The New York Society of Security Analysts’ Financial Reporting and Analysis Group hosted a program on using XBRL formatted structured SEC corporate data filings to expedite and ease financial reporting and analysis. Panelists were Mohini Singh (CFA Institute), Todd Castagno (Morgan Stanley), Pranav Ghai (CalcBench), Ralph Schroeder (FASB), Mike Willis (Securities and Exchange Commission), Mark Montanaro (FDIC) and Campbell Pryde (XBRL). The program was organized by Arthur Fliegelman (Office of Financial Research) and Mohini Singh.
With over 150 million data points in this structured database, XBRL has the potential to increase the volume, speed, and access to information available to users and regulators. XBRL is currently being widely used to enhance financial analysis and decision making. Further improvements and expansion of structured filings would make this data even more valuable.
XBRL usage is still developing. There are several important areas related to data quality and accessibility needing improvement. Three basic but important issues relate to – who needs the information, what information is needed and when is it needed. The most important single improvement would be to require earnings releases also be filed as structured filings. Requiring tagged data associated with earnings releases is an area needing urgent attention if structured data is to provide investors with useful and timely information.
Investors and analysts interested in promoting tagging of data associated with earnings releases, can approach the SEC through the comment letter process or by a petition for rulemaking.
High quality of filed data is vital. As its use advances, data quality will improve. A key priority of standard setters is improving both the taxonomy and tagging of data to enable more efficient data access by users.
In the current environment, active fund managers find it increasingly difficult to outperform market indices. Previously successful strategies no longer produced excess returns and new investment approaches are needed. Strategies involving more advance analytical techniques using large scale financial statements can help accomplish this objective. This is an area where structured data can be extremely useful in improving the analytic power and speed.
Castagno discussed using structured data to access companies’ and industries’ unremitted foreign earnings. Analysis that previously would have taken weeks to accomplish manually was accomplished in days. Similarly, Castagno noted that Morgan Stanley rapidly generated information on corporate exposure to the U.S. markets by accessing data on the percentage of pre-tax profit and the proportion of long-lived assets both inside and outside the U.S.
User groups currently access structured data mainly through the use of aggregators such as CalcBench.
The SEC uses structured data in several ways including text analysis of narrative disclosures to analyze tone and sentiment. The commission has also used structured data to create a Corporate Issuer Risk Assessment dashboard scaled by industry sector and size as part of monitoring company risk profiles.
An example of data accessibility issues highlighted by Castagno relates to the FASB’s recent change to accounting for stock based compensation. Companies paying stock compensation and have seen their share price increase, can now include this excess benefit in their profit and loss statement as well as in their operating cash flows. For many companies this can increase their net income and free cash flows by 6% to 8% (for example Facebook in 2014 and 2015). However, no tag for share based compensation within the rate reconciliation table of the notes to the financial statements currently exists. Investors must access this information manually, but it highlights the potential of what XBRL can achieve when a fully functional taxonomy is in place.
Other future improvements include users accessing the accounting standard behind the disclosure. Since accounting standards are moving more in the direction of principles than rules, this enables users to better understand management’s accounting choices.
Finally, while there is some cost based resistance to structured data adoption among smaller and medium sized companies, the exposure benefits that it would provide to them would be a major advantage. Ghai noted that 80% of financial data search on CalcBench’s platform is for small to medium size companies that may not otherwise be economic to analyze.
XBRL is still developing but already offers compelling user advantages. It does not diminish the need for financial analysts to use their judgments in decision making, but it enhances their ability to do so. It has the potential to expedite the extraction of high quality data for investor decision making. There is more work to be done but the results so far are very promising.
By Santhosh Abraham, CFA (Excelsior College) & Arthur Fliegelman, CFA (Office of Financial Research)