Example Regulatory Reporting Scheme Working Prototype: Common Elements of Financial Report

This blog post explains a completely new approach to regulatory reporting.  This prototype uses a very basic, simple example of a reporting scheme to keep this first example easy to explain.  See the "Additional Information" section below for more sophisticated report fragments.

This regulatory reporting scheme is created using the Seattle Method framework. To test the framework I created about 35 different reporting schemes. Here is the list which contains pointers to all reporting scheme metadata. Those 35 different reporting schemes were used to test the framework.

For this demonstration I will use the Common Elements of Financial Statement (Version 3) (Four Statement Model) prototype financial reporting scheme.  Imagine that as an example of a regulator reporting scheme.

Step 1 would be for a regulator to create and publish their reporting scheme using the XBRL global standard following the good practices specified by the Seattle Method.  That includes publishing all the necessary machine-readable rules specified by the Seattle Method to enable verification that submitted reports have been correctly created.

Step 2 would be for a regulated entity to create their report using any of the many software applications for creating XBRL-based digital financial reports.

Step 3 would be for the submission mechanism to verify that reports satisfy all published machine-readable reporting rules.

Step 4 would be to put the reported information into a repository that is private to the regulator or publicly available.

Step 5 would be for analysts to extract information from the report repository to automate many aspects of their analysis process.

Here is a video showing how easy it can be to create an XBRL-based digital financial report. Again, in this case I am using the Common Elements of Financial Statement (Version 3) in the video. Don't get hung up on the rather simple nature of the reporting scheme.  Again, see the "Additional Information" section for more sophisticated reporting schemes.

Note that different mechanisms can be used for creating a report.  Templates could be loaded from a reporting scheme; the reporting entity can manually modify the template(s); report facts can be pumped into the report using an API or Excel/JSON import. This video shows a combination of different creation approaches.

Additional Information:

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