Machine-readable financial reporting is less scary than you think

Bonds

Despite opposition from various municipal bond market experts and interest groups, Congress has now instructed the Securities and Exchange Commission to develop machine-readable standards for EMMA filings.

As implementation of the Financial Data Transparency Act (FDTA) begins, it is important to clear up some misunderstandings about this legislation.

Opponents of FDTA expressed concern that a single template would be imposed on a wide range of municipal issuers around the country. If true, this would be a very serious issue because the financial statements of cities differ greatly from those produced by school districts, water districts, road districts, etc.

Marc Joffe addresses concerns about machine-readable financial reporting.

There is also substantial variation across states, including some that have not implemented Governmental Accounting Standards Board standards for local government financial reporting.

But this concern is easily addressed during implementation.

First, there is no hard and fast requirement that all entities must use a single reporting taxonomy (i.e., a dictionary of financial statement concepts). There could be one or more specialized taxonomies for New Jersey cities, Washington state school districts and other non-GASB compliant issuers.

More importantly, a taxonomy does not straitjacket issuers into a fixed set of concepts.

General purpose governments and special districts use overlapping categories of revenues and expenditures. But there is no limit to the number of categories that can be included in an eXtensible Business Reporting Language (XBRL) taxonomy and no requirement to use all the categories provided.

When my colleagues at XBRL US partnered with University of Michigan’s Center for Local, State and Urban Policy (CLOSUP) to develop an XBRL taxonomy for Michigan local governments, we reviewed a large number of Annual Comprehensive Financial Reports (ACFRs) to determine which financial statement captions appeared most frequently.

We included all of these in the taxonomy. Also, we provided a mechanism for financial statement filers to include concepts that were not specifically listed in the taxonomy.

Filers can use a feature of XBRL to add custom line items they need to report that are not explicitly included in the taxonomy. An entity-specific line item can be created that rolls up into assets or revenues, for example. Issuers can report what they need, and data can still be compared across issuers at the asset or revenue level.

The CLOSUP project was XBRL US’s fourth version of an ACFR taxonomy in four years, which brings me to another point about the opposition critique of FDTA.

Contrary to critics’ assertions, two years is plenty of time to develop machine-readable reporting standards. In fact, if the SEC chooses to base its taxonomy on XBRL US’s work products, the development time could be significantly shorter.

Another contention was that the compliance costs would be very high: perhaps $1.5 billion over two years as public agencies replace accounting systems and/or hire expensive consultants. But neither of these options is necessary.

The XBRL community includes firms that offer document production solutions, which can take the form of Software-as-a-Service (SaaS) web sites, desktop software, or Excel add-ins, as well as companies that can prepare an XBRL version of a financial statement from the filer’s PDF.

Open-source tools, which are free to use, are also available.

During the runup to implementation, the community will be updating their products to support ACFRs and other municipal market disclosure.

Open data standards foster competition among tool and service providers which keeps costs low and encourages innovation. Reporting packages and applications in use today by government entities can be adapted to work with the open standard, minimizing potential disruption to issuers.

Municipal market participants who want to learn more about machine-readable disclosure are welcome to join a free webinar hosted by XBRL US and University of Michigan CLOSUP on Jan. 24.

Even if concerns over implementation time and cost are overblown, some industry observers still question the need for machine-readable municipal disclosure. After all, market participants have been investing in bonds based on paper disclosures, PDFs, or perhaps not even consulting disclosures at all, so why bother?

But since research shows that certain financial ratios are associated with heightened default probabilities, ignoring the data in municipal disclosures is a recipe for making suboptimal investment decisions.

The inability to quickly access free fundamental issuer data sets the municipal bond market apart from the U.S. corporate securities markets and is one reason why our market is so inefficient. Corporate securities investors can quickly find issuer data on SEC EDGAR or one of a dozen free web sites.

Machine-readable disclosures will lead to the commoditization of municipal finance fundamentals because it will become extremely inexpensive to create municipal databases from XBRL filings. While data commoditization may be an adverse development for today’s data vendors, it is a prerequisite for an efficient municipal securities market, which will benefit issuers and investors alike.

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