Digital Financial Reporting

AsReported has provided a set of measurements related to the quality of XBRL-based financial reports created by different software vendors and filing agents.  Here is their blog post that has the measurements.

What AsReported is measuring is a bit different than what I am measuring.  My focus is on accounting and reporting logic.  AsReported is more focused on mechanical, structural, mathematical, and some logical relations at this point it seems.  What is interesting is that they give each filing agent/software vendor a score (see the right most column).  They call this the "Quality Score" and discuss that metric on their blog.

Another software vendor taking measurements is XBRL Cloud.  They provide details for each filing on their EDGAR Dashboard.  You can search by company name and get details by public company.  Here is an example.

I am leveraging the success of my informal campaign to improve the high-level fundamental accounting concept relations of XBRL-based financial filings submitted by public companies to the SEC.  I am starting a new informal campaign to improve the quality of disclosures.  This is a great learning opportunity.

Between March 2015 and August 2017 filing agents and software vendors were able to reduce the number of errors related to the reporting of basic, fundamental high-level accounting concepts in XBRL-based financial reports from approximately 4,463 to 1,059.

These errors related to reporting high-level facts such as Assets, Liabilities and Equity, Revenues, Net Income (Loss); about 75 or so facts on average. During that period, there were four filing agents/software vendors which had tuned their processes to deliver 99% or better consistency with my basic set of business rules that uses automated processes to detect logical, mathematical, consistency, and continuity related issues within and between these high-level fundamental accounting concepts.

The errors I detected are generally not disputed because they relate to logical and mathematical relations between concept defined by US GAAP, evidence exists within public company financial reports of these relationships, about 99.02% of the actual reported facts within XBRL-based reports are consistent with and therefore support the machine-readable business rules used in my processes, and 88.2% of public companies are consistent with and support all of the business rules used to evaluate reports.

All of this information is publically available on my blog.  Anyone can verify or dispute issues by simply looking at any XBRL-based financial report of a public company. I have created summaries that professional accountants can use to examine and understand these errors.

The most important benefit realized from taking these measurements, building rules, and detecting these errors is an excellent understanding of XBRL-based financial reports and what makes them work. Currently, the best understanding of these reports seems to exist within the processes and procedures of four institutions that have been able to create repeatable, reliable processes of creating financial reports that are 99% or higher in consistency with these fundamental accounting concept relations: 

• Merrill
• RDG Filings (Thunderdome software)
• Donnelley Financial Solutions
• DataTracks  

There are several other software vendors/filing agents that are closing in on repeatable processes that yield high-quality results. How to build repeatable processes that yield high-quality results can be learned.

Building on what I have learned from the measurement of the fundamental accounting concept relations; I am embarking on the next step in my systematic, methodical, deliberate, rigorous journey to understand and be able to create high-quality XBRL-based financial reports: the disclosures.

A grass-roots, market-driven, informal effort to improve the quality of about 65 specific disclosures in the 10-K financial reports of public companies which are submitted to the SEC in the XBRL format will take place during this years "10-K filing season" during December 2017, January 2018, February 2018 and March 2018.

A few software vendors/filing agents already have a jump on others and are improving 10-Ks which will be filed during Q4 of 2017.

What I am trying to do is disseminate information to as many professional accountants, particularly certified public accountants, as possible so that they can better understand the subtleties and nuances of XBRL-based financial reports. This will help the institution of accountancy leverage this useful tool which the SEC has helped to create and is helping to make a real, reliable, working, knowledge media. Analysts also need to understand the subtleties and nuances of such reports. Software engineers creating software need to understand.

The use of this knowledge media will go beyond financial reporting but will be built upon the successful use of XBRL for financial reporting.

Here is information that is helpful in understanding this campaign: 

• Summary Information about Campaign: The document Campaign to Improve Disclosure Quality of XBRL-based Public Company Financial Reports Submitted to the SEC summarizes information related to this informal campaign.
• Summary of 65 Disclosures Tested: This is a DRAFT of the disclosures that I will initially target for my campaign. Current measurements show that on average about 85% of these disclosures are consistent with logical, mechanical, structural, and mathematical expectation.
• Details about 65 Disclosures: The document Disclosure Best Practices provides additional details about the 65 targeted disclosures.
• Understanding Business Rules: A big part of this campaign is understanding the role that business rules play in specifying how XBRL-based financial reports should be created.  The document Supply Chain Agreeing on Disclosure Business Rules walks you through the process of understanding and revising business rules.
• Creating High Quality Digital Financial Reports:  The document Blueprint for Creating Zero Defect XBRL-based Digital Financial Reports helps you understand how to create high quality XBRL-based financial reports.
• Getting ready for the future of financial reporting:  The document Getting Ready for the Digital Age of Accounting, Reporting and Auditing: a Guide for Professional Accountants helps you understand that financial reporting will be going through a transformation and helps you understand that you need to get ready for that new paradigm.
• Disclosure Effectiveness: This guide by EY, Disclosure Effectiveness, What companies can do now, provides a helpful framework for thinking about financial report disclosures.
• Commercial Tools Available:
  • Disclosure mechanics and reporting checklist
  • Fundamental accounting concept relations
  • Reporting Checklist, Disclosure Mechanics and Fundamental Accounting Concepts
• XBRL US Statement of Cash Flow Guidance
• Disclosures by Topic (Prototype)

This is a HUGE learning opportunity.  You will get out of this in proportion to what you put into it.  Because Donnelley Financial Solutions, Merrill, RDG Filings and DataTracks did so well to get their filings free from the fundamental accounting concept relations continuity cross check errors, I am very motivated to help them continue on and get their disclosures to the same 99% consistency that they were able to achieve.  But, I will help anyone that shows true effort.

