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Avoiding the pitfalls of analytical procedures

Sageworks
July 28, 2015
Read Time: 0 min

By definition, analytical procedures is a process of
analytically detecting ways to decrease time and increase efficiency. This
process can appear daunting at times because of the numerous comparisons of
financial information that must be made when working on a client’s statements.
The overall goal for an auditor is to identify unusual or unexpected balances as
well as areas of discrepancy that could jeopardize the financial health
of a client.

While performing analytical procedures auditors can fall
into two different types of error:

  • Poor time management: Not approving financially sound
    information or spending too much time mulling over correct statements
  • Exposed liability: Approving financially incorrect
    information due to the pressure of deadlines, which then exposes the firm to
    liability

Auditors are metaphorical adventurers traveling into
sometimes unchartered financial territory. On either side of the path are
different types of obstacles, waiting should they slip too far in one direction
or the other. To combat these threats, auditors have identified ways to avoid
these pitfalls and produce consistent and timely audits. Additionally, an
auditor should identify his or her personal tendencies toward conservative or
liberal pre-audit planning and adjust accordingly. In this post we will look at methods that auditors can use to avoid these errors.

  • Using thresholds that are common to the company and industry
    is one of the most generally used tools when investigating audits. One study reportedly
    shows that the most widely used decision rule in planning an audit was to
    investigate if the account balance had changed by more than 10 percent from the
    previous year.

    Having working knowledge and benchmarks
    of how most businesses in the industry are performing will increase your
    ability to identify areas of concern. Additionally, compiling a pool of
    common-size financial statements can eliminate time spent researching from outside
    sources.

  • After identifying deviations from set thresholds, the next
    step for assessing risk is identifying those within the business being audited
    that can provide insight about the discrepancy. Here an accountant’s knowledge of
    and relationship with the organization can come into play by helping to
    identify who should be contacted and how to work with difficult individuals
    within the company.

    Clearly communicating the risks and seriousness of the discrepancy
    to the appropriate individuals should lead to timely and adequate answers.
    Knowing how to explain the discrepancy to the firm’s decision makers in an easy-to-understand
    language
    is a strength in and of itself. Navigating communication about
    discrepancies with clarity and precision will allow you to return to audit
    processes.

  • Narrowing the risks to assess can also be done by performing
    reviews of cash flow forecasting or other procedures to determine the movement
    of capital within the company. Having additional procedures like these in place
    can help to identify which balances are materially misstated and those that are
    correct. Recognizing when financials prove an initial suspicion incorrect can
    redirect you to the pressing risks facing a client.

Developing these steps can help standardize the road map
your firm uses to navigate pre-auditing hazards. Redirecting your tendency to
over-analyze or under-analyze will produce timely and accurate audits that will
grow your business and prevent the approval of misstated financials.

For more information, download a Guide to Audit & Review Best Practices and Pain Points

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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