BLOG:  Digital Financial Reporting

This is a blog for information relating to digital financial reporting.  This is my brain storming platform.  This is where I think out loud (i.e. publicly) about digital financial reporting. It is for innovators and early adopters who are ushering in a new era of accounting, reporting, auditing, and analysis in a digital environment.

Much of the information contained in this blog is synthasized, summarized, condensed, better organized and articulated in my book XBRL for Dummies and in the chapters of Intelligent XBRL-based Digital Financial Reporting. If you have any questions, feel free to contact me.

Deloitte's Vision: The Finance Factory

Deloitte is articulating a vision of what they call "The Finance Factory".  I buy into that vision.  Here is how Deloitte describes the Finance Factory:

The finance factory handles core finance processes, and connects to finance centres of excellence and outsourcing partners in a hub-and-spoke model.

There’s no paper, anywhere. Employees use cloud-based apps on mobile devices to transact their business, and highly standardized, simplified, workflow-enabled business processes handle the rest. Automated controls and intelligent process monitoring and analytics keep watch over core, extended and outsourced process performance, exceptions and service levels to help minimize rework. Finance managers receive event-driven, real-time updates thanks to new integration tools and advances in in-memory processing.

The close process is continuous, if not yet real-time. A daily soft close is the new norm, made possible by visual close management tools, integrated sub-ledgers, daily time capture, journal workflows, reconciliation tools, as well as automation of consolidation, foreign exchange, allocation and intercompany transfers. Finance teams now simulate pre-close results and can support the continuous development of the MD&A throughout the close process.

The description of the vision is maturing.  Last year I heard the term "lights-out finance" explained in broad brush strokes.  Now, I would point you to these Deloitte documents that help paint the details of the vision:

Others provide insights into the possibilities but refer to the same thing using different terms.  "Financial Transformation" and "Finance Digital Transformation" and "The Modern Finance Platform" and "Digital Finance" and "Mirror World" are some of the different terms used:

Also, consider that the end or OUTPUT of The Finance Factory is INPUT into some other system for, say, the analysis of financial information or RegTech systems used by regulators or lendors.  For example, creating a discounted cash flow model using the information from a financial report is a step after information leaves The Finance Factory.

So, the vision is great.  But how do you actually get this vision implemented?  Well, of course, the giant consulting firms like Deloitte would tell you to hire them.  But even if you hired Deloitte or someone else and paid them a bunch of money, how would they actually implement all that "stuff"?  Here are the specific pieces that I came up with:

I would not encourage people to "role your own" solution.  My personal view is that the best approach is to purchase off-the-shelf software where you can.  Now, very little software exists currently.  That will change.  I would encourage you to ask software vendors if they use global standards or if they use proprietary formats and approaches.  Avoid proprietary formats and approaches, go with global standard approaches and formats supported by software vendors.  That way, if you are not satisfied with one software vendor you can easily switch.  If you cannot find the software you need, then wait.  This transformation will take years and years.

Posted on Wednesday, February 20, 2019 at 04:23PM by Registered CommenterCharlie in | CommentsPost a Comment | EmailEmail | PrintPrint

Essence of a General Purpose Financial Report

A general purpose financial report is a high-fidelity, high-resolution, high-quality information exchange mechanism. The report is a compendium of complex logical information required by statutory requirements and regulatory rules plus whatever management of an economic entity wants to voluntarily disclose.  The report represents quantitative and qualitative information about the financial condition and financial performance of an economic entity.  There are a number of different financial reporting schemes: US GAAP, IFRS, IPSAS, GAS, FAS, etc.

Use case:

Two economic entities, A and B, each have information about their financial position and financial performance. They must communicate their information to an investor who is making investment decisions which will make use of the combined information so as to draw some conclusions. All three parties (economic entity A, economic entity B, investor) are using a common set of basic logical principles (facts, statements, deductive reasoning, inductive reasoning, etc.), common financial reporting standard concepts and relations (i.e. US GAAP, IFRS, IPSAS, etc.), and a common world view so they should be able to communicate this information fully, so that any inferences which, say, the investor draws from economic entity A's information should also be derivable by economic entity A itself using basic logical principles, common financial reporting standards (concepts and relations), and common world view; and vice versa; and similarly for the investor and economic entity B.

Principles:

  1. A general purpose financial report is a high-fidelity, high-resolution, high-quality information exchange mechanism.
  2. Prudence dictates that using information from a financial report should not be a guessing game.
  3. All formats conveying information should convey the exact same meaning be that format paper, e-paper, or some machine readable format. 
  4. Explicitly stated information from information bearers or reliably derived information is preferable to requiring information receivers to make assumptions.
  5. Double entry accounting enables processes that allow for the detection of information errors and to distinguish errors  (unintentional) from fraud (intentional).  
  6. Catastrophic logical failures are to be avoided at all cost as they cause systems to completely fail.