What I am doing here in no way takes away from what the XBRL US DSC is doing.  It supplements that work.  The more rules the better because the more rules, the more than can be automated.  The more that can be automated; the more machines can augment human effort…just like a calculator augments a humans capabilities to do math.

If you are unclear where I am going, I would suggest that you read or reread this document:  Getting Ready for the Digital Age of Accounting, Reporting and Auditing: a Guide for Professional Accountants.

The enemy is not each other.  The enemy is the status quo.  If you want to expand your market from the 10,000 public companies that are REQUIRED to use XBRL-based digital financial reporting, to the 26 million private companies in the US that might WANT to leverage XBRL-based digital financial report capabilities; you MUST make it better than the current old school approaches that they use.  If XBRL-based reporting does not fundamentally work, that will never happen.

Once the initial batch of 65 disclosures are tuned; I will add the next batch of 500.  Then the next batch of 2,000.  I really have no idea how many unique disclosures there are, but I will find out.  I suspect somewhere between 2,000 and 5,000 perhaps.  But between now and March 31, 2018 I will focus on the 65 easy targets.

If you want to join the XBRL-based digital financial report study group, please contact me.

If you want additional information, feel free to contact me.  Follow my blog for information flowing from this grass roots campaign.

Analysis summaries:

• Disclosure analysis set 1
• Disclosure analysis set 2

So here is a documented case where XBRL contributed to detecting and correcting an accounting error. Click on the image below to get a larger image after you read this.  In this public company's March 31, 2017 income statement (on the LEFT) they ordered their income statement line items one way.  Then, in the June 30, 2017 income statement (on the RIGHT) they ordered them a different way.

The NEW way is consistent with literally all public companies that report these line items and consistent with the US GAAP Financial Reporting XBRL Taxonomy.  The OLD way was not.

(Click image for larger view)This inconsistency was detected using the fundamental accounting concept relations validation continuity cross checks. Now, they still don't have their XBRL-based representation correct.  They have some concept selection issues that need to be fixed.

A measurement of XBRL-based public company financial reports to the SEC that I have made indicates that those reports are about 88% consistent with what I would expect.  That said, the measurement is per a sampling of 65 disclosures for all 6,023 public company 10-K filings for 2016 and I cannot call this a verifiably scientific set of results.  However, if anyone has a better measurement I would love to see that measurement.

Here are the details:

(Click image for larger view)I am just starting a journey that will be very similar to the measurement of the fundamental accounting concept relations that I have been taking.  Those measurements are more precise and indicate that 99.19% of those relations are consistent with expectation.  There are currently 5,271 of 6,000 reports or 87.9% of all reports that are consistent with all 22 of the fundamental accounting concept relations.

Right now I am calling this measurement the "Disclosure Mechanics" of a disclosure.  If you want to understand this in detail, please go read Understanding the Mechanical Rules of Disclosures.  Here is the crash course.  First, I create logical, structural, and mathematical relations information in machine-readable XBRL format.

That rule in human-readable form looks like this:

(Click image for larger view)There are similar rules for 65 disclosures.  Software uses the rules (currently there are two commercial implementations) to check disclosures.  Here is the explanation mechanism provided by one of the commercial implementations:

(Click image for larger view)The results are summarized and either a disclosure is consistent with expectation or inconsistent with what was expected.  There are THREE REASONS an inconsistency might occur:

1. The filing has an error that needs to be corrected.
2. The US GAAP XBRL Taxonomy has an error that needs to be corrected.
3. My test or the software algorithm has an error that needs to be corrected.

How do I know I am getting the results right? Observed empirical evidence from the XBRL-based reports themselves.  Here is an example of that for the inventory components disclosure.  I have some really good tools that I have created and perfected.  Also, there are commercial tools that are becoming available.  I helped XBRL Cloud create this tool for checking Disclosure Mechanics rules.  Tools will continue to improve and evolve.

Over time these errors are corrected and the consistency rate increases, just like they did for the fundamental accounting concept relations.  Harmony increases in the system, information quality goes up.  What is the quality goal?  In my view, the goal is Sigma Level 6 which is 99.99966% consistent with expectation. Right now we are between Sigma Level 2 and 3.

If you want to know more about creating zero-defect XBRL-based reports, please read Blueprint for Creating Zero-Defect XBRL-based Digital Financial Reports.

If you have some tool ideas, please send me an email.

There are now 11 software generators and filing agents that have 90% or more of their XBRL-based public company financial reports consistent with all of the fundamental accounting concept relations continuity cross-checks.

This ZIP file contains an Excel Spreadsheet which contains detailed information about errors.

Per my measurements, the quality of XBRL-based public company financial reports continues to improve. If you compare the 2016, 2015, and 2014 results you can definitly see the improvement.

Here is the summary of consistency with the fundamental accounting concept relations continuity cross-check business rules as of March 31, 2017:

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Comparison March 2017 with November 2016:

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Compare March 2017, March 2016, March 2015:

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**********************PRIOR RESULTS**********************

Previous fundamental accounting concept relations consistency results reported: November 28, 2016; August 31, 2016; June 30, 2016; March 31, 2016; February 29, 2016; January 31, 2016; December 31, 3015; November 30, 2015; October 31, 2015; September 30, 2015; August 31, 2015; July 31, 2015; June 30, 2015; May 29, 2015; April 1, 2015; November 29, 2014.

Information helpful in understanding errors.