Leveraging XBRL Data in Financial Analysis
Back in August 2003, Timothy Koller wrote in McKinsey Quarterly an article “Numbers investors can trust”, where he emphasized the importance of “genuine disclosure” of financial information by public companies. It was a call to corporations that wished to regain the trust of investors after the 2000 dot-com collapse. By strange coincidence, that year was marked by a new crisis of sub-prime mortgages, which was again partly related to the lack of proper disclosure of business and financial information.
Today, we observe how the XBRL standard approaches its maturity stage. There exist a number of different validation layers/tools developed by the government and private organizations for improving the quality and consistency of XBRL data. The filers themselves have gained from 2 to 4 years of experience working with the new standard and the US-GAAP Taxonomy underwent a series of improvements. In June 2013, the limited liability for misstatements in “Interactive Data” filings (XBRL) in the US will expire. All these factors indicate that it is time for financial analysts to draw their attention to XBRL, which provides a powerful and flexible framework for investigating companies’ financial performance in ultimate detail and enforcing the outliers to become more transparent.
At FinDynamics.com, which stands for Financial Dynamics, we believe that one thing is still missing today – a simple and easy-to-learn tool for working with XBRL filings. What can be more familiar to the analysts and investors than Excel?! So, we decided to close this gap with our free Excel Add-in called XBRLAnalyst. It provides a seamless integration of Excel with XBRL filings and allows fetching the XBRL data in your existing workbooks and templates without any modifications to the latter. Moreover, we added Excel built-in functions that help pulling XBRL data together with other financial information provided by such aggregators as Bloomberg, Yahoo, and Google. In order to promote a more dynamic expansion of XBRL usage, we encourage users to collaborate by developing and sharing their Excel models leveraging XBRL. We believe that the full potential of XBRL reporting standard can be unearthed through interaction and collaboration and our XBRLAnalyst is intended to facilitate that. We collaborate with a research team from the University of Waterloo Centre for Information Integrity and Information System Assurance. They will use our software for performing data quality analysis on the XBRL filings of all the public companies in the US.
-Article by Ilya Vadeiko