Digital Financial Reporting

AccountingToday reports in an article, AICPA CEO Melancon: CPA licensing under threat, that the American Institute of CPAs president and CEO Barry Melancon talked about the need for CPAs to learn new skills as hiring of accounting graduates has slowed and the CPA licensing model has come under threat in some states.

In the article, Melancon points out, “Hiring of accounting graduates over the last four years by public accounting firms is down 31 percent. Total hiring is basically flat and proportionally slightly down. If we don't find a way to put those other skill sets, predominantly technology, into the CPA Evolution, we're going to continue to see that equilibrium change.”

The article mentions two other important details.  First, it says "The AICPA has been working with the National Association of State Boards of Accountancy on an initiative called CPA Evolution to transform the CPA licensure model to teach more technology skills to CPAs."  Two or maybe three years ago, I went to the State Board of Accountancy in Washington state and told them the same thing.  They basically ignored me.

Second, the article talks about the AICPA's Dynamic Audit Solution initiative. Be sure to keep on top of that.  AI assisted audits are really a slam dunk.

So, where do you start?  I strongly suggest that the first step is to get some Computer Empathy to understand how computers work. This will help you understand the real potential impact of artificial intelligence, structured information, digital distributed ledgers, etc.

Analogy is a powerful cognitive mechanism that people use to make inferences and learn new abstractions.  Per the Stanford Encyclopedia of Philosophy, "An analogy is a comparison between two objects, or systems of objects, that highlights respects in which they are thought to be similar."

The video, How Drones Could Change the Shipping Industry, helps you understand the possible impact artificial intelligence, structured information, and distributed ledgers will have on accounting, reporting, auditing, and analysis.

Use your imagination. What analogies do you see?  Let me know.

The European Securities Market Authority (ESMA) has published its Strategy on Sustainable Finance.

The ESMA will place sustainability at the core of its activities by embedding Environmental, Social, and Governance (ESG) factors in its work. Other terms for ESG that have been used are sustainability reporting and triple bottom line.

Triple bottom line is a term that was coined in the 1990's by John Elkington. Basically it means that organizations should not be measured by financial performance along, but rather on financial performance, social performance, and environmental performance.  The ideas have been tuned over the past 30 years.

Key priorities per the ESMA include: 

Great job ESMA!

Someone made me aware of one of the most interesting ideas that I have heard about in a long time.  Smart Media Tokens (SMT) are characterized as a new way for publishers of information/knowledge to monetize their online contributions within a community using block chain technology.

Steem is said to be the first cryptocurrency that attempts to accurately and transparently reward an unbounded number of individuals who make subjective contributions to a community. Steemit is such a community.

This white paper written in 2017 seems to be the beginning of Steem. This white paper seems to be an updated version of that first white paper. And this STEEM bluepaper seems to be more business professional oriented.  This 5 minute video gives a good, quick overview of smart media tokens. This 2 minute video explains how smart media tokens work.

Here is what I am thinking.  I have pointed out I have created a new, modern approach to creating financial reports.  The approach requires thousands of machine-readable business rules to be created and generally, these rules need to be created by professional accountants.  But, they need tools to create those rules.  Validation software such as XBRL Cloud and Pesseract use such rules.  Companies creating reports need the machine-readable rules and the rules engines that can process the rules.  Data aggregators need the same machine-readable rules to extract information from reports.  AI assisted audit software needs these same machine-readable rules to help see of the XBRL-based reports were created correctly.

I could go on and on.  Basically, what I am pointing out is an ecosystem.  What if something like a smart media token (SMT) offered a way to reward professional accountants for their brain power, software vendors for their brain power, etc.

This is a really good way to take high cost incumbents, inept middlemen that don't add value, and others that do not add value out of the process of accounting, reporting, auditing, and analysis moving into the future.  If everything is standards based then everything that can be a commodity will become a commodity.  Those that truly do add value can add to the ecosystem.  Bye-bye vendor lockin.  You are in charge of your reputation.

Interesting stuff.  I signed up for Steem, here is my blog.  This is a link to all stories that use the keyword "xbrl".

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This is an excellent comparison of Medium and Steem as a blogging platform.

In his paper, Future Directions for Semantic Systems, John Sowa points out the following:

No one can predict what innovations will be discovered in the future, but commercially successful systems must satisfy two criteria: first, they must solve problems for which a large number of people need solutions; second, they must have automated and semi-automated methods for acquiring, analyzing, and organizing the required knowledge.

Hamed Mousavi and I created a working proof-of-concept that is a semantic system.  We call the software application Pesseract. You can download the software (requires Windows), fire it up, and give it a spin.  We created a bunch of demo scripts that you can walk through.

If you cannot or don't want to download the application, you can watch a set of videos that show the semantic system in action.

To get the semantic system to work, we had to create the "semantics".  Those semantics are in the form of information related to several financial reporting schemes represented in XBRL.  There is at least one commercially available software application that also uses those semantics, XBRL Cloud. There is at least one open source software application that uses these same ideas, XBRLQuery.com.

We have taken information from these three and other implementations to create a high-level logical conceptualization of a business report. Keep in mind that a financial report is a type of business report.  There have been several iterations of this logical conceptualization.  OMG's Standard Business Report Model (SBRM) is the most current version of that logical conceptualization.

All of this is proven to work.  I can also explain how it works. The document Special Theory of Machine-based Automated Communication of Semantic Information of Financial Statements explains how it all works.

The Digital Financial Reporting Manifesto explains why all this is useful.  While all of my metadata works and allows for these ideas to be explored and tested, the metadata is not sufficient to be a complete financial reporting scheme.  A lot more metadata is necessary to provide a complete system.

Whether there is enough existing metadata to begin enabling machine learning based approaches to help create new metadata is unclear.  I don't think that there is quite enough yet to semi-automated metadata creation.  But, I could be wrong.

The next step is to turn the working proof-of-concept into one or more products.