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.
The CFA Institute paper which calls for broader and deeper use of structured data in financial reporting points out that to achieve the vision that paper articulates, accountants and auditors need increased education. I agree with that assessment of the CFA Institute.
The paper calls specifically for increased education in "technology and analytical methods". That is not very specific and I think it misses one very important skill. That skill is a discipline of philosophy, formal logic.
Also, there is a general movement going on to "get everyone to learn how to code". That notion is misguided. That is NOT what is needed. I am not the only one who believes this "learn to code" movement is misguided.
Besides, this Wired article, End of Code, has the sub title "Soon we won't program computers. We'll train them like dogs." That is a very succinct and accurate statement. But I do disagree with one thing Wired is saying. Business professionals will train software using business rules, not code. Financial reporting is not the sort of thing machine learning was designed for. So don't believe the snake oil salesmen who tell you otherwise.
Further, if you are judging what you have to know based on the current software that is available to create structured data and you don't consider the Law of Conservation of Complexity and the Law of Irreducible Complexity, then you are apt to reach the wrong conclusion as to what professional accountants and auditors even need to understand. Most structured data tools today expose far, far too much technology "stuff" to users of the software. That technical stuff will be burried far more deeply within software in the future.
What professional accountants and auditors need is to understand how computers work and how to control the workings of computers to accurately understand what computers are capable of doing and what they are not capable of doing. You want to get the correct training? Go test drive a Tesla. Literally. If you go try out the driver assist feature and then think about your experience, you will learn way more that if you learned how to code.
Professional accountants and auditors have the vast, vast majority of what they need to understand dialed in. Consider this question: how long do you think that it might take for a computer science professional to learn the domain of accounting and financial reporting?
What professional accountants and auditors need is between a 3 and 5 day class on how to communicate effectively with information technology professionals. This is a bit of the discipline of philosophy, specifically formal logic. It is also a bit of engineering, or specifically something like Six Sigma or Deming or systems theory. Professional accountants need to understand how to communicate effectively with information technology professionals to help technology professionals build the software they really need and to be able to test that software to see that it is working correctly.
Additionally, accountants and auditors need to re-understand that they think differently than non-accountants. The section A Very Brief History of Accounting will help them recall Friar Luca Pacioli's invention of double-entry bookkeeping and how it was engineered to detect errors and fraud. Don't make the mistake of taking this feature for granted or even worse, forgetting about it!
What professional accountants and auditors need to understand is the basics of how computers actually work and the mechanisms used to control a computer. I understand this because I have a degree in accounting and am a trained auditor. I also have a significant amount of formal training in information systems. As it happens, I also received training in formal logic as an under graduate. When working toward my graduate degree I studied Deming. That combination was pure chance.
I got the XBRL ball rolling. I invested in understanding XBRL by helping to create it. Then, I spend the next 15 years trying to figure out how to get XBRL to work the way I know accountants and auditors need XBRL to work. Along the way I took lots of notes. I took what I learned; organized, summarized and synthesized that information as best that I can at this point. This is what I came up with:
- Conceptual Overview of an XBRL-based Structured Digital Financial Report: Begin with the end in mind as the Seven Habits of Highly Effective People points out. What is the objective? What exactly is "structured data". The CFA Institute paper does an excellent of laying out their vision, but they don't provide a lot of detail as to what structured data is or how to make it work.
- Knowledge Engineering Basics for Accounting Professionals: This document helps you sort of what computers do, what they can't do, and how to get computers to do what you want. Computers work using the rules of formal logic, which is a discipline of philosophy which was invented in about 450 BC. Yes, you need some philosophy training to use computers appropriately! (This is just an outline, check back as I will improve this document over the coming weeks.)
- Comprehensive Introduction to Business Rules for Professional Accountants: Business rules guide, control, suggest or otherwise influence behavior. Accountants and auditors understand human-readable rules that you get out of books. They need to understand machine-readable rules and the sorts of rules machines need.
- Comprehensive Introduction to Intelligent Software Agents for Professional Accountants: Intelligent software agents is how work will be automated. This helps you understand what an intelligent software agent is, how they work, what it takes to control such agents, and other information about using these potentially helpful creatures. It also helps you understand their limitations.
- Financial Report Semantics and Dynamics Theory: This theory provides a conceptual model of the mechanics of a digital financial report. It explains the mechanics of the machine. It helps you see the difference between the mechanics of a digital financial report and the stuff that goes into the report which is subjective and needs the help of a professional accountant to determine.
- How XBRL Works: This five minute video helps you understand the difference between structured information and unstructured information. It helps you see how computers can address specific information within a structured digital financial report.
If anyone has better information, please send it my way. I always work to improve. I like to reach conclusions based on evidence and facts, not based on unsupported subjective opinion.
There are a lot more details if you want them, but that the information above is really the essence of what you need to get your head around the future of financial reporting which is digital financial reporting. With 3 to 5 days of work, professional accountants and auditors will understand how to get their heads around digital. Digital is not software or even a technology. Digital is a mindset.
Accountants tend to try and understand XBRL from the perspective of what they are doing today and what they understand today. That will not work. Structured information is a transformational change, it is not an incremental change.
And don't make the mistake of thinking that accountants and auditors are in this boat alone. Every business professional is in this same boat of needing to understand digital. In fact, most information technology professionals are in this boat also. Most information technology professionals are fixated on relational databases and don't understand how to leverage business rules appropriately.
