How has the quality of XBRL filings improved? What areas still need attention?
To mark the tenth anniversary of the SEC implementing its XBRL-tagging requirement for financial disclosure filings,
Dimensions asked six XBRL experts in the securities regulation, financial reporting, or capital markets sectors to comment on the structured-data revolution in SEC reporting. In Part 1 (see the June/July 2019 issue of Dimensions), the experts commented on whether the XBRL requirement has been a success, how the use of structured data has evolved over the past ten years, and what challenges remain for issuers in preparing SEC filings. Here in Part 2, we cover quality issues, Inline XBRL, and future developments.
In today's blog, we will focus on quality issues.
• Mike Willis, Assistant Director, SEC Office of Structured Disclosure
• J. Louis Matherne, Chief of Taxonomy Development, FASB
• Campbell Pryde, President and CEO, XBRL US
• Christine Tan, Co-Founder and Chief Research Officer, idaciti
• Pranav Ghai, CEO, Calcbench
• Lou Rohman, Vice President of XBRL Services, Toppan Merrill
NOTE: The views expressed here are solely those of the individual respondents, and they do not necessarily reflect the views of their respective organizations.
Question: How has the quality of XBRL filings improved? What areas still need attention?
Mike Willis, SEC: There are several factors contributing to quality improvements. First is filer awareness of the growing use of XBRL data, not only by the SEC, with integration into EDGAR itself, but also by data providers in the marketplace. This increasing use should help to focus filer attention on the sources of potential error. Further, with the increasing use, filer management should understand that they are personally liable for structured-disclosure errors in the same manner that they are liable for their traditionally reported disclosures. As a result, appropriate process controls and oversight are critical to their structured-disclosure reporting risk assessments.
Second is an awareness of validation and quality rules that can be applied to the structured disclosures. The machine readability of the structured disclosures offers a huge benefit in the application of automated data-quality assessments. The data-quality rules freely provided by the XBRL US Data Quality Committee should be a filer priority consideration.
Third is the awareness that not all error types are covered by the current data-quality rules and that subjective tagging consideration may be outside of the scope of automated detection.
In short, reporting judgment remains a critical matter for filer attention, and filers can benefit from a growing body of formal and informal guidance, methods, tools, and understanding among accountants and analysts. Where this understanding remains weak, it is most commonly reflected in structured-data errors such as:
• Inappropriate extensions (e.g., creating an extension for a very common disclosure that has a standard element in the taxonomy)
• Incorrect element selection (e.g., tagging revenue disclosures with the discount rate tag)
• Disclosures not tagged (e.g., numeric values in the notes are not tagged)
• Using deprecated elements (e.g., use of “old” revenue tags despite the “new” tags available under a current revenue-accounting standards)
• Calculation relationships incorrect or missing (e.g., an asset component is not included in the calculation relationship for total assets)
• Scaling errors (e.g., reporting in billions in HTML and millions in XBRL)
• Context errors (e.g., inconsistent reporting periods, such as a third-quarter Form 10-Q with a fiscal-year-end date)
The existence of tag selection and usage errors may be an indicator that management is not sufficiently invested in the review and assessment of their structured-disclosure reporting processes.
For more on other common error types, staff observations, and staff guidance, please visit www.sec.gov/structureddata/osdstaffobsandguide.
Christine Tan, idaciti: The quality of the filings has improved. Some areas still require attention. Companies often switch tags from filing to filing but should really conduct a cost-benefit analysis of switching tags. The consequence of
tag-switching is that it truncates the time series of a given line item.
Pranav Ghai, Calcbench: Extensions need attention.
Campbell Pryde, XBRL US: While data quality can always be improved, we have made a lot of progress, certainly since the program first launched in 2009. And quality began an even steeper upward trajectory in 2015, when the Data Quality Committee began publishing guidance and automated rules for issuers. One of the biggest areas of concern from the start was the use of negative signs on facts that should have been reported as positive. That error category alone has declined significantly, along with many other error types.
One of the biggest challenges we are seeing right now is for IFRS filers who are working with the IFRS Taxonomy for the first time. When a taxonomy is first used, often unexpected issues arise that need to be worked out. The more a taxonomy is used, the more quickly it matures and improves. To help move this process along, we have been developing validation rules for IFRS filers, in addition to the ones for US GAAP filers.
The good news is that we have learned so much from the US GAAP program that we can pinpoint the kind of rules which will quickly help foreign private issuers get on the right track, much faster than with US GAAP. For US GAAP
filers, the areas that still need improvements are disclosures in the notes to the financials, to ensure consistency across filings.
J. Louis Matherne, FASB: Report quality improves every quarter in large measure through the collaborative efforts of market participants with the XBRL US Data Quality Committee. The FASB also participates in these efforts,
listening to and leveraging the market’s desire for data-quality improvements that can result in taxonomy improvements for identified issues. Additionally, the Data Quality Committee publishes validation checks that effectively enforce the guidance the FASB publishes in the Taxonomy Implementation Guides and Taxonomy Implementation Notes in the Taxonomy. All of this has resulted in primary financial statements that are measurably better. Disclosures, however, will be the next big challenge, as attention shifts from improving the statements
to improving the notes. Disclosures are inherently more complex, and we know there are data-quality issues here to be addressed.
Lou Rohman, Toppan Merrill: The most significant improvement to XBRL quality has come from automated rules produced by the Data Quality Committee—a consortium of companies led by XBRL US. Registrants can run these rules free of charge prior to submitting XBRL, to identify and correct errors in the XBRL tagging. Tens of thousands of errors have been corrected due to these rules. However, many errors remain that cannot be caught by automated rules, and those are the areas that still require attention from registrants.
Overall, the quality of XBRL tagging is still not where it needs to be. The SEC has not imposed direct consequences for improper XBRL; as a result, despite the legal liability of submitting XBRL that communicates erroneous financial
information, XBRL quality has not been a focus for some registrants.
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