By Jen Stretch. Quality and data accuracy is everything when dealing with financial disclosures. The pressure of looming deadlines can sometimes lead to compromised quality for some public companies, but it doesn’t have to. In this blog, Jen Stretch, manager of compliance services at Certent, provides guidance around proper quality control procedures and critical quality reviews.
Quality Control Procedures: Not all quality and completeness checks can be completed automatically; therefore, a significant amount of time should be invested in manual review processes – the most important review being an XBRL proof. This is a process in which the XBRL rendering is checked for completeness and accuracy. Every value in the financial statements and footnotes to the financial statements should be included in the XBRL rendering where it is then reviewed for appropriate label, calendar, member (if applicable), scale, and decimals attribute. Once the value has been reviewed it is checked off of the source document. It is usually best to have a peer conduct the XBRL review in order to validate the work. The XBRL proof should be conducted once the document is approximately 90% complete and no later than a few days prior to filing.
Other quality reviews are based on some of the more common XBRL errors such as invalid axis/member combinations and negative instance document values. The following are additional reviews that should be conducted for each filing.
Taxonomy Structure Review: With invalid axis/member combinations being one of the most common XBRL errors reported by XBRL US, this review should be conducted for every filing after taxonomy changes have been finalized. The process consists of reviewing the hypercube table, axis/member combinations, and line item abstract for each taxonomy presentation group for appropriateness. For more on this error visit my earlier blog 4 Most Common XBRL Errors: Part One.
Negative Instance Document Value Review: This review also addresses a very common XBRL error and should be conducted for every filing. The steps to this review include filtering the instance document values to identify all negative values and reviewing each one for appropriateness. Some elements are meant to have negative instance document values, but most are not and can be reported incorrectly when they do. For example, an incorrect negative value could cause investors or analysts to misinterpret the data since it is inconsistent with the balance type and definition of the concept. For more information on preventing and identifying negative value errors, visit my blog, Four Most Common XBRL Errors: Part Two.