auditors to forget how they developed an expectation, why they performed a calculation or why they reached a particular conclusion. Continually update work papers as new evidence is obtained and evaluated, and try to clear open items as quickly as possible.

o Review. Make sure documentation is complete (see requirements noted above per the professional standards) and error-free and clearly conveys and backs up the significant findings to avoid calling audit evidence into question during reviews. Also be sure to double-check cross-referencing among work papers.

o Integrate software. To promote efficiency, effectiveness, and compliance of analytical procedures documentation, consider using software that integrates with audit programs and work papers. Technology offers several advantages:

— Technology can often calculate expected values and perform analyses quicker, as well as standardize documentation of results and methodologies. This information can be added to audit files with a click of a button, thereby improving efficiency and reducing the likelihood of erroneous or incomplete documentation.

— By automating a chunk of the documentation the auditor once had to do manually (explaining complex calculations, identifying trends and anomalies and even producing basic narrative analyses), software frees up the auditor to focus on the aspects that can’t be automated because they require thought and professional judgment.

— The critical evaluation of evidence involved in analytical procedures also makes them prime for use beyond compliance. Data analytics packages, for example, help auditors obtain a more comprehensive understanding of their clients’ businesses, and the documentation of those procedures can be used in post-audit reviews and presentations. To that end, software can help portray financial results to clients more clearly and in a more interesting way—making the audit more decision-useful.

Using software to perform and document analytical procedures and being mindful of the other best practices noted above will help auditors assure compliance with professional standards and retain more time for the “critical thinking” aspects of their work. After all, that is where auditors can truly add value for their clients, as they uncover insights that can help management bolster financial performance. 

Find more information here on how to automate and standardize documentation for analytical procedures used in audits and reviews of for-profit, nonprofit and government organizations, and for financial institutions


Lana Richards, a contributing writer for Sageworks, is a writer, editor and content marketing strategist for professional services firms. She is a former accountant and has a master’s degree in accounting.

About the Author


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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