A Broader and Deeper Use of Structural Data
CFA Institute recently co-sponsored the XBRL Investor Forum 2021: Data That Delivers. SEC Commissioner Caroline Crenshaw gave a keynote speech outlining the extensive benefits of structured data.
Crenshaw began by reflecting on the SEC’s history with XBRL data and what it delivers:
Commission’s implementation of XBRL requirements has allowed EDGAR to provide machine-readable data that have improved transparency in a number of ways. For example, XBRL has enabled automatic processing and analysis by software tools, which lowers costs and offers more timely insights. Users can access better and more granular information about these data, like the accounting codifications and guidance associated with it. Machine-readable languages like XBRL and iXBRL allow machine learning and artificial intelligence programs to leverage both numeric and narrative disclosures. It allows the automation of all manner of disclosure analysis—identifying what is and is not reported, identifying data quality errors, comparing results across data sets, performing other analytics, generating time series charting and benchmarking, and much more.
She also noted that such data are used by investors (both institutional and retail), regulators, data aggregators, academics, and news media:
All of this user activity adds up to more market transparency and more efficient markets. For example, since the implementation of the XBRL mandate, we have seen stock prices become more reflective of firm-specific disclosures; we’ve seen increased quantitative disclosure from firms; and we’ve seen decreased earnings smoothing. It also adds up to fairer, more competitive markets. Research indicates that XBRL disclosures reduce the advantages enjoyed by insiders, relative to non-insiders.
These views are in line with those of CFA Institute, as outlined in our 2016 publication Data and Technology: Transforming the Financial Information Landscape.
How Can We Deliver Better Data?
Crenshaw then addressed how the quality of the data could be improved:
However, while I believe XBRL data are delivering myriad benefits, there is room for improvement in terms of the quality and accuracy of the data. Some users have found material error rates in data tagged in our filings, including errors in tags that are likely to be crucially important to investors like Revenues, Net Income, and Assets, and scaling errors that can be impactful.
CFA Institute not only is aligned with Crenshaw on these data quality views but also has urged the EU not to replicate the mistakes made in the United States in this regard.
Delivering More
Finally, Crenshaw addressed what more could be done:
Now, as I’ve discussed at length today, the potential benefits of tagging data are extensive. So we at the SEC should continue to investigate where else data structuring can improve our disclosure ecosystem. The tagging of narrative disclosures, even just block tagging, could enable data users to more easily extract and compare non-structured disclosures, like management discussion and analysis, earnings reports, and executive compensation. This could be relevant in the context of ESG disclosures, SPAC disclosures, and elsewhere.
Again, we agree.
In the report on our findings, we outlined our vision for the future—the broader and deeper use of structured data.
Structured reporting is most effective when it is applied broadly to all aspects of reporting—that is, to earnings releases and all regulatory filings, proxy statements, and tax reporting. And structuring needs to apply to all companies, big and small.
Furthermore, regulators need to require structured reporting beyond just the financial statements by applying structuring to all reports in their entirety. Doing so will allow investors to take a deeper look into annual reports and other reports, including the notes and management commentary.
Broader and deeper use of structured data across all reports in their entirety would bring about untold efficiencies and transparency for all users.
Image Credit: © Getty Images/Andriy Onufriyenko
