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.
Are you an expert of the past? Or, do you anticipate the future? Technology disruption is part of every day life these days. Disruption is good for small companies because it is small companies that generally innovates best.
Open innovation is essentially inter-company cooperation in research and development. The term was promoted by Henry Chesbrough and is described in more detail as:
Open innovation is a paradigm that assumes that firms can and should use external ideas as well as internal ideas, and internal and external paths to market, as the firms look to advance their technology”. Alternatively, it is "innovating with partners by sharing risk and sharing reward." The boundaries between a firm and its environment have become more permeable; innovations can easily transfer inward and outward.
Open innovation is further explained in these videos:
- Open Innovation 02 - What is “open innovation"? (8 minutes)
- Three things I learned about disruptive innovation as an UberX driver, Ted Graham (10 minutes)
- TedTalk: Charles Leadbeater: The era of open innovation (20 minutes)
You want to be a disruptor. Disruptive innovation changes markets. The reward is highest where the uncertaintly and risk is the highest.
Don't listen to the experts of the past. If you want to disrupt the financial reporting market, here is informationthat will help you make sure you build the right products and solutions. Bolt-on solutions to existing inefficient processes is not innovation. Digital financial reporting will cause a transformation.
In a prior blog post I mentioned a statement Barack Obama made in an interview with Wired magazine related to artificial intelligence. (yes, the president of the United States discussing artificial intelligence) The president made the following statement about self-driving cars:
"There are gonna be a bunch of choices that you have to make, the classic problem being: If the car is driving, you can swerve to avoid hitting a pedestrian, but then you might hit a wall and kill yourself. It's a moral decision, and who's setting up those rules?"
This statement which relates to self-driving cars points out two things that accounting professionals and other business professionals need to consider when thinking about XBRL-based digital financial reports:
- WHO: who writes the rules, the logic, which software follows,
- HOW: how do you write those rules and put them into machine-readable form and get all this to work reliably?
Think about that statement. Who writes the rules that makes software go? How, exactly, do you make the software work reliably, predictably, safely?
Computers are machines. In the past, machines were mechanical and worked using hardware. Gears, levers, etc. The gears, levers and other hardware were logically linked together. Computers are really not that different from other machines except for one thing. Software.
What software means is that you can adjust how the machine works dynamically by flipping bits.
But you still need to have logical and well reasoned software to flip those bits and get the computer application to work the way you want it to work. If you have standard problem solving logic, such as ISO/IEC standard Common Logic, then software will be interoperable with other software. No magic. Deliberate, conscious, skillful execution is what makes this work. That is the HOW.
This is what problem solving logic is all about. I explained my understanding of all this in a document, Comprehensive Introduction to the Notion of Problem Solving Logic for Professional Accountants. Check the document out and learn a few skills that help you thrive in the digital age.
In a Wired article; Barack Obama, Neural Nets, Self-driving Cars, and the Future of the World; many important points were made relating to the capabilities and issues related to artificial intelligence (AI). The article starts out with this statement:
IT'S HARD TO think of a single technology that will shape our world more in the next 50 years than artificial intelligence.
Here is a summary of important points made by the article:
- Generalized artificial intelligence vs Specialized artificial intelligence: A computer that can play chess is an example of specialized artificial intelligence. An example of generalized artificial intelligence is where a computer can perform multiple tasks. Specialized AI is not remotely as challenging to make work as generalized AI.
- Choices, Who creates the rules: This statement was made regarding driverless cars, "There are gonna be a bunch of choices that you have to make, the classic problem being: If the car is driving, you can swerve to avoid hitting a pedestrian, but then you might hit a wall and kill yourself. It's a moral decision, and who's setting up those rules?" Think about that. When you program a computer choices are made. Who will make those choices?
- Reliability and predictability: This statement was made, "One of the challenges that we'll have to think about is, where and when is it appropriate for us to have things work exactly the way they're supposed to, without surprises?" Reliability, predictability, repeatability are essential to harnessing the power of artificial intelligence.
- Role of government bureaucrats: This statement was made, "The last thing we want is a bunch of bureaucrats slowing us down as we chase the unicorn out there." While the government can be very important to starting innovation, the government needs to understand when to get out of the way.
- AI eliminating jobs: This statement was made, "There are actually very high-level jobs, things like lawyers or auditors, that might disappear." And, "You're also right that the jobs that are going be displaced by AI are not just low-skill service jobs; they might be high-skill jobs but ones that are repeatable and that computers can do." AI will eliminate jobs. Best to add value in ways that computers cannot add value.
