In today’s digital world, companies are moving from manual processes toward automation, and so too are financial statement users. It is therefore essential that high-quality data is available to them in a structured, digital format. XBRL does just that.
XBRL is a framework of tags that allows users to digitize data points in a company’s financial statements and tax and regulatory filings, creating a machine-readable document. In essence, it converts the unstructured data in companies’ financial statements into structured data.
High-quality XBRL information promotes trust and can be a competitive advantage to companies. However, data quality issues within XBRL filings persist. And even though XBRL US reports errors they identify through their data quality rules, that's only a small percentage of total errors. An independent review of the tagging and judgments can help companies enhance the credibility of their XBRL information.
Better data leads to better decisions. The use of XBRL enables users to receive financial statements and footnotes of all public companies directly from the companies, without changes by third-party data providers. In doing so, XBRL helps facilitate analysis by investors, credit rating agencies, and regulators, and can even help management run the business.
XBRL makes it faster and more cost-effective to extract, sort, and compare financial information across companies for investors who analyze large amounts of data. In 2019, there were nearly 660,000 SEC filings.1 Although they vary, some filings can exceed 100 pages, so evaluating unstructured data can be cost-prohibitive for investor analysis at scale. XBRL provides investors with data in a usable format.
XBRL structures critical data for the capital markets, but it’s essential that it be reliable. To date, that has not always been the case. For the first three quarters of 2020, about 46% of Form 10-K or Form 10-Q filings of Fortune 500 companies had at least one XBRL-related error, according to the XBRL US Data Quality Committee (DQC). During that period, the average number of errors identified by the committee was 7 per filing.
So how can companies enhance accuracy and trust in the data? Understand judgments, refresh controls and processes, and supplement with assurance.
Structured data should accurately reflect the details in company financial statements and disclosures. The XBRL taxonomy can provide information without loss or distortion of information during collection and aggregation.
Judgment is required to apply the proper tags, especially for certain company-specific information. In some cases, company-specific customized tags are used to capture a company’s complexity and accounting policies. However, when used unnecessarily, they can distort investor understanding and make it difficult to compare companies.
The quality of XBRL data depends on the adequacy and effectiveness of internal control over the XBRL reporting process. To ensure their XBRL filings are accurate, companies should have strong internal controls and processes. To that end, companies that integrate XBRL tagging into the financial reporting process, rather than bolting it on at the end or solely relying on third-party vendors, are better positioned to produce high-quality XBRL data.
Some users assume, or expect, that the auditor’s opinion extends to the XBRL-tagged data. However, there is currently no audit requirement in the US on the XBRL filing, only on the financial statements as a whole. But many other countries have such requirements. Most notably, the European Union has an XBRL mandate that will require an auditor opinion for some EU countries in 2020 and others in 2021.
An Inline XBRL filing is a digital filing with two layers of information: one layer of data that can be read by human beings and another layer of data that can be read by machines … Investors, however, expect both layers of the filing to be audited. With both the United States and the European Union requiring Inline XBRL filings (and with Asian jurisdictions expected to follow suit), the time has come to at least start a discussion about the development of standards.
US companies should consider whether auditor procedures on their XBRL-tagged data would provide further credibility. Given the auditor’s role with respect to the financial statements, the auditor is in a unique position to evaluate the accuracy and completeness of XBRL tagging. Although not required by the SEC, companies can engage their auditors to (1) provide an independent perspective of whether the company’s tags, including company-specific tags, are appropriate and (2) identify errors related to the underlying machine-readable data and other technical specifications.
XBRL democratizes important financial statement data, making it more useful to investors. Improved consistency and quality in XBRL tagging, which can be supplemented by assurance, can improve the reliability of the data for users.