Columbia Business Schools Center for Excellence in Accounting
and Security Analysis An Evaluation of the current state and future
of XBRL and interactive data for investors and analysts (Dec. 2012)
Interviews and surveys with: preparers; regulators; analysts;
investors; XBRL developers; data aggregators; XBRL filing and
consumption tool developers Findings: In our view, XBRL has
succeeded in so far as the objective of providing users with free,
interactively-available numerical data from portions of published
financial statements and footnotes, as soon as they are filed with
the SEC. Most of the analysts and investors we spoke with are
interested in and tried to use the footnote data that are
XBRL-tagged. We have no doubt that analysis of companies will
continue to be based off increasing amounts of data that are
structured and delivered to users in an interactive format.
However
Slide 5
However Unless the XBRL stakeholdersincluding filers,
regulators, and developersfocus on the datas reliability and on
value- added, easily integrated consumption tools, we doubt that
the XBRL-tagged data will be used by a significant number of
investors and analysts. Unless the FASB and SEC also ensure that
the focus of the underlying taxonomy is on simplification and
enhanced utility, improved data quality is not going to be
sufficient for users to readily access and use the data.
Slide 6
However Unless the XBRL format becomes integrated as the
language to structure data in the underlying general ledger or MIS
systems, we believe that it is unlikely to become the format for
most of the firm-specific financial data that investors and
analysts want to use. We question whether it is necessary to have
the data structuring provided by the issuer at the source of a
regulatory filing versus by a data supplier or other end user,
given the current state of technology. However, providing
issuer-tagged information would be valuable, as long as it was
tagged at the disaggregated source, rather than only at the
aggregated level as reported in a periodic regulatory
presentation.
Slide 7
Recommendations The entire XBRL community must find a way to
reduce significantly the error rate and unnecessary extensions
(company-specific data tags). Some approaches that might achieve
this are: providing greater regulatory oversight potentially
requiring an audit of the data or requiring filers to resolve the
error and quality checks communicated to them by XBRL US. Filers
should spend the effort they are investing in attempting to destroy
the SECs XBRL regulation on improving the quality of their own
data, as well as on making their own data more useful and
accessible to users. XBRL technology development needs to be taken
over and run by technologists, rather than accountants and
regulators.
Slide 8
Slide 9
Craig M. Lewis is Director and Chief Economist of the Division
of Risk, Strategy, and Financial Innovation (the SECs think tank,
also known as RiskFin or RSFI) and is on leave as a professor of
finance at Vanderbilt University. Q&A with an Expert: The SEC
is Developing Tools That Use XBRL Data to Discover Accounting
Anomalies and Improve Financial Disclosures
Slide 10
Risk Modeling At The SEC: The Accounting Quality Model
Developing cutting-edge ways to integrate data analysis into risk
monitoring. The mining of XBRL data is a key part of this
work.
Slide 11
Accounting Quality Model Developed with the SEC a predictive
model that attempts to identify firms which have made unusual
accounting choices relative to their peer group it is a fully
automated system that effectively takes a firms filing the day it
comes in, processes it, and then keeps it in the database so that
somebody who is interested in looking at a report on that company
would be able to do so within 24 hours of the filing being posted
on EDGAR. XBRL is critical to the development of the tool simply
because it allows us to have complete coverage.
Slide 12
How will this monitoring tool parse the XBRL data to select the
companies whose financials need extra review? The tool itself tries
to model what is known in the financial- accounting literature as
discretionary accruals. It is a predictive model that estimates how
much of the total accruals that a company reports are
discretionary. (Total accruals are the difference between cash
flows and net income.) One of the exercises we need to go through
is to take the taxonomy and synthesize it in a way so that we can
compress the actual taxonomy choices that companies make and the
way they use the taxonomy into high-level financial
statements.
Slide 13
Companies develop their own XBRL extensions. Does that cause a
problem in your system? One of the things we have noticed is that
the longer a firm is actually making XBRL filings, the fewer unique
extensions they tend to choose. So there is a learning curve that
seems to be going on, where filers may begin by using unique
extensions, but over time, as they become more comfortable with
using the taxonomy, the number of those unique extensions tends to
collapse.
Slide 14
XBRL Quality Now that there is an actual liability associated
with inaccurate XBRL statements, I fully expect quality to improve.
My view is that the real solution to this is inline XBRL: creating
a document where the tags are embedded directly into your filing so
that you do not have to have two separate documents. This seems to
be where the industry is moving, and I fully support that.
Slide 15
What about the claim that XBRL data is not being used? Data
hasnt been around long enough Time series data is needed SEC is
using the data Data quality improves as firms gain experience The
SEC was really just allowing firms to have a window to figure out
how to tag data. Now that the window has shut, we are just going to
start to use the data. I view it as the natural outcome of giving
filers the opportunity to figure out what they are doing with
XBRL.
