Digital Financial Reporting

Per MAKHFI.COM Knowledge Modeling is

the concept of representing information and the logic of putting it to use in a digitally reusable format for purpose of capturing, sharing and processing knowledge to simulate intelligence. Among others it can address business matters such as Agility, Compliance, Consistent Decisioning, Reasoning and Knowledge retention.

In the simple form, a Knowledge Model would be designed with the purpose of receiving data produced from various sources and generate outputs that could trigger actions.

I would point out the phrase "simulate intelligence".  In terms of, say, financial reporting; the knowledge is in the form of what someone like a certified public accountant or external reporting manager knows about financial reporting.  Or, the resources that they use in the process of external financial reporting such as the accounting standards codification, a disclosure checklist, and other such resources. 

You can move this knowledge.  Someone who as the knowledge can put it into the form that a machine can use and then the machine can tie all these resources together and the machine can help you create a financial report.  The machine simulates the intelligence necessary to create a financial report by using the knowledge which was articulated in machine readable digital form.

You can check out that web site, lots of useful information.  I will point out two very helpful things.

First, on the introduction page that site provides another explanation of the difference between data, information, knowledge, and wisdom (or they use intelligence).

• Data: The basic compound for Intelligence is data -- measures and representations of the world around us, presented as external signals and picked up by various sensory instruments and organs. Simplified: raw facts and numbers.
• Information: Information is produced by assigning meaning to data relevant to mental objects. Simplified: data in context.
• Knowledge: Knowledge is the subjective interpretation of Information and approach to act upon in the mind of perceiver. As such, knowledge is hard to conceive as an absolute definition in human terms.
• Wisdom (or Intelligence): Intelligence or wisdom embodies awareness, insight, moral judgments, and principles to construct new knowledge and improve upon existing ones.

They provide the following examples to help you understand the difference. DATA: The numbers 100 or 5, out of context; INFORMATION: Principal amount of money: $100, Interest rate: 5%; KNOWLEDGE: At the end of Year I get $105 back; INTELLIGENCE: Concept of growth.

Second, the web site categorized information into two distinguishable types:

• Explicit knowledge: Can be articulated into formal language, including grammatical statements (words and numbers), mathematical expressions, specifications, manuals, etc. Explicit knowledge can be readily transmitted to others. This type of knowledge can be easily "modeled" using various computer languages, decision trees and rule engines.
• Tacit knowledge:  Personal knowledge embedded in individual experience and involves intangible factors, such as personal beliefs, perspective, and the value system. Tacit knowledge is hard (but not impossible) to articulate with formal language. Neural network offers the best possible method for modeling tacit knowledge.

Now, I would encourage you to go back and read this blog post: Digital Financial Reporting Will Change Accounting Work Practices.  Read the part about how CAD software works.  Project that into how digital financial reporting software will work.  If you still don't get it, try this video: Digital Is Not Software, It Is a Mindset. Be sure to watch the part about the Amazon.com warehouse with "robot storage shelves that move around."

The Louvre museum has an annual balance sheet of a State-owned farm, drawn-up by the scribe responsible for artisans: detailed account of raw materials and workdays for a basketry workshop. Clay, ca. 2040 BC (Ur III).

Wiki commons

Paper-based (or clay-based) and even electronic PDF or HTML financial reports are readable by humans. On the other hand, digital financial reports are readable by both humans and machines.

Machines can therefore do things to help humans create or use digital financial reports that such machines could not help humans with before. This help from machines in creating and using the financial information within a financial report will reduce costs and increase quality. For example,

• A computer can read the reported financial information, understand the information, and can help make sure all of your mathematical computations are correct and intact; make sure everything foots and cross casts and otherwise ticks and ties.
• A computer can read the reported financial information, compare the reported information to disclosure rules, and make sure the creator followed mandated disclosure rules.  This is somewhat like a manually created disclosure checklist is used today as a memory jogger.
• Reported information can be easily reconfigured, reformatted, and otherwise repurposed without the need to rekey information because a computer can do all this for you.
• Ambiguity is reduced for humans because for a computer to make use of the information, the information cannot be ambiguous.  Making the information easy for a computer to correctly understand also makes it easier for humans to understand.
• Processes can be reliably automated because computers can reliably move information through the work process.  Unlike trying to link spreadsheets together, linking digital financial information together can be much more reliable.
• Computer software can adapt itself to specific types of reporting scenarios, again because software leverages and understands the machine readable financial report information.
• Because processes can be automated, the time it takes to create financial reports will be reduced and the human costs of connecting processes can be reduced.

This is not to say that humans will not be involved in the process of creating financial reports.  Clearly machines will never be able to exercise judgment. Computers cannot detect all possible mistakes, they can only help humans.

How can all this happen?  The more a machine can understand (high semantic clarity), the more a machine can assist humans.

These resources can provide you with additional background information on the possibilities offered by digital financial reporting:

• Digital Isn't Software, It Is a Mindset
• How Data will Transform Business
• Project10X: The Power of Strong Semantics
• Semantics Overview
• Understanding Concept Computing
• Digital Financial Reporting will Change Accounting Work Practices
• Race Against The Machine: How The Digital Revolution Is Accelerating Innovation, Driving Productivity, and Irreversibly Transforming Employment and The Economy (MIT)

All we need to do is get the right software built which understands digital financial reports.