Views on improving the integrity of global capital markets
22 June 2021

For The EU: Lessons To Be Learned About Digital Filings

Posted In: EU, US SEC, XBRL

Globally, regulations requiring public companies to provide information in an XBRL (eXtensible Business Reporting Language) for­mat have steadily increased. But XBRL implementation has faced some challenges, particularly in the United States.

The quality of the information provided in the XBRL reports is one such challenge.

The XBRL taxonomy associated with US GAAP has many thousands of data elements from which a company may select. This volume, however, has led companies to tag similar items differently. In addition to inconsistent tagging, other data quality issues that affect the automated analysis of XBRL data include scaling errors (the wrong number of zeros, billions instead of millions) and input errors (e.g., incorrectly using negative values).

Chief among the data quality challenges is the unnecessary use of customized extensions.  If you extend the core dictionary of fields (i.e., the taxonomy) excessively, the XBRL platform loses the vitally important benefit of comparability of information across companies.

Indeed, in the United States, some users report that approximately 70% of data elements can be directly mapped onto the US GAAP taxonomy and 30% are extensions.

Such excessive use of extensions results in the need for manual intervention by users. Analysis of extensions must be manually executed, whereas analysis of a taxonomy element can be automated across companies.

What caused these implementation issues?

One of the problems was that when XBRL was first implemented, guidance for companies was insufficient. Another issue has been insufficient regulatory enforcement. Currently, companies, especially in the United States, do not face any real consequences if they submit poor quality data. Any mistakes in the XBRL financials need to be picked up by regulators and addressed through proper enforcement mechanisms. This effort would go a long way toward improving data quality.

We see some data quality issues, including extensions and scaling errors, in the new European Single Electronic format filings. I would urge the EU to learn from these mistakes made in the United States and ensure that they are not repeated.

What else would improve data quality? Audit of the XBRL filings.

The US Securities and Exchange Commission and the European Securities and Markets Authority have mandated the use of Inline XBRL filings. This mandate raises questions about the audit of these filings.

An inline filing has two layers of information. Currently, only the human-readable layer of information needs to be audited, but not the machine-readable layer. Investors, however, are using this digital information to make investment decisions. So, investors expect both layers of the filing to be audited.

A significant consequence of an audit is that it would motivate companies to start paying attention to their XBRL tagging and to do it the right way. A second benefit of an audit is that the improved quality of the data would decrease the pain and effort of consumers of the XBRL data to “fix” the data before using it. According to a 2016 survey of CFA Institute members, 77% of respondents want some level of assurance over the XBRL report. 

To sum up, policy makers should focus on the following:

  • Improve the quality of the data by using enforcement mechanisms.
  • Curtail the use of customized extensions.
  • Support auditor involvement to provide assurance on the structured data.

Finally, sustainability disclosures are becoming increasingly important to investors. These should be required to be reported in a structured format.

Photo credit @ Getty Images / Donald Iain Smith

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About the Author(s)
Mohini Singh, ACA

Mohini Singh is director of financial reporting policy at CFA Institute. She represents membership interests regarding financial reporting and disclosure proposals issued by the FASB, the IASB, and others. Singh holds the Associate Chartered Accountant (ACA) designation.

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