Digital Financial Reporting

The book, Digital Transformation at Scale : Why the Strategy Is Delivery, by Andrew Greenway, is a guide to building a digital institution.  Here is a description of the book:

Organisations that grew up on the web have changed our attitude to the services we rely on every day. We expect them to work, be simple, cheap or free. They have done this by perfecting new technologies, practices, cultures and business models. However, organizations founded before the Internet aren't keeping pace - despite spending millions on IT. Faced with the digital revolution, many people working in large organisations instinctively see its consequences as another layer of complexity. To some of them, 'digital' promises a better fax machine, a quicker horse, a brighter candle. In fact, digital is about applying the culture, practices, business models and technologies of the Internet era to respond to people's raised expectations. It is not a new function. It is not even a new way of running the existing functions of an organisation, whether those are IT or communications. It is a new way of running organisations. A successful digital transformation makes it possible not only to deliver products and services that are simpler, cheaper and better, but for the organisation as a whole to operate effectively in the online era.

The book seems to have been written by consultants that work for Public Digital.

Many years ago I ran across Scratch and Blockly that is based on the ideas of Scratch. I used the notion of a block to manage the structures within an XBRL-based financial report.

Seems like someone else has a similar idea for legal related applications which they called Legal Blawx. This seems to be a free download on GitHub. This Ted Talk explains the ideas behind what is going on here.

To understand Blawx, I would recommended reading Blawx: Rules as Code Demonstration. Also, this YouTube video is helpful in understanding, Encoding Rocks Paper Scissors in Blawx.com.

The working proof of concept is a combination of Flora-2 (a.k.a. ErgoLight), an open source declarative logic programming language, and Blockly, a Google platform for developing visual coding environments. Blockly is a descendent of Scratch, a tool designed to teach kids how to code.

Here is more information on rules as code: 

• Rules as Code
• Working Blawx Proof of Concept
• Blawx Tutorials
• Source Code for above working proof of concept
• Ted Talk

Why does this matter? Computational Professional Services. Microsoft has created something similar to Blockly called Make Code. (This is an ONLINE version of Make Code that you can use.) Imagine a logic driven interface, driven by metalogic and a metamodel.  See this. See this.

Should accountants learn to code?  Here, an AICPA article Should Accounting Students Learn to Code? tries to make the case that there are advantages.  Similarly lawyers are asking the same question.  This article, To Code or Not to Code: should lawyers learn to code? You could generalize this question and ask, "Should professional services providers learn to code?"

Here are my personal observations.  First, I know how to code.  I recall that my first programming class was FORTRAN.  That may have helped me; but the thing that I believed perhaps help me the most was a Formal Logic philosophy class that I took in community college.

I did not just "learn to code" and then my accounting career took off.  Someone referred to me as a "dinker" once. She was right.  I "dink" around, trying things.  How did I have time to dink around?  Well, I made the time.  Something interesting here is that when I was with Price Waterhouse I was one of the most productive staff in our office.  I moved to another smaller CPA firm and I was also the most productive person there also.  Was there some sort of connection between my "dinking" around and being productive?  Dinking around builds productive capacity, but takes away from actually producing.  Producing contributes to production.  Throughout my careeer I was always flipping between producing and building productive capacity.

"Learning to code" is not what is necessary.  What is necessary for some professional accountants is:

• To understand how to think logically (formally).
• To understand how to communicate with information technology professionals.
• To understand how to solve problems and improve processes.

If I had it to do over again, I would go to Stanford University and get into their Symbolic Systems Program. That program did not even exist when I went to college, it was created in 1986 (I graduated from college in 1982).  Also, you might want to check out declarative logic programming.

In my view, "learning to code" is not necessary for every accountant.  Understanding how to code provides certain advantages for certain advantages, similar to how understanding a foreign language can provide certain advantages.  What is important is not just ability, but also diversity.  There is no one right answer.

Audit, reporting, accounting, and analysis all have their issues and can be improved.

Technologies such as structured machine-readable information (such as XBRL), digital distributed ledgers, knowledge based systems, and artificial intelligence offers an unprecedented opportunity to create what I am calling Computational Professional Services.

Some people call this "smart regulation". Others call it "algorithmic regulation".  Still others us the term "rules as code". Some use the term "robo cop". Deloitte seems to use the term "finance factory".  The SEC has a vision. "Continuous audit" and "continuous reporting" fit into computational professional services.  Another term for all this is "finance transformation".

But, whatever you call it; many of the repetitive, monotonous, routine, mechanical, boring tasks and processes related to accounting, reporting, auditing, and analysis be performed by machines which will free up humans to do more interesting work. This transformation is about talent, not technology. (This begs the question as to whether accountants should learn to code)

Professional services is about rearranging abstract symbols that represent information and knowledge. Computers can help perform these tasks and processes much like a calculator helps accountants do math.

So how do you get computational professional services to work effectively?  Well, XBRL-based digital financial reporting to the SEC and ESMA offers a bunch of clues if you know where to look.  Check out the document on that first link.

Here is how you implement computational professional services.

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AI for Services (Full Report 2020)

Center for Computational Thinking

Shawn Riley posted this article Machine Learning vs Machine Understanding which helps one understand the capabilities of artificial intelligence.

Here are all of Shawn's articles.

This video is particularly good at differentiating knowledge engineering and machine learning.