Digital Financial Reporting

This is a progress report on activity related to the OMG Standard Business Report Model (SBRM). This adds to the initial submission information.

Note this hot topics information about SBRM published by OMG.  And also note this in depth workshop/training session that OMG will hold in March.

Here are more updates: 

• Most Current UML Models (Formal)
• Terms
• Axioms (same information as the Associations between Terms, but in axiom format)
• Associations between Terms (same information as the Axioms, but in graphical form)
• Narrative
• Primer
• This is my informal home page with information about SBRM

If you have any feedback, comments, or other input; send it to me and I will get it to where it needs to go.

Organizations exchange information. Artificial intelligence, distributed ledgers, and machine-readable structured information offer unprecedented opportunities to automate many information exchanges within and between organizations. Furthermore, in most countries, organizations are required to submit formal information to one or more regulators regarding their business or financial performance, compliance and exposure. These have traditionally been as documents that use standard forms or templates defined by each regulator.

Recent years have seen the emergence of Standard Business Reporting, an approach that supplements traditional form-based documents with machine-readable versions containing structured data of the same content. The structured data, with identifiable fields (as opposed to electronic 'e-paper' documents in formats like PDF), is important to allow the data to be stored, analyzed and compared. The widely-accepted standard for business information exchange is XBRL (eXtensible Business Reporting Language), which allows the definition of different report structures based on the tagged markup language, XML (eXtensible Markup Language). SBRM builds on XBRL, further increasing its usability and applicability, by formally documenting a logical conceptualization of a business report in both human-readable and machine-readable models.