- Technology gap between public and private sector: "There's a huge amount of work to drag the federal government and state governments and local governments into the 21st century. The gap between the talent in the federal government and the private sector is actually not wide at all. The technology gap, though, is massive."
The entire article is worth reading.
I created a document, Issues in XBRL-based Digital Financial Reports, which summarizes accounting logic representation issues within XBRL-based public company financial reports submitted to the SEC. The document contains about 50 easy to understand errors which are explained so that a reader can use the document to understand the error. Additionally, there is a link to the filing so that anyone can go to the filing and confirm (or refute) the information that I have provided.
There are two pieces of information that help you understand how helpful that document is. First, here we are five years into the mandate for public companies to file XBRL-based financial information with the SEC. FIVE YEARS!!! Software vendors and filing agents are still getting these 22 basic, fundamental accounting concept relations incorrect. But, if you look at a comparison of periods you see two things: (a) that there are filing agents and software vendors that are getting a high percentage of the financial filings they create consistent with these basic accounting concept relations; and (b) that consistency with these relations are slowly improving: March 2014: 93.92% , March 2015: 97.00%, , March 2016: 98.75%, August 2016: 98.90%.
Second, why did those 8 software vendors/filing agents understand and then correct those errors? Because I have been providing infomation such as what is in that PDF to as many filing agents/software vendors as I can to help them understand, detect, and correct those sorts of errors. (No one really ignores the information, some are faster to fix errors than others.) Basically, the PDF is an excellent learning tool for accountants creating XBRL-based digital financial reports.
Public companies and the SEC are the "canary in a coal mine" for digital financial reporting. The SEC is being pretty tolerant as software vendors, filing agents, accountants, financial analysts, and auditors figure out how to make digital financial reporting work appropriately. The CFA Institute has an excellent vision of what they call structured data can provide.
Keep in mind that these accounting logic relations need to be checked in every report, for every period. I am checking only 22 relations between about 40 concepts. There are probably 1000 to 5000 such relations in the typical 10-K financial statement. That is way too much to check manually, automated processes are necessary. To automate processes, you need machine-readable business rules.
XBRL-based digital financial reporting is not likely going away. Fact is, its use will likely only increase. Reading the PDF will help you tune your digital financial reporting skills. Want to really understand digital financial reporting? Here you go!
The Resource-Event-Agent (REA) model is an approach to conceptualizing the semantics of economic exchanges such as accounting transactions. The REA model is an ISO standard, ISO/IEC 15944-4:2007. (You can download a FREE copy of the 2007 version of the ISO standard, the newest 2015 version requires a purchase. Appendix B: REA Model Background, page 70.)
The REA model is best understood by understanding the "R" the "E" and the "A".
- Resources: Economic resources or claims are objects that are under the control of an economic agent. Economic resources/claims may things such as goods, services, rights, obligations, claims.
- Event: Economic events are the events, transactions, circumstances, and other phenomena which change economic resources from production, exchange, consumption, and distribution.
- Agent: Economic agents are identifiable parties which obtain, use, or dispose of economic resources.
People seem to use the REA model for various things: describing databases, capturing information about value creation patterns, explaining how to make accounting systems better, and so on.
My interest in REA is simple: use the semantics to represent economic exchanges such as accounting transactions in machine-readable form such as XBRL. Can I do that? Well, I already have. I built an XBRL taxonomy and an XBRL instance to prove the idea. I want to build a good set of examples before I make my XBRL taxonomy and XBRL instance available.
Here are several resources for more detailed information about REA:
- REA Models video: This is an 8 minute video which provides an overview of the REA model.
- REA Model Tutorial: Very basic tutorial which takes about 60 minutes to work through.
- What is REA?: An explanation of REA by REA Technology, lists of books and other resources.
- Research papers: A bunch of research papers related to REA provided by Bill McCarthy, the creator of REA.
One obvious question is: What is the difference between XBRL Global Ledger (XBRL GL) and REA? From what I can tell, REA and XBRL GL tend to do many of the same things. REA is more top down, big picture, work to the details. REA is not really a syntax, it is semantics. XBRL GL is a syntax that also provides detailed semantics. XBRL GL tends to be bottom up, working from the details to the big picture. From what I see, REA and XBRL GL tend to be complementary in nature. REA is an ISO/IEC standard. XBRL GL is an XBRL International standard.
Why am I interested in REA? Think drill-down from an XBRL-based financial report to the underlying transactions. Stay tuned! I will make my prototypes available, but I want to tune them some more.