Professional System for Creating Financial Reports Leveraging Knowledge Graphs

The document Professional System for Creating Financial Reports Leveraging Knowledge Graphs explains a new approach, a new paradigm, for creating financial reports.  The document provides a practical, nontechnical description of a professional system for creating provably high-quality financial reports where the report creator is using financial reporting schemes (such as US GAAP and IFRS) where report creator is permitted to modify the report model which leverages global standard knowledge graphs represented using XBRL.

This new approach is useful, it is highly novel, and the details were highly complicated to pull together.  This is certainly not an incremental innovation.  It is definitely a disruptive innovation and it could very well be a foundational innovation. You can decide which for yourself.

Foundational technologies have two dimensions that need to be considered: novelty and complexity. The more novel the technology is, the more effort needed to ensure users understand the problems the new technology solves.  The higher the number of parties and the diversity of parties that have to work together to work together to produce a new solution, the more complexity is involved in making that product available.

The report is just the beginning. The entire record-to-report process will be rethought over time.  Today, enterprises spend 90% of their effort overcoming the symptoms of problems.  This approach is about solving the fundamental problem.

Eventually, there will very likely be hundreds of different approaches used to create knowledge graphs; some more on the formal side, others likely more informal. This specific approach is an intentional, conscious, rigorous, more formal, non-technical oriented, standards-based, logical theory-based approach to knowledge graphs for professionals where the tolerance for error is low, demand for quality is high, and models are permitted to be modified by information bearers providing information.

Quality knowledge graphs can help solve big, previously unsolvable problems.  As we have defined and designed them they will very likely be superior to other less functional approaches to constructing and working with knowledge graphs.

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