BLOG: Digital Financial Reporting
This is a blog for information relating to digital financial reporting. This blog is basically my "lab notebook" for experimenting and learning about XBRL-based digital financial reporting. This is my brain storming platform. This is where I think out loud (i.e. publicly) about digital financial reporting. This information is for innovators and early adopters who are ushering in a new era of accounting, reporting, auditing, and analysis in a digital environment.
Much of the information contained in this blog is synthasized, summarized, condensed, better organized and articulated in my book XBRL for Dummies and in the chapters of Intelligent XBRL-based Digital Financial Reporting. If you have any questions, feel free to contact me.
Entries from June 16, 2019 - June 22, 2019
Federal Energy Regulatory Commission (FERC) Adopting XBRL
The U.S. Federal Energy Regulatory Commission (FERC) announced that they are adopting XBRL for utilities reporting. See the final rule for more information.




XBRL Taxonomy Information Retrieval
Software vendors are providing a pretty poor level of functionality when it comes to finding information within an XBRL financial reporting taxonomy. What is the state-of-the-art? Text search.
But I think there is a significantly better way, so I created this prototype to brainstorm and solidify my ideas. I then created this prototype wizard. This is a web service where you provide an element name and it returns information for the requested report element name. This is the same information in machine-readable form.
But this is the best working prototype that I have for now. That is for US GAAP, it does not incorporate the more advanced graph-type searching. But, what this will allow me to do is communicate with software engineers and others better.
This prototype combines a bunch of things together and has a nicer user interface.
Not sure where to put these roll up relations. Ah! I just had an idea.
The idea is that the search would leverage metadata and other information in order to provide a significantly more precise information retrial mechanism.
So the US GAAP XBRL Taxonomy has 17,077 elements. That is a lot to work with. But, you can break that full set into lots of different groupings. For example, those 17,077 elements are comprised of:
- 325 Tables
- 251 Axis
- 1,783 Members
- 330 LineItems
- 2,537 Abstracts
- 183 Level 1 Note Text Blocks
- 311 Level 2 Policy Text Blocks
- 474 Level 3 Disclosure Text Blocks
- 10,883 Concepts
Further, some of those groupings are still quite large so you can break them down by data type, period type. balance type, authoritative reference, etc.
If you did a raw text search on say "Cash" (you can try that here) you get 552 hits. Somewhat helpful, but not quite what is needed.
But what if you could do a search and specify:
- The concept contains the text string "Cash".
- It relates to ASC topic "230"
- You want only concepts
- The concept is a "credit" and has a period type of "duration"
- The concept is monetary in nature.
- And it relates to the disclosure "CashFlowStatement"
I think you get the idea. Lots of different ways to specify what you might be looking for. Financial reporting concepts and terms, such as the US GAAP, are filled with a rich set of relations. If you put that information into machine-readable terms, then the machines can perform what seems like magic.




McKinsey: An Executive's Guide to AI
McKinsey provides An Executive's Guide to AI:
Staying ahead in the accelerating artificial-intelligence race requires executives to make nimble, informed decisions about where and how to employ AI in their business. One way to prepare to act quickly: know the AI essentials presented in this guide.
Propositions and Inference
Artificial Intelligence: Foundations of Computational Agents, 2nd Edition, by David L. Poole and Alan K. Mackworth is an excellent resource and freely available online.
The resource methodically and precisely explains the details of artificial intelligence in understandable terms.
In particular, I found the chapter on Propositions and Inference quite helpful.



