XBRL Data Quality Committee’s validation rules decrease errors 64% in Q1 2016 SEC filings

The XBRL US Data Quality Committee (Vintage is a founding member, BTW!) announced that corporate filers reduced the number of errors in their XBRL filings (for the data covered by the Committee published rules) by 64 percent in Q1 2016 as compared to Q1 2015.

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To view results of the analysis: https://xbrl.us/data-quality/dqc-results/

“We’re very enthused by the results measured from the first full quarter of rule implementation,” said founding committee member Chase Bongirno, Senior Manager – XBRL, Vintage. “We’ve worked diligently with our clients to guide them, both tactically and conceptually, concerning the trickle-up importance of accuracy. There’s no broad adoption of the XBRL data without quality,” finished Chase. “Accuracy is not optional.”

The XBRL US Data Quality Committee rules are freely available and can be accessed on the XBRL US website or directly from Vintage’s XBRL team. 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 in a PDF document.

FROM XBRL US ANNOUNCEMENT

“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, Professor of Finance, Vanderbilt University, and former SEC Chief Economist.

The Data Quality Committee will publish a second release of guidance and validation rules for public comment shortly.

To access the rules: https://xbrl.us/data-quality/rules-guidance.

The XBRL US Center for Data Quality provides funding for the Data Quality Committee. In addition to Vintage’s founding-member status, members of the Center include our partners Certent and DataTracks.

Our XBRL team, lead by Chase, has always had a wonderfully stubborn, inflexibility towards quality. The “flex” in our successful fleXBRL program refers to which XBRL tag and review process best matches your reporting workflow!

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