Many accountants working with XBRL-based stuctured digital financial reports are actually ahead of the curve, not behind it. Look at the first graphic on this page; anyone who creates 90% or more of their XBRL-based public company filings to the SEC is on the right track.
Become knowledgeable enough to differentiate a snake oil salesmen from someone that actually has something useful. Might save you a lot of money and frustration.
There is a tremendous amount of hype and misinformation when it comes to what software is capable of doing and what is necessary to make software actually achieve the desired results. A really good way to cut through this hype and misinformation is to dig into the details just a little to understand how software actually works.
In that spirit I created the document Comprehensive Introduction to Intelligent Software Agents for Professional Accountants (DRAFT). Have a look at the document; if you have any feedback or questions please let me know.
Here is an excellent NPR story related to a different domain (i.e not financial reporting) that can give you an idea of the sort of hype and misinformation you can run into. That domain is "autonomous vehicles". Even the headline is misleading, Uber to Roll Out Self-Driving Cars in Pittsburgh. Listen to the story.
Notice first that the "self-driving" cars are really not autonomous. Uber will have a human in each car. What's the point? Are they saving anything by investing in creating the driverless car only to keep a human in the passenger seat as a safety net if something goes wrong? Sure they are. They are experimenting and trying to perfect the system. If they can make that work, Uber can save a lot of money in driver salaries.
Second, notice how you have three different predictions as to when this will actually work: couple of years, 10 years, 60 years. Who is right? Well, that depends how you define "autonomous vehicle".
On the other hand, go test drive a Tesla. Use the driver assist feature. Notice how useful that feature is. But then again, if you don't employ the feature properly, bad things happen. The point here is that setting the correct expectation, or goal, as to what software can do for you is important.
Finally, information technology people like to push things like "machine-learning" and "deep learning" and the power of "neural networks". But these people don't understand how domains such as financial reporting actually work. Not only can these sorts of approaches very expensive, you have to be careful about the results that you actually get. I repeat this statement from the blog post above, note the statement "high tolerance for error":
What Applications Should Neural Networks Be Used For?
Neural networks are universal approximators, and they work best if the system you are using them to model has a high tolerance to error. One would therefore not be advised to use a neural network to balance one's cheque book! However they work very well for:
•capturing associations or discovering regularities within a set of patterns;
•where the volume, number of variables or diversity of the data is very great;
•the relationships between variables are vaguely understood; or,
•the relationships are difficult to describe adequately with conventional approaches.
Be very careful when the snake oil salesman knocks at the door. The best defence is being an informed buyer. Reading that introduction to intelligent software agents can help make you an informed buyer, rather than an ignorant victim of hype and misinformation.
Now, this is not to say that these technologies don't have applicability to financial reporting. That is not what I am saying. They do. In terms of analyzing a financial report, they can be very helpful. But when creating a financial report, they are not necessary.
If you really want to understand this stuff, please read the following documents in addition to the one above:
- Conceptual Overview of an XBRL-based Structured Digital Financial Report: this document provides the vision.
- Knowledge Engineering Basics for Accounting Professionals: this helps you understand important moving pieces and the capabilities of computers; this is an outline at the moment but will be turned into a narrative (check back).
- Comprehensive Introduction to Business Rules for Professional Accountants: this points out the important role business rules play in making software perform work.
- Financial Report Semantics and Dynamics Theory: this helps you understand the conceptual model of a digital financial report.
- How XBRL Works: this video helps you see, in detail, why structured information makes all this work.
Over estimating the capabilities software can deliver is a mistake. But it is also a mistake to under estimate the work software applications will perform. As structured information is use more and more, understanding all of this will be of increasing importance.
In a paper, Data and Technology: Transforming the Financial Information Landscape, the CFA Institute outlines their vision of a broader and deeper use of structured data in financial reporting. The paper, which looks at what the CFA Instutute calls the "currently inefficient system" of financial reporting from end-to-end.
In the paper, the CFA Institute calls for structuring data earlier:
"Structuring data early in the process would not only benefit companies but would also allow auditors to use audit data analytics to make the audit more efficient and potentially provide users with a better quality and greater granularity of financial information with greater reporting frequency and possibly a higher level of assurance."
The paper can be purchased from Amazon.com for $9.99. It is worth purchasing and reading.
To better understand the efficiencies of structured data of an XBRL-based digital financial report, see my Conceptual Overview of an XBRL-based, Structured Digital Financial Report.
But what about all those quality issues in XBRL-based public company financial filings to the SEC? Employ business rules correctly and not only will the quality problems go away; THAT is how the effeciencies the CFA Institute mentions will be realized. The benefits of structured data are real! When you understand the details, you understand that structured data can work.
Business rules arise from the best practices of knowledgeable business professionals. A business rule is a rule that describes, defines, guides, controls, suggests, influences or otherwise constrains some aspect of knowledge or structure within some business domain.
Professional accountants work with business rules every day and the tend to not realize that they do so. Most of the business rules are available only in human-readable form. With more and more information being made available in structured form, such as XBRL-based public company financial reports, machine-readable business rules are becoming increasingly important.
The document Comprehensive Introduction to Business Rules for Professional Accountants helps professional accountants and other business professionals get their heads around business rules.
In his Harvard Business Review article, Why Technologists Should Think Like Biologists, Samuel Arbesman points out that one way they learn about a system is by examining when that thing goes wrong. That is one way that I learned about XBRL-based digital financial reports. By looking at basic, fundamental accounting concept relations that were not working as I would have expected.
This short article is worth reading.