Reasons Why Fundamental Accounting Concept Tests Fail
Sunday, September 28, 2014 at 09:37AM
Charlie in Becoming an XBRL Master Craftsman
There are exactly three possible reasons why a relation between the high-level fundamental accounting concepts fails:
  1. Error in filing: The public company SEC XBRL-based financial report which reports some fact or facts does so incorrectly; a fact is wrong or a relation between facts is wrong or is interpreted differently than was anticipated for some reason
  2. Error in base taxonomy: The US GAAP XBRL Taxonomy expresses a concept which is used to report a fact does so incorrectly which is an error or does so ambiguously so that there are different interpretations by those using the taxonomy or some important or common concept is missing altogether
  3. Error in mapping or impute metadata: The metadata used by the software algorithm to compute or otherwise interpret the fundamental accounting concepts or the relations between those concepts is in error or are interpreted differently by different software creators

If there is any issue detected by software applications in the high-level fundamental accounting concept relations, it becomes impossible to then safely use that information without a human getting involved to determine the reason why the anomaly has occurred. And this does not mean using the fundamental accounting concepts; this means using any information in the entire report becomes risky.

As such, it is these high-level fundamental accounting concept relations which serve as a solid base upon which other relations are then built.  For example, if the accounting equation is known to be true which is "Assets = Liabilities and Equity", then next obvious question is does assets foot and does liabilities and equity foot.

Further, prudence dictates that using financial information in SEC XBRL financial filings should not be a guessing game.  Software vendors must write algorithms and create metadata which enables them to make use of machine readable financial information.  If untangling and otherwise deciphering this information is too complicated for them, then it increases the probability that different software vendors will create different metadata and software algorithms, and therefore different software applications will give different answers to exactly the same question.

Therefore, the safe, reliable, predictable, repeatable use of the facts reported within a machine readable digital financial report demands that the high-level fundamental accounting concept relations to be 100% satisfied.  Or said another way, deriving some set of high-level concepts so that facts reported within a machine readable digital financial report can then be safely, reliably, predictably, and repeatedly be sent to automated downstream processes is essential to using any information in that machine readable report.

In order to communicate with someone else about this information it is critical to use consistent terminology so that both parties understand what is being communicated in the same way.  If parties communicating have different understandings of specific words, communication does not really take place.  The following are specific terms which are used and the definitions of these terms.

There is a difference between a fact, the interpretation of a fact, knowledge, and an opinion.

When attorneys argue a case one of the first things they do is try and agree on the facts, the items about the case which are not in dispute. When an interpretation is agreed to by both attorneys, that interpretation becomes a fact.  If both parties in a case agree on some set of facts it can be said that both attorneys have knowledge of the facts, generally both parties agree when there is evidence which can be used to justify that knowledge.  Everything else which cannot be agreed to becomes an opinion which is then argued in the case.

Evidence is provided but the parties don't agree on the evidence or they can dispute evidence with different interpretations of facts.

Sometimes it is a useful thing to create a shared reality to achieve a specific purpose: To arrive at a shared common enough view such that most of our working purposes, so that reality does appear to be objective and stable.

Computers are dumb machines. Computers only appear smart when humans create standards and agree to do things in a similar manner in order to achieve some higher purpose.  In the process of agreeing, it is important to understand the difference between what is important and what is unimportant in the process of agreeing:
Nuances and subtle differences are important things that matter. Negligible things are unimportant and do not matter.  The difference between what is a nuance or a subtle difference and what is negligible many times takes professional judgment.
I say again, computers are dumb.  Computers only appear smart when humans create standards and agree to do things in a similar manner in order to achieve some higher purpose.  In the process of agreeing, it is important to understand the difference between what is important and what is unimportant in the process of agreeing:

Sometimes things are required, other times things are a choice.  Yet in other times setting some policy eliminates certain options which could have been considered.

Agreed upon standard interpretations are critical to making a system work safely, reliably, predictably, and in a manner which can be repeated over and over without error.  Philosophical or theoretical debates, trying to satisfy all arbitrary options, trying to meet every unimportant negligible situation, confusing what is objective and what is subjective, confusing policies with requirements and with choices only make something which could be sophisticated but simple into something which is complex, confusing, and can never be made to work.

Some people might believe that there is one absolute reality and that reality is their reality and that everything about their reality is important and they can compromise on nothing.   Some people insist that everything involves judgment and that nothing is in any way subjective.  But this is to miss the point. The point being:

A shared view of reality which is clearly interpretable and understood to achieve the purpose of meaningfully exchanging information so that time is reduced, costs are reduced, and information quality improves provides a benefit.

The goal is to arrive at some equilibrium, to balance the duality, to recognize that there is no singular objective reality but in spite of that, if we create a common enough shared reality to achieve some specific and agreed upon working purpose and considers important nuances and subtleties machines can be made to do useful work.

To make reality of the financial reporting domain appear to be objective and stable in certain specific and agreed upon ways in order to fulfill some higher purpose.  The purpose is to enable a machine to read and interpret certain basic information such that manual human work can be effectively eliminated and that higher-level interpretations are then possible.

So basically, public companies should want their financial reports to be fundamentally decipherable and consistently interpreted at some fundamental level.  If reported information is not fundamentally interpretable, there is no foundation upon which to build.

Why information cannot be interpreted by automated processes is excellent evidence in determining what is necessary to make information interpretable by automated processes.  Even better, comparing two or more interpretations against each other is really the only way to assure that interpretations can be consistent.

What can be interpreted can grow.  But it can only grow as fast as the business rules, the tests, which prove consistent interpretation.  If business rules are not provided, what is there to test how information was interpreted?  The fundamental accounting concepts are both a base level of interpretation and a very good clue as to what is needed to correctly interpret more aspects of a digital financial report.  The fundamental accounting concepts are an important building block.

And so these other things are just steps in the interpretation process.  The "minimum criteria" is for making base use of reported facts. The base expands based on expanding buiness rules. To the extent business rules assure that information is correct, is to the extent that interpretation of information can occur.

So, the issues pointed out by fundamental accounting concept tests are interpretation issues.  If a process stumbles in an attempt to interpret information, that is a strong clue that something is wrong.  It could be filer error, taxonomy error, or metadata/algorithm error.  The processes is to agree which category caused the process to stumble, fix that error, and try again.  When interpretation software does not stumble, then the system is in equilibrium.

Filings are publically available, the US GAAP XBRL Taxonomy is publically available, and the metadata used by software algorithms created by software vendors should be publicly available.   Any arguments people have need to be directed at one of those three things: the filing, the taxonomy, or the other metadata.

Examining each also provides clues where things can be made less complex.  Why are so many mappings necessary, can some be eliminated?  Why are impute rules so complicated, can't they be simplified?

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