The XBRL US Data Quality Committee has released an analysis showing big improvements in the quality of filings in Extensible Business Reporting Language format by companies that follow a new set of validation rules.
The SEC began phasing in requirements for companies to use XBRL, a data-tagging technology, for their financial filings in 2009, as a way to help investors and financial analysts compare financials across companies and industries. However, the quality of the filings has long been a problem, making it difficult for analysts to use the technology. Still, the SEC has been able to make some use of XBRL to look for outlying data that could be a sign of accounting problems (see SEC Looking More Closely at XBRL Filings). XBRL US, an industry consortium that helps develop XBRL technology, has a Data Quality Committee that has been producing documents to provide guidance and validation rules to be used for improving the quality of SEC filings.
A new analysis by the XBRL US Data Quality Committee shows that errors for filers who used its first set of validation rules reduced errors by 64 percent in the first quarter of 2016 compared to the first quarter of 2015. The error count for accelerated filers (that is, large companies with equity securities valued at more than $5 billion) declined by 70 percent, while the error count for smaller reporting companies declined by 60 percent.
The Data Quality Committee’s validation rules—which enabled validation of more than 1.9 million data points in the first quarter of 2016—are designed to help public companies detect inconsistencies or errors in their XBRL-formatted financial data. The rules identify potential errors (such as incorrect negative values, improper value relationships between elements and incorrect dates) that obstruct automated processing and analysis of the data. The DQC approved the rules in November 2015 after a 60-day public review, and they became effective Jan. 1, 2016.
“The early success of the DQC’s validation rules in reducing errors is the first step in its mission to improve the usability of XBRL data,” said DQC chairman Mike Starr in a statement. “We expect that as more registrants use these rules, we will see a further decrease in the number of errors in the data covered by the DQC’s rules.”
The DQC intends to publish a second release of guidance and validation rules for public comment next week. In addition, the DQC plans to issue for public comment a discussion document later in June that will be the first of a series on a proposed framework for element selection and extension use.
“We’re pleased that we now have clear evidence that filers are actively embracing the new data quality rules. Greater consistency and quality in XBRL-formatted financials significantly improves investor access to financial data,” said Craig Lewis, a professor of finance at Vanderbilt University and a former SEC chief economist.
“Compliance with the proposed framework would improve the element-selection process, constrain the use of extensions and eliminate unnecessary extensions,” said Starr. “The use of unnecessary extensions has been one of the major reasons that data aggregators and investors have not moved from manual to automated processing and analysis of XBRL data.”
The rules are available for free and can be accessed on the XBRL US web site or through certain XBRL service providers. When the rules identify a potential error, they provide detailed information on the potential error with guidance on how to correct it. In addition, an explanation of each rule’s function is available on the XBRL US website in a downloadable PDF file. Software providers can have their implementation of the rules approved by the XBRL US Center for Data Quality. To view results of the analysis, visit https://xbrl.us/data-quality/dqc-results/. To access the rules, go to https://xbrl.us/data-quality/rules-guidance.
The XBRL US Center for Data Quality provides funding for the Data Quality Committee. Members of the Center include Altova, the American Institute of CPAs, Certent, DataTracks, DisclosureNet, Merrill Corporation, P3 Data Systems, Vintage, a division of PR Newswire, and Workiva.
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