Improving the Quality of XBRL
Recently, we've written a few articles about what the SEC should be doing to make XBRL practical for investors and other stakeholders.1 Based on our experience with the SEC's XBRL program and feedback from those attempting to use XBRL data, we concluded that in order for XBRL to realize its full potential, the staff should:
- Require revision of filings to correct tagging errors and eliminate unnecessary extensions
- Integrate the use of structured data into its internal review process to increase efficiency and effectiveness
- Simplify the tagging of financial data using XBRL
- Determine the appropriate level of assurance on structured data for investors
- Transition the SEC's entire filing regime from document formats to structured data formats
These articles, Congress's interest in XBRL, and the SEC's Investor Advisory Committee seem to have sparked commentary from others using, or attempting to use, XBRL-formatted financial information.
From a data quality and government policy standpoint, Travis Korte, a research analyst at the Center for Data Innovation, echoed our call for the SEC to begin reviewing XBRL filings with the same level of scrutiny as the rest of the filing. This would eliminate document-format filings and expand structured data reporting to more filings. In his article "XBRL: How to Save a Good Idea from a Bad Implementation," he pointed out that,
Government agencies of all stripes should learn a lesson from the SEC's XBRL difficulties: an exclusive focus on releasing data overlooks other important data policy issues such quality and adoption of standards. Otherwise, it is just "garbage in, garbage out" and the good ideas behind better use of data in government may end up going to waste.
David Trainer, CEO of New Constructs, LLC, and a publisher of data and analysis for investors, agrees that automated data gathering allows for more sophisticated analysis by regulators, analysts, and investors, and he has a strong interest in using XBRL data in his work. However, in his attempts to use XBRL data, he has seen many basic errors, including incorrect shares outstanding, incorrect dates, and missing data. These errors have caused him to question the overall quality of the data and suspend further attempts to use the data until these quality issues are fixed.
In a recent Forbes article "XBRL Would Be Wonderful If It Always Worked," Trainer noted that, "Right now, enforcement is so lax that many companies with incorrect XBRL tags don't even realize they're making mistakes."
He goes on to say, "The potential utility of XBRL as a tool for regulators to fight fraud and investors to better analyze companies makes its numerous flaws that much more of a shame. I can only hope that the SEC realizes the value of XBRL and makes a commitment to ensuring the accuracy and validity of XBRL data."
This view is consistent with the findings of a Columbia Business School paper, "An Evaluation of the Current State and Future of XBRL and Interactive Data for Investors and Analysts," which found that investors and analysts have a deep interest in machine-readable data but are unwilling to change their current data gathering processes until XBRL quality issues are addressed.
However, like most complex issues, there is more than one side to the story.
A few analytical tool developers have started to use the existing XBRL data although they agree that there are errors, and sometimes serious errors or careless mistakes, in the data. They have been able to achieve some level of automation for error correction, allowing for more automation in data analysis.
These developers believe that improved automation processes, along with improving the as-filed data quality, will allow users to realize the full benefits of XBRL. In particular, they note that the customized analysis of individual companies is improved because of the granularity of the XBRL-tagged financial information. They also believe that one of the best ways to improve data quality is for companies to use XBRL data for their own benchmarking and peer analysis. This way, companies would quickly understand the impact of avoidable errors if they were using the data.
It's clear that demand for XBRL-formatted financial information is strong among investors and analysts, and that errors continue to hamper efforts to make real use of the data. We hope that the SEC will hear the stakeholders' call for the enforcement of XBRL filing quality and act accordingly.
1 See Dear SEC, Let's Correct the Errors in XBRL Filings and The State of SEC Reporting.
Harris, T. and Morsfield, S. (2012). An Evaluation of the Current State and Future of XBRL and Interactive Data for Investors and Analysts. [White paper]. Retrieved from The Columbia Business School Center for Excellence in Accounting and Security Analysis https://www8.gsb.columbia.edu/
"In response to Forbes article about XBRL errors." (2013). Calbench blog. Retrieved from http://www.calcbench.com/blog/in-response-to-forbes-article-about-xbrl-e...
Korte, T. (2013). "How to Save a Good Idea From a Bad Implementation." SmartData Collective. Retrieved from smartdatacollective.com/tkorte/165746/xbrl-how-save-good-idea-bad-implementation
Trainer, D., (2013). "XBRL Would Be Wonderful If It Always Worked." Forbes. Retrieved from http://www.forbes.com/sites/greatspeculations/2013/11/07/xbrl-would-be-w...
"XBRL does work. Here's how." (2013). Calcbench blog. Retrieved from http://www.calcbench.com/blog/xbrl-does-work-heres-how