High Quality Examples of Errors in XBRL-based Financial Reports
Saturday, April 29, 2017 at 10:59AM
Charlie in Becoming an XBRL Master Craftsman

Below are links to PDF files that have high-quality documentation of approximately 380 errors that exist in XBRL-based financial reports of public companies which and been submitted to the SEC as of March 1, 2017. I detected these errors as part of my measurement of the fundamental accounting concept relations and the continuity errors discovered as part of those cross-checks.

Examining and understanding these errors can help professional accountants improve their skills in working with XBRL-based digital financial reports and software developers create software useful to business professionals that help them not make these sorts of mistakes.

I created this information so that I could provide it to professional accountants who were not detecting these errors when they created their XBRL-based financial reports.  Over the past several years I have made this information available to filing agents and software vendors which they used to understand and fix these sorts of errors.  These 380 errors are about one quarter of the remaining high-level errors in the set of about 7,000 public company financial reports.

These errors tend to be very uncontroversial.  Proof of that is that software vendors and filing agents, once they are made aware of these errors; fix these errors.  For example between 2015 and 2017; Merrill went from 55% consistent to 97% consistent; RR Donnelley went from 73% to 98% consistent; DataTracks went from 62% to 98% consistent. (See the comparison of periods here.)

All of these errors were detected using processes that have been implemented in commercial software. For example, here is a tool provided by XBRL Cloud which they make available on their Edgar Dashboard.

None of these errors are related to the XBRL techical syntax.  The errors all relate to employing XBRL to convey meaning.  These are logical, mechanical, and mathematical mistakes made by the creators of the reports.  Software needs to support the functionallity to detect these sorts of errors.  Here are a few examples of the patterns of errors that you find in the XBRL-based financial reports of public companies: (documented by the PDFs provided below)

Each of these errors are logical errors, mechanical errors, or mathematical errors which have NOTHING to do with XBRL technical syntax.  Each error was represented using PERFECT XBRL technical syntax; but the information conveyed was just wrong.

Principles help you think about something thoroughly and consistently.  As a result of my measurement of the fundamental accounting concept relations, I created the XBRL-based digital financial reporting principles.  They help you think about XBRL-based reports.

This information should be very helpful to professional accountants creating XBRL-based reports and software developers building tools those professional accountants use.  There are those reports grouped by audit firm.  I am not saying that any of these audit firms have responsibility for any of these inconsistencies, I am simply making this information available in this form because I also sent this information to each audit form to help them understand these sorts of errors. (April 2017)

Happy learning! Oh, if you are wondering why I am taking time to put together the business rules for discovering there errors; have a look at the components of an expert system and/or check out my little expert system for creating financial reports. The rules contribute to making the expert system work.

Article originally appeared on Intelligent XBRL-based structured digital financial reporting using US GAAP and IFRS (http://xbrl.squarespace.com/).
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