Digital Financial Reporting

Algorithmic Business Thinking (ABT) is an idea created by MIT that helps business professionals and computer professionals communicate. This video, Algorithmic Business Thinking with Paul McDonagh-Smith, discusses ABT.

I get the impression that Algorithmic Business Thinking builds on Computational Thinking. That is mentioned a couple of times. ABT is important as we transition from the industrial economy into the digital economy, we are in the fourth industrial revolution now.

The following are the four cornerstones of ABT: 

• Decomposition: Taking larger problems or challenges and breaking them down into a series of smaller problems or challenges that are easier to manage and solve.
• Pattern recognition: Rather than trying to build everything from scratch, use things that you have done before or that someone else has done before to leverage in order to solve problems and overcome challenges.
• Abstractions: Filter out unnecessary details out of the problem or challenge in order to focus on what is important.
• Algorithms: Humans and machines working together to on an ordered, sequential set of actions in order to solve a problem or overcome a challenge.

Algorithmic Business Thinking uses the four ideas above in order to solve problems and overcome challenges.

ACTUS (Algorithmic Contract Types Unified Standards) is doing some very interesting work related to standard financial contracts. The basis for this work is the book Unified Financial Analysis: The Missing Links of Finance.

The stated goal of ACTUS is:

The goal of ACTUS is to break down the diversity in financial instruments into a manageable number of cash flow patterns – so called Contract Types (CT).

This standardization work is based on the same observation that I had related to financial reporting: patterns. What Dr. Willi Brammertz observed is that 98% of all financial contracts can be represented by a small number (about 30).

What they call "contract types" is very similar to my notion of "reporting styles". Here are the similarities that I see: 

• Contract types (these are Structures)
• Taxonomy (these are Structures)
• Data dictionary (these are Terms)
• Applicability (these are Rules)
• Demo application (these show the Associations)
• Technical specification (these are Rules)

You can look at all this information within an Excel spreadsheet here. Here is their blog.

What would be interesting is to convert all this information into XBRL.  This is somewhat of an example of a financial instrument in XBRL.  Maybe I will do that.

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Ariadne

Poolparty provides this semantic search example application. The application is explained in this PDF.

NFT trade volume is up: (interesting embedded chart) 

You can get more information here.

The Poet of Logic Programming is an interview of Bob Kowalski, the designer of PROLOG and co-creator of the field of logic programming. Bob also is the creator of Logical English.