The Story of Our New Language

(UPDATE: President Biden did, in fact, sign the Financial Data and Transparency Act into law on December 23, 2022 as part of the National Defense Authorization Act.  Here is the actual text of the bill that was passed.)

In July of 1998 a meeting of the AICPA High Tech Task Force took place in Sedona, Arizona.  The purpose of the meeting was to discuss an idea that I had to represent financial reports in machine readable form using the Extensible Markup Language (XML) which was published by the W3C earlier that year.

At the meeting were (pictured below in order) John Woodburn (The Woodburn Group), Dianne Spencer (Deloitte & Touche LLP), Charles Hoffman (Knight, Vale and Gregory), Mike Harnish (Dickinson Wright et al), Wayne Harding (Great Plains Software), Chris Reimel (N.J. Department of Labor), Barbara Vigilante (AICPA), and Karen Waller (AICPA).

As a result of that meeting, the industry standard Extensible Business Reporting Language (XBRL) was created and XBRL International was established as its governing body.  The story of how XBRL was created is chronicled in this document published by the American Institute of Certified Public Accountants (AICPA), The Story of Our New Language.

Today, per XBRL International, there are 213 implementations of XBRL-based reporting systems in 60 countries around the world.

Add about 10 more to that list from the United States of America.  Yesterday, the Financial Data Transparency Act (FDTA) was passed by the U.S. Congress as part of the National Defense Authorization Act for Fiscal Year 2023.  See page 2445 for Title LVIII Financial Data and  Transparency and page 2462 Data Transparency Relating to Municipal Securities.

What this seems to mean is that the Federal Government is going all in on digital machine readable financial reporting.  The FDTA says that for all "covered agencies" the "financial entities the jurisdiction of the covered agency" will be required to report standards based machine readable information.  While all these groups of entities are not covered by this act; this seems to mean that the following will eventually be covered:

  • About 7,000 public companies that are regulated by the Securities and Exchange Commission. (already in place)
  • About  110,000 state and local governments that issue municipal securities and it seems will be regulated by the Securities and Exchange Commission; they currently report to the U.S. Census Bureau.
  • About 6,000 national banks regulated by the FDIC (already in place).
  • About 5,000 credit unions regulated by the National Credit Union Administration.
  • About 350,000 not-for-profit organizations that receive grants from the Federal government and report information to the Treasury Department.
  • About 850,000 pension plans that report to the Department of Labor. (does not seem to be covered by this current law)
  • Unknown amount of entities that report to the Office of the Comptroller of the Currency.
  • Unknown amount of entities that report to the Bureau of Consumer Financial Protection.
  • Unknown amount of entities that report to the Federal Reserve.
  • Unknown amount of entities that report to the Federal Housing Finance Authority.

In addition, I predict that private equity will also be reporting using machine readable digital reports sometime in the near future. The paper, An Economic Case for Transparency in Private Equity: Data Science, Interest Alignment and Organic Finance, suggests this.  And finally, I predict that the approximately 25 million small and medium sized entities in the United States will be creating digital financial reports within 5 to 10 years, perhaps less.

Digital financial reporting is a once in 500 years change.  This change, a paradigm shift really, is happening now and it was fun being part of making this a reality.








The Story of Our New Language

For more information about XBRL:

For more information about the Financial Data Transparency Act:
  • International Organization of Securities Commissions (IOSCO)
  • Australian Securities and Investments Commission (ASIC)
  • United Kingdom's Financial Conduct Authority (FCA)
  • Canadian Securities Administrators (CSA)
  • Japan Financial Services Agency (FSA)
  • China Securities Regulatory Commission (CSRC)
  • Brazil's Securities and Exchange Commission (CVM)
  • India's Ministry of Corporate Affairs (MCA)
  • South Africa's Companies and Intellectual Property Commission (CIPC)
  • Russia's Federal Financial Markets Service (FFMS)
  • Mexico's National Banking and Securities Commission (CNBV)
  • Turkey's Capital Markets Board (CMB)
  • Saudi Arabia's Capital Market Authority (CMA)
  • United Arab Emirates' Securities and Commodities Authority (SCA)
  • Indonesia's Financial Services Authority (OJK)
  • Vietnam's State Securities Commission (SSC)
  • Thailand's Securities and Exchange Commission (SEC)
  • Philippines' Securities and Exchange Commission (SEC)
  • (Other projects, list of 213 projects provided by XBRL International at the time of this writing)

Comments

Post a Comment

Popular posts from this blog

Getting Started with Auditchain Luca (now called Luca Suite)

Image
(Note that a newer, production version as opposed to only the development version , of Luca Suite is available) The Innovator's Dilemma points out that disruptive innovations often look like toys that are doing everything wrong. Auditchain Luca , which is part of the Auditchain Suite , is a unique approach to creating a knowledge graph .  To experience using Auditchain Luca, have a look at the Getting Started with Auditchain Luca instructions. Be sure to grab the Excel and JSON import files used for this getting started exercise.   This getting started exercise uses one of several different approaches to getting information into a tool for constructing and viewing professional quality knowledge graphs .  Additional getting started guides will be made available over time. Auditchain Luca might not make sense to you if you don't understand the paradigm shift that is occurring and if you have not shifted your mental map. For the next step in your journey, consider t...
Read more

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

Professional System for Creating Financial Reports Leveraging Knowledge Graphs

Image
The document Professional System for Creating Financial Reports Leveraging Knowledge Graphs explains a new approach, a new paradigm, for creating financial reports.  The document provides a practical, nontechnical description of a professional system for creating provably high-quality financial reports where the report creator is using financial reporting schemes (such as US GAAP and IFRS) where report creator is permitted to modify the report model which leverages global standard knowledge graphs represented using XBRL. This new approach is useful, it is highly novel, and the details were highly complicated to pull together.  This is certainly not an incremental innovation.  It is definitely a disruptive innovation and it could very well be a foundational innovation. You can decide which for yourself. Foundational technologies have two dimensions that need to be considered: novelty and complexity. The more novel the technology is, the more effort needed to ensure users ...
Read more