General Purpose Financial Report:

 

(Click image for larger view)

A logical theory defines and describes things.  All of this can be described logically in a manner that is easy for a professional accountant to understand.  For example, consider the Logical Description of a Business Report.

Logic a set of principles that form a framework for correct reasoning. Logic is a process of deducing information correctly.  Logic is about the correct methods that can be used to prove a statement is true or false.  Logic tells us exactly what is meant.  Logic allows systems to be proven.

The principles of logic are topic-neutral, universal principles which are more general than say the single domain of biology, mathematics, accounting, economics, or other domain. Logic has to do with the meaning of concepts common to all domains and establishes general rules governing concepts.

Logic is the process of deducing information correctly; logic is not about deducing correct information. Understanding the distinction between correct logic and correct information is important because it is important to follow the consequences of an incorrect assumption. Ideally, we want both our logic to be correct and the facts we are applying the logic to, to be correct.  But the point here is that correct logic and correct information are two different things.  If our logic is correct, then anything we deduce from such information will also be correct.

Logic is also not the psychology of reasoning.  Again, logic tells us how we ought to reason if we want to reason correctly.  Whether people follow these rules is not our concern here.  The psychology of reasoning helps one understand the actual reasoning habits of people including reasoning mistakes. Again, our concern is getting the logic correct.

From the set of allowed laws and regulations, professional accountants can exercise their judgement as to which allowed alternatives from that set best conveys information.

Details about financial reports must be explained to brainless robots.  Once you define things you can ask questions.

The discipline of describing something in a form a computer algorithm can understand also assists you in understanding the world better; weeding out flaws in your understanding, myths and misconceptions.

Posted on Monday, February 18, 2019 at 12:19PM by Registered CommenterCharlie in | CommentsPost a Comment | EmailEmail | PrintPrint

Preparing Professional Accountants for the Next 25 Years

Many business professionals really have no clue about what is about to be thrust upon them over the next 25 years.  Business professionals really have no choice what-so-ever as to whether this change will occur or not.  The change is already occurring.  Business professionals, including professional accountants, can choose whether they deal with this change prospectively or retrospectively.

There is no universal "right" or "wrong" answer to the question as to the best approach to take, proactive or reactive.  But, the choice you make will have consequences.

When I graduated from college in 1982 and showed up that fall in the offices of Price Waterhouse, one of the managers pointed to a room that had two IBM Personal Computers and said something like, "Why don't you see if you can make those do something."

Most of the other 50 or so accountants paid no attention to those new computers.  Me, I took a class in VisiCalc which was the first electronic spreadsheet made for personal computers.  Some years later I learned Lotus 1-2-3, then Excel.  At one point I took a five day class at Microsoft that had to do with macros and Visual Basic for Applications (VBA).

Others.  Well, many other accountants adopted the strategy of avoidance.  There were accountants that figured that they could retire in five to ten years so they were just going to ignore the whole computer thing.

Today, many accountants seem to be adopting a similar approach of retiring or simply denying that anything will change.  Trust me when I say that while that might work for some older accountants, it is really a dumb strategy for those who are younger.

Another thing is that does not work very well is listening what what the majority of the profession is saying and doing that.  The problem with that is that the majority of the profession really has no idea what is coming because they don't have the proper background to understand.

First, what is going to change?  In my opinion based on what I have seen and experienced over the past 20 years the following is going to happen:

  1. Specialized artificial intelligence: Computers will become even more adept at doing useful work for professional accountants, other business professionals, and in general.  The primary new capability that will enable this is "specialized artificial intelligence".  What I mean by that is a software program augmenting the skills of an accountant, similar to how a calculator augments your skills for doing math.
  2. Structured information: More structured, semantic-oriented information will be used.  This is as contrast to "text search" and computers figuring things out from unstructured information.  What I am talking about is professionals representing information in machine-readable structured form and then computers working with that rich, structured information. XBRL-based general purpose financial reports are a good example of structured information. Artificial intelligence software (i.e. #1) can do much more with structured information.
  3. Digital distributed ledgers: Whether it is blockchain based or hashgraph based or one of the many other digital distributed ledger formats available; digital distributed ledgers will have a big impact.  The primary thing that digital distributed ledgers do is turn proprietary, local databases into standard, public databases and make sharing information easier.  Digital distributed ledgers is a method of making more structured information available (#2) which means that you will have more information that AI applications (#1) can work with.
  4. Automation of accounting, reporting, auditing, and analysis processes: Enabled by #1, #2, and #3 above; financial transformation and moving to a more modern finance platform is a no brainer.  For example, XBRL-based general purpose financial reports.

