BLOG:  Digital Financial Reporting

This is a blog for information relating to digital financial reporting.  It is for innovators and early adopters who are ushering in a new era of digital financial reporting.

Much of the information contained in this blog is summarized, condensed, better organized and articulated in my book XBRL for Dummies and in the three documents on this digital financial reporting page.

Putting the Expertise into an XBRL-based Knowledge Based System for Creating Financial Reports

As someone put it, rather than "paving the goat path" and replicating existing inefficiencies related to old-school paper-based reporting in XBRL-based digital financial reporting software; we chose a different path.

One type of practical knowledge is know-how; how to accomplish something.

Creating a knowledge based system involves the transformation of machine-readable instructions in such a way as to explain to a machine how a system works and how to make a system work the way you want that system to work.

Then, brick-by-brick, much like building a house, business domain experts and software engineers can create tools that automate certain types of tasks in that process. Humans encode information, represent knowledge, and share meaning using machine-readable patterns, languages, and logic. That will be the way an increasing number of work tasks will be performed in the Digital Age of accounting, reporting, and auditing.  The result will be more efficient processes.

A software engineer and I tested the feasibility of creating an expert system for creating XBRL-based structured financial reports to prove the concept.  We are making that software available free of charge until March 31, 2018.

We also provided information about the techniques we used to create this working proof of concept.  The document, Putting the Expertise into an XBRL-based Knowledge Based System for Creating Financial Reports, provides this information.

We will be making this software available free of charge to filing agents, software vendors, accountants, and public companies as part of my Campaign to Improve Disclosure Quality of XBRL-based Public Company Financial Reports Submitted to the SEC.  This is an excellent opportunity to understand the explicit knowledge and the tacit knowledge needed, the know how, to build such a system and how that system needs to work in order to be considered useful by professional accountants.

The software engineer that is collaborating with me on this and his colleagues won the prize of 9th XBRL Global Academic Competition 2008-2009, which was held in Bryant University, USA.

In addition, another software vendor has implemented these ideas in a product that is commercially available.  This is explained in the document, Process for Verifying Quality of an XBRL-based Financial Report, which helps one understand how to create a reliable, repeatable process for creating quality XBRL-based financial reports.

We believe this will be an industry changing technology, disrupting the process of creating financial reports. Most people don't recognize this yet because they don't understand the paradigm shift that is occurring. But, we do.

If you don't want to follow the same old goat path, read PART 1 to understand the general approach to what we are doing and PART 2 to better understand the conceptual model of an intelligent XBRL-based digital financial report.

Posted on Sunday, November 19, 2017 at 01:49PM by Registered CommenterCharlie in | CommentsPost a Comment | EmailEmail | PrintPrint

Will Accountants Be Replaced By Robots (And What Can You Do About It)?

This is an excellent video, Will Accountants Be Replaced By Robots (And What Can You Do About It)? It is an hour and six minutes long, so a bit of an investment, but it is worth watching.  Interestingly, it was published in 2015.

The most interesting thing about this video to me was this person's statement that accountants should control the business logic of systems, not the IT department.  No system should be a "black box" or require the accounting department to rely on the IT department to change business logic or processes.

I completely agree with that statement.  As artificial ingelligence us employed to automate more and more things over the next 30 years, professional accountants need to take back what they gave away during the last 50 years.  Understanding business logic and tools for working with that logic are key.

Accounting existed before writing and numbers, invented 10,000 years ago.  Like writing and numbers, computers are just a tool.  A very powerful tool, but a tool none-the-less.  Do you really want the tool makers controlling your craft?

 

Posted on Tuesday, November 14, 2017 at 02:30PM by Registered CommenterCharlie in | CommentsPost a Comment | EmailEmail | PrintPrint

WIRED: Data is the New Oil of the Digital Economy

In his WIRED article Data is the New Oil of the Digital Economy, Joris Toonders points out the value of data in today's digital age for those that learn to extract and harvest that data.  But there is one thing that is even more valuable than data.  Metadata.

Fortune has a similar article, Data is the New Oil, by Jonathan Vanian. The tag line of that article is, "Artificial intelligence is only as good as the data it crunches."

While it is true that data is important; metadata is even more important.  The key ingredient in a knowledge based system is domain knowledge.  Metadata organizes knowledge.  What is not in dispute is the need for a "thick metadata layer" and the benefits of that metadata in terms of getting a computer to be able to perform useful and meaningful work. This is simply science.

But what is sometimes disputed, it seems, is how to most effectively and efficiently get that thick metadata layer.  There are two basic approaches to getting this metadata layer:

  • Have the computer figure out what the metadata is: This approach uses artificial intelligence, machine learning, and other high-tech approaches to detecting patterns and figuring out the metadata.
  • Tell the computer what the metadata is: This approach leverages business domain experts and knowledge engineers to piece together the metadata so that the metadata becomes available.

 

And this is not an "either/or" question.  Both automated and manual knowledge acquisition methods can be used.  The question is how to best combined the two approaches to most effectively and efficiently get the important metadata you need.

Because knowledge acquisition can be slow and tedious, much of the future of artificial intelligence and expert systems depends on breaking the knowledge acquisition bottleneck and in codifying and representing a large knowledge infrastructure using automation. But, domain professionals are still going to need to participate.  And to participate, they need to understand knowledge and knowledge science.

So how do you do that?  Where do you even start?  Does this mean you have to get completely retrained?  No.  You only need to learn some important fundamentals and everything will fall into place. 

