Common Practice Financial Reporting XBRL Taxonomies

I am thinking of creating two common practice financial reporting taxonomies.  One for US GAAP and one for IFRS.  These XBRL taxonomies would be for small and medium sized enterprises (SMEs).  There are several reasons to do this.

  1. Currently, the IFRS Foundation is reluctant to provide common practices concepts in their XBRL taxonomies.
  2. Currently, the IFRS Foundation is reluctant to include commonly used subtotals in the IFRS standards or the IFRS XBRL taxonomy.
  3. Both the US GAAP and IFRS XBRL Taxonomies are not very well represented.  Both disregard XBRL International Best Practices guidance for using XBRL dimensions by mixing their modeling approaches (e.g. sometimes hypercubes are used, other times hypercubes are not used).
  4. Neither the US GAAP XBRL Taxonomy nor the IFRS XBRL Taxonomy can be considered complete.  Both leave out important mathematical computations that need to be represented using XBRL Formula.
  5. Neither the US GAAP XBRL Taxonomy nor the IFRS XBRL Taxonomy represents "wider-narrower" associations.
  6. Neither the US GAAP nor IFRS XBRL Taxonomies follow the good practices guidance of the Seattle Method.
  7. Neither the US GAAP nor IFRS XBRL taxonomies are of the quality that could be used internally within an enterprise.
  8. There is currently no XBRL taxonomies that could be used by small and medium sized companies that wanted to leverage XBRL-based digital financial reporting for external general purpose financial reports or internal financial reports. This is not about meeting some regulator mandate or even generating XBRL-based reports; this is about making financial reporting processes better, faster, and/or cheaper.

And so, the current US GAAP and IFRS XBRL Taxonomies are not optimal.  Part of the reason for this experimentation is to learn how to do this right.  Here is a first prototype of an IFRS common practice XBRL taxonomy.


Here are 13 prototype base financial reporting schemes represented using XBRL. (See the numbered list).

Here is a prototype for AASB 1060 that provides the best idea of what those common practices XBRL-taxonomies that I will create would look like.

Comments

Post a Comment

Popular posts from this blog

Relational Knowledge Graph System (RKGS)

Image
Relational Knowledge Graph System (RKGS) is an interesting idea that combines the relational paradigm and the knowledge graph paradigm.  This documentation, Why RKGS , explains the idea. This gets even more interesting with the notion of "relational AI".  RelationalAI is described as follows by the company of the same name, Relational.ai : “RelationalAI is a cloud-based relational knowledge graph management system, with state of the art probabilistic processing and declarative reasoning at scale to make developing Data Applications a superpower for your business.” This notion of knowledge graphs represented in relational databases fits into my belief that knowledge graphs have two aspects: the expression SYNTAX and the logic of what is expressed or SEMANTICS. While the LOGIC of a knowledge graph is always the same regardless of technical syntax used to express that logic; there are many, many different technical syntaxes that can be used to represent a knowledge graph. There
Read more

Graph Hairball

Image
Knowledge graph system logic, the "things" and "relations between things" that  graph theory calls "vertices" (a.k.a. nodes, points, entities, things) and "edges" (a.k.a.  links, lines, relations, associations), looks like a big graph hairball as some people call it an example of which you can see here: Why?  This common view of a graph is because there has to be some "general view" of the information provided by the graph.  This is just like a general view of the information within a relational database is a table ; a set of ROWS and COLUMNS for exactly one table at a time. So what is interesting is that with a graph database the default view is everything in the graph of knowledge.  Whereas the default view of everything in a relational database is one table at a time. Further, it does not really matter whether the information that populates your knowledge graph comes from, say, CSV files, Excel, JSON, XBRL, RDF, PROLOG or whateve
Read more

PLATINUM Business Use Cases, Test Cases, Conformance Suite

Image
A brick wall is made of exactly two things: bricks, mortar. But a brick wall created by a master craftsman, or mason, and a brick wall created by a “weekend warrior” with no knowledge of masonry will be very different. Master craftsmen are created and that process takes time and effort. This blog post is a first prototype that brings several things together into one useful resource for business professionals.  It pulls together the human readable information of the Showcase of Reports   and the machine readable information of the Conformance Suite of XBRL-based Financial Reports Prepared using the Seattle Method .  Then, I want to incorporate the information found in these PLATINUM XBRL-based Financial Report Examples . The three resources can be useful and used independently; but they are even more useful when used together.  Business professionals really could not care a less about the technical details of getting some result that they want.  But technical professionals need to under
Read more