A Massive Productivity Enhancement For Research Analysts


New York, NY – One of the compelling trends taking place at a number of the larger buy-side firms in the past few years has been a move to  “internalize” their research capabilities.  And while some firms have chosen to invest more on their own analytical capabilities, most firms have increased the research burden on existing analysts — a development that has forced buy-side analysts to cover more and more companies.

This trend has prompted many buy-side research directors to look for  tools to increase the productivity of their analysts.  One development which has been in the offing for a few years could be a real boon to buy-side (and sell-side) analyst productiviey is the widespread adoption of the Extensible Business Reporting Language or XBRL.

XBRL is an electronic tagging system developed by a consortium called XBRL International that users of financial statements (analysts and investors) can use to select and pull both financial and non-financial information from the text and financial statements of public disclosures such as press releases, 10-Qs, and 10-Ks.

Despite vocal support from SEC Chairman Christopher Cox, XBRL has not been widely adopted in the US with only 54 of more than 10,000 publicly traded US companies voluntarily filing in this format.  However, the global use of XBRL is gaining considerable momentum.  In fact, as of September 2005, more than 800 Chinese companies filed their half year reports using the XBRL standard.

Of course, the major issue in the US is that the XBRL format has not been mandated by either the SEC or by the individual stock exchanges as it has in many overseas countries.  However, a number of extremely influential members of the SEC have publicly commented that at some point in the future, they would support mandating that public companies file their SEC documents using XBRL.

Unfortunately, many sell-side and buy-side firms are relatively unaware of the massive productivity benefits of using XBRL in their day to day operations.  To that end, we have included the following excerpt from a recent research report published by Bear Stearns’ Accounting & Tax Policy analysts outlining the benefits of using XBRL.  This report was published on October 5, 2007 and is titled, XBRL: The Investor’s Path to Better, Faster, & Cheaper Financial Information.


What are the primary benefits of XBRL to investors? If I am an analyst already subscribing to databases that allow me to download financial information, why is the introduction of XBRL a meaningful event for me?

XBRL should make the financial information collection process simultaneously faster, cheaper, and more accurate, thus it should outperform our current collection methods (manual input and databases) on all relevant metrics.

XBRL has the ability to level the information-collection playing field. By giving all stakeholders the ability to capture relevant data at the instant it is released by a company, everyone will have equal access to XBRL-tagged information. As a result, the process of preparing financial analysis will be increasingly focused on value-added analytical  activities and any marginal advantages some participants have cultivated through their ability to churn through financial information faster than others due to more manpower or better filtering technology will be drastically reduced.

Some analysts collect financial information directly from financial filings, while others simply download information from fee-based databases such as FactSet or Bloomberg. Whether analysts collect the data themselves or outsource data collection to database providers, this information is prone to the same common types of problems and errors that affect its reliability and relevance. First, there is the collection time delay between when information is released by companies and when it is manually entered into spreadsheets and databases. Further, data collectors often misidentify or mistype information. The use of tags provides the ability to gather the information the instant it is released, eliminate the possibility that the analyst typed in the wrong data due to looking at the wrong data field or making a typographical error, and essentially eliminates a time-consuming portion of the analyst’s responsibilities.

We can use our own group’s activities as an example. Often times we conduct very large studies on accounting issues impacting companies in indices such as the S&P 500 and Russell 3000. Due to the significant volume of data we need to analyze in these studies, we either must spend weeks or months manually collecting the data or download the data from the databases available to us.

If we collect the data ourselves, we often must make the decision to not collect some relevant data to our analysis simply because every additional data item we decide to collect can lead to days or weeks of additional data-collection time. Further, we have found that when we make the decision to collect information from databases, we often must spend days or weeks “cleaning” the data due to errors made by the data collectors. When we compare our manually-collected information to database information, we typically find an unacceptable level of data entry errors in databases. While cross-checking our data adds to the reliability of the information we publish in reports, it is a costly and time consuming process that could be completely eliminated with the mass-use of XBRL technology.

The cost of information is reduced with XBRL because it is available either directly from the company or through the SEC’s XBRLbased Interactive Financial Report Viewer (IFRV) at no charge. Further, Hitachi America, Ltd. offers a free XBRL reader called Xinba Reader that gives users the ability to import, open and read XBRL financial information filed on IFRV in Microsoft Excel.

Fee-based databases will still be valuable to investors since they aggregate this information across thousands of companies and provide users with the ability to simultaneously download information on thousands of companies rather than just one at a time.  These fee-based databases will also benefit from XBRL because their data will be more accurate since it will be aggregated electronically rather than being gathered manually. By eliminating or at least significantly reducing manual data entry, XBRL should reduce the cost structures at database companies, which potentially could lead to more competitive pricing.

In the end, better data adds more integrity to our financial system. This is especially true given that there are more and more quantitative analysts screening enormous amounts of data across thousands of companies and often times their computer programs focus on data outliers. It has been our experience that a lot of the outliers in large data screens are due to data inaccuracy. XBRL can help to eliminate this data contamination.

In addition, it has been our finding based on years of talking to clients that analysts employ a multitude of different investment philosophies and processes. While some data points are of primary importance to some analysts, those same data points can sometimes be of little or no importance to other analysts – even when they are analyzing the same company.  Analyst models often significantly diverge from GAAP financial statement presentations. It is important that analysts have the ability to build models that recast the financial statements with the format and content that they see fit to make an investment decision – regardless of whether or not that format is consistent with US GAAP. This ability to adjust data will become increasing important as we see more and more of the financial statement line items measured at fair value. XBRL will give analysts the ability to make adjustments as to how they chose to treat fair value gains and losses.


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