You can start here, Introduction to Knowledge Engineering for Professional Accountants.  Once you read that, you will understand that there are a few additional pieces, which can all be found in PART 1 - Foundation for Understanding: Background, Framework, Theory, Principles.

I figure there is about 187 pages of information that professional accountants need to understand in order to be well positioned for the digital age of accounting and reporting.

Posted on Tuesday, October 31, 2017 at 07:08AM by Registered CommenterCharlie in | CommentsPost a Comment | EmailEmail | PrintPrint

Hashgraph: An Alternative to Blockchain for Distributed Ledgers?

I thought that blockchain was the only way to build distributed ledgers.  Seems like there is a new technology: hashgraph.  This article, Blockchain Just Became Obsolete: the Future is Hashgraph, helps you understand the difference between blockchain and hashgraph.  In particular, this 10 minute video is very helpful.

Remember that a distributed ledgar is an application or a use case.  Blockchain and hashgraph are technologies that are used to implement distributed ledgers.

Posted on Saturday, October 28, 2017 at 06:27AM by Registered CommenterCharlie in | CommentsPost a Comment | EmailEmail | PrintPrint

Conceptual Legos and the Universe of Discourse

A significant problem that professional accountants have with XBRL is that they don't understand the moving pieces of the conceptual model, the "Conceptual Legos" that make up the pieces of an XBRL-based digital financial report.

If you don't understand the higher-level conceptual model then the model is defined in solely syntactic terms and as such do not have any meaning until they are given some interpretation.  That interpretation is the semantics of the model.

How hard is it for you to interpret the information in the graphic below? (Click the image, and a larger view will be provided.)  It is probably pretty easy for either accountants or even non-accountants to interpret that information.  That graphic is driven by 100% pure XBRL.  Now, the application processing the information is driven by some additional information about business reports, the multidimensional model. That helps software render the information.  The multidimensional model provides information that gets things into the right rows, columns, and cells.

(Click image for larger view)

Now, the report fragment above happens to be a disclosure of the goodwill roll forward, the changes in goodwill from each balance sheet beginning balance to each ending balance.

Not surprisingly, reports contain lots of report fragments.  Those report fragments represent lots of different disclosures.  Many of those disclosures are roll forwards.  Others are roll ups.  I gave the terms "roll forward" and "roll up" and similar patterns in the organization of reported disclosures a name; I call them concept arrangement patterns.

If you scan this document that contains descriptions of about 65 or so financial disclosures, you will see lots of different roll forwards, roll ups, and other concept arrangement patterns. If you look at each of those disclosures and the one shown above, you see cells colored GREEN which represents a mathematical computation.  Every roll forward actually mathematically rolls forward.  That is shown be the GREEN cells in the last row of that disclosure.  This particular roll forward also cross-casts shown by the other GREEN cells.  I gave this cross-cast a name also, I call it a member arrangement pattern.

I documented all these terms that I refer to in this Introduction to the Conceptual Model of a Digital Financial Report.

A Universe of Discourse is the set of all things under consideration during a discussion, examination, or study.

A universe of discourse is also the set of all objects or entities that is defined by a conceptual model.  XBRL-based digital financial reporting is NOT "conceptually promiscuous"; you simply cannot just add new pieces to the conceptual model.  Now, don't get confused here.  The conceptual model is the shape of the information you put into the model.  Remember, the same XBRL technical syntax can be used to define both US GAAP and IFRS financial reporting schemes.  US GAAP and/or IFRS concepts (and other stuff) is what goes INTO the conceptual model.  US GAAP and IFRS share the same business report and financial report conceptual model.

Now, you don't want all this to be a mess and you want a consistent interpretation of the conceptual model, so you define rules.  Why?  Because rules prevent anarchy.  See XBRL-based digital financial reporting principle #3: "Anarchy is defined as 'a situation of confusion and wild behavior in which the people in a country, group, organization, etc., are not controlled by rules or laws.'  Rules prevent anarchy."

Rules assert knowledge.  For example, "Assets = Liabilities and Equity" (i.e. the accounting equation) is both a rule and knowledge.  Constraints are restrictions on existing knowledge. Constraints can be used to detect incomplete information. Constraints can be used to check knowledge for inconsistencies and contradictions.  Rules all follow the same rules of logic. 

The rules of logic are a common denominator for a universe of discourse, or sometimes referred to as a domain. Business professionals interact with the conceptual model using the semantic level of these "Conceptual Legos" logical pieces software applications expose that are understandable by the user of the software system.  Business professionals don't interact with the technical syntax.

The system is not a "black box", rather the system is transparent do that the business professional using the system and understands what the system is doing. 

Digital financial reporting requires that every business user of the system share the same universe of discourse, the same fundamental conceptual model, and the same logical rules.  The goal is that every interpretation of the conceptual model is consistent with the intended interpretation of the conceptual model.  The conceptual model is formal, the conceptual model is definable, and the conceptual model has a finite set of shapes.

When a software developer puts all these pieces together correctly, what do you get?  You get easy to use software and zero defect digital financial reports. Software is easy to use because it is simple.  Not simplistic, simple.  Simple means you work hard to keep complexity to a minimum.  See the Law of Conservation of Complexity.  Reports don't have defects because humans augmented by machines that leverage rules watch over the creation of the report.

Here is an example of such software. That is just a robust proof of concept to test all these ideas. More software is on the way!

Pretty good stuff, huh!  Well, I cannot take any credit for it. These ideas come from Blockly which came from Scratch. I am simply applying those ideas to financial reports.

Posted on Thursday, October 26, 2017 at 12:54PM by Registered CommenterCharlie | CommentsPost a Comment | EmailEmail | PrintPrint
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