XBRL Data quality has been a hot topic lately.

PwC, as a data-driven organization, has been a significant supporter of the structured data standard. They have been excited about the benefits of XBRL in providing timely and useful information to the capital markets to facilitate decision making.

I have seen the importance of XBRL and the positive impact it can have on the usefulness of business reporting through digitization and standardization. This globally important standard helps promote an information environment that can lead to better decision making. XBRL can also help management and auditors in promoting quality, credible information in the markets.
Wes Bricker, PwC Vice Chair and US and Mexico Assurance Leader, XBRL International Board Director

PWC recently published a white paper that discusses how a company’s XBRL data quality can help the company gain a competitive advantage. Importantly, the white paper suggests that companies that do not take ownership of their own XBRL data quality will cede messaging their narratives to investors and analysts. PwC is not alone; we have seen increased interest in the quality of XBRL from all stakeholders.

Regulators and standard setters are focusing on XBRL data quality.

The Financial Accounting Standards Board just this year incorporated some of the XBRL US Data Quality Committee Rules (DQC) in the release of the 2020 US GAAP Financial Reporting Taxonomy (“Taxonomy”) to encourage corporate filers to tag their financial statements with data quality in the forefront of their minds.  The motivation to embed the DQC rules into the Taxonomy was to elevate its presence and visibility.

in June 2020, the Securities and Exchange Commission published an analysis of company-specific tags (“extensions” or custom tags), noting that the creation of unnecessary extensions reduces the comparability of data across companies, and therefore limits the use of XBRL data for analyses.  S.P. Kothari, Chief Economist and Director, Division of Economic and Risk Analysis of the SEC, recently noted that “Structured data will likely drive future research in corporate finance and macroeconomics.”

XBRL US publishes the “Filing Results and Quality Checks” dashboard on its website for investors, analysts, peer companies, and the general public at large to view the DQC errors in public companies' filings.

Technology can help reduce effort significantly in checking the validity and consistency of filings.

While there is much recent attention on XBRL data quality, how does a company stay ahead of its own XBRL data quality while meeting the challenges of the current uncertain environment?

Here are some suggestions.

Demand your XBRL vendor provide integrated DQC checks in their platform

This will  ensure the errors are found and corrected before submission. And if you collaborate with consultants on XBRL filings,  make sure they fully understand the DQC rules and how to correct the issues.

Leverage the DQC validation rules checker, which is freely available.

The automated checks can quickly flag errors or issues in your filing which you can fix before submission to the SEC.

Minimize unnecessary extensions and maintain consistency in tagging.

Creating an extension means that your company cannot be compared to peer companies for analyses easily. Also, swapping out a standard US-GAAP element for an extension means that investors may not be able to  analyze your company’s historical trend.

For instance, one company, in its most recent 2020 Q2 filing, created an extension for “Airline Related Inventory, Aircraft Parts And Supplies, Net” to replace the standard element “us-gaap:AirlineRelatedInventoryNet” on its balance sheet. Investors and analysts will not be able to analyze its trend in airline-related inventory over time.

Previously, the company has used the standard element that was also used by its peer companies allowing for cross-company comparison over time.  Notice that the company's “Airline Related Inventory, Net” time-series is truncated at 2020 Q1 which means that from 2020 Q2 (and possibly onwards, unless corrected) it is no longer comparable to its peers for this particular line item because it has replaced the standard element with an extension.

Review large variances.

Sometimes, when companies are tagging their XBRL filings, they might make the mistake of adding a few more zeroes to a reported fact. This type of error has implications for analysts and investors who use this data for analyses.

Here is one company that tagged its Line of Credit, Remaining Borrowing Capacity as $555 billion when it should be $555 million.  From the chart below, the error skews the graph and shows that perhaps the company did not have any Line Credit Facility, Remaining Borrowing Capacity in prior quarters.

In fact, the company does have $1.5B in 2019 Q3. A large variance check would reveal the potential issue similar the following finding.

"The reported value of 555,000,000,000 (03/31/2020) for us-gaap_LineOfCreditFacilityRemainingBorrowingCapacity shows a variance of 36,900% from the value reported from prior quarter. The value for the prior quarter was 1,500,000,000"
**Large variance check from idaciti Inline XBRL Viewer custom validation

Paying close attention to your company’s XBRL filing quality is essential for your company to control the messaging to the investors, analysts, the public, and the SEC.  

Your investor relations team and audit committee likely do not want to see your company appearing on XBRL US “Filing Results and Quality Checks” dashboard as having filing errors. Neither would you want the SEC to come knocking on your door when your filing cannot be compared to peer companies. Finally, investors and analysts think that your company has $555 billion in lines of credit borrowing capacity, which may result in bad investment decisions. To avoid these pitfalls, make sure you get a tool that has built-in automatic data validation checks.


Fix these problems before filing with the SEC.