So, what should you learn to make sure that you have the skills you need to survive and thrive over the next 25 or so years?  What do you need to understand in order to best grasp the opportunities that will appear in the coming years? This is my view:

  • Logic: The single most helpful thing that I did was to take a college class in formal logic.  Now, I would admit that an entire course in formal logic is probably overkill.  But unfortunately, it is harder to find a college professor that is teaching only the portions of formal logic that you need.  What you need, in my view, is to formalize your understanding of logic a bit rather than just rely on your natural, innate understanding of logic that most people have.  Logic helps you understand how computers "think" and helps you understand what they can and cannot do and how to get them to do the things they can do.  I summarized a lot of this information in the document Computer Empathy.
  • Information Science:  This hard to define precisely.  First off, you don't need to learn a bunch of "technical" stuff.  What you need to learn is fundamentals of what information is (as contrast to data), what it takes to get computers to do useful work for you, and other things like that.  Again, i tried to articulate as best as I could what I believe you need to learn in the document Computer Empathy.
  • Business Analytics: Excel is an excellent tool...except when it is not. One good definition of business analytics is “the study of data through statistical and operations analysis, the formation of predictive models, application of optimization techniques, and the communication of these results to customers, business partners, and business executives.” There are lots of good business analytics tools.  But, what you really need is the understanding of statistics, interpretation of information, analysis methodology, etc.

In my personal view, somewhere between 30% and 70% of accounting jobs will change.  That means that somewhere between 30% and 70% of professional accountants can do nothing different and still do just fine.  Some studies say that 98% of accounting jobs will simply go away.  That just will not happen.

And so some professional accountants are definitely at risk.  Others will completely miss the opportunities that reveal themselves because they were not prepared.  Be very careful who you listen to, they might be pointing you in the wrong direction.  And don't just take my word for any of this, I don't have a perfect crystal ball, I simply have some of the skills necessary and a track record to make a decent prediction.

Posted on Monday, February 18, 2019 at 09:31AM by Registered CommenterCharlie in | CommentsPost a Comment | EmailEmail | PrintPrint

Things, Not Strings; Understanding Knowledge Graphs

Jo Stichbury, in his article WTF is a knowledge graph, does a great job of explaining what a knowledge graph is and why it is useful.  Here are the key points as I see them related to knowledge graphs:

  • A knowledge graph is a graph rather than a table, or a tree. I pointed out the difference between tables, trees, and graphs in the document Computer Empathy (page 16). Basically, a graph is a powerful and flexible way to store knowledge.
  • A knowledge graph is self-describing; basically there is logic that explains the meaning being conveyed within the knowledge graph.
  • It is not simply about the knowledge graph itself but more about the combination of the knowledge graph and tools to work with the information within the knowledge graph. The object is to make use of the information in the knowledge graph.

If you want to understand more about knowledge graphs, see this paper Towards a Definition of Knowledge Graphs.

So why are knowledge graphs plus the tools for using information from a knowledge graph so important?  Using the right tools, a skilled craftsmen can easily produce works that are useful, elegant, and durable.

Today, many software developers and business professionals are using the wrong tools.  They tend to be stuck in the "data" world when we have really moved on to the "information" age.  Most business professionals have clumsy, ugly, barely functional software that does not remotely meet their needs when it comes to working with structured information such as XBRL.

There are many modern tools for building useful, elegant, and durable tools. For example, GRAKN.AI is an open source tool for building knowledge graphs and using information.  It is basically infrastructure.  It is only the foundation upon which products or solutions would be constructed.

Why is understanding knowledge graphs important to business professionals?  Because it helps them understand what to ask for in terms of tools.

Consider this definition of a knowledge based system which I have provided before:

A knowledge based system is a system that draws upon the knowledge of human experts that has been represented in machine-readable form and stored in a fact database and knowledge base. The system applies problem solving logic using a problem solving method to solve problems that normally would require human effort and thought to solve. The knowledge based system supplies an explanation and justification mechanism to support conclusions reached by the knowledge base system and presents that information to the user of the system.

A modern application for creating a financial report will be a knowledge based system which leverages technologies such as knowledge graphs to make them work elegantly and effectively.

Posted on Friday, February 15, 2019 at 07:44AM by Registered CommenterCharlie in | CommentsPost a Comment | EmailEmail | PrintPrint

Logical Theory Describing a Business Report

A logical theory defines and describes things. Details must be explained to brainless robots.  Once you define things you can ask questions. Interestingly, the discipline of describing something in a form a computer algorithm can understand assists you in understanding the world better, weeding out myths and misconceptions.

Several years ago Rene van Egmond and I wrote a logical theory which describes a financial report, Financial Report Semantics and Dynamics Theory.

We used that base, removed everything related to the domain of financial reporting (which is a specialization of a business report), and now we have a Logical Theory Describing a Business Report (the more general use case).

There really are very few differences.  One difference is that a financial report has "disclosures".  The equivalent in a business report is a "fact set".

A logical theory is an excellent communications tool. In order to get a software engineer or a team of software engineers to be able to work together and build the right software, a logical theory is very helpful.

If anyone has any feedback, please send it.  Always looking for ways to improve!

 

Posted on Sunday, February 10, 2019 at 01:54PM by Registered CommenterCharlie in | CommentsPost a Comment | EmailEmail | PrintPrint
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