INDEX (US GAAP Financial Reporting Scheme)

The US GAAP Financial Reporting Scheme is a working proof of concept and prototype XBRL-based digital financial reporting scheme that demonstrates a modern approach to creating a financial reporting scheme. This approach can be used for general purpose or special purpose financial reporting. The provided metadata is used both creation of reported information and consumption of reported information.

This page contains detaied information primarily for use by machines reading the information. For better human-readable information and a summary, please go to the HOME page.

This 'logical system' or 'ontology-like thing' was created leveraging the Open Source Framework for Implementing XBRL-based Digital Financial Reporting. It will ultimately be adjusted to support the OMG Standard Business Report Model (SBRM). To understand why this ontology-like thing is important, please have a look at Artificial Intelligence and Knowledge Engineering Basics in a Nutshell.

For one resource that ties all the puzzle pieces of XBRL-based digital financial reporting together, please see Intelligent XBRL-based Digital Financial Reporting. If you want the most recent information, then follow my blog.

US GAAP Financial Reporting Scheme (US GAAP) Knowledge Base

The US GAAP Financial Reporting Scheme conceptual framework describes this financial reporting scheme. The information in this conceptual framework is documented below in both human-readable and machine-readable terms.

The following is a list of both human-readable and machine-readable information for implementing this knowledge base within software.

• Profiles: (Human | Machine) Summary of all profiles used to implement each financial reporting scheme.
• Model Structure Rules: (Human | Machine) Summary of the allowed XBRL presentation relations allowed. (recommend that the STRICT version is used even though the LAX version is allowed)
• Fundamental Accounting Concepts (FAC) Rules: (Human | Machine) Summary of the allowed intermediate subtotals used (i.e. reporting styles and high-level relations)
• Reporting Checklist Rules: (Human | Machine) Summary of the reporting checklist rules.
• Disclosure Mechanics Rules: (Human | Machine) Summary of the disclosure mechanics rules.
• Type or Class Rules: (Human (not available) | Machine) Summary of the type/class associations rules. (disallowed associations)
• Base Taxonomy (Entry Point): (Human | Machine) Entry point of the base US GAAP XBRL Taxonomy.
• Topics: (Human | Machine) Summary of the topics available to organize disclosures within.
• Disclosures: (Human | Machine) Summary of the topics available to organize disclosures within.
• Templates: (Human | Machine) Summary of templates for US GAAP disclosures.
• Exemplars: (Human | Machine) Summary of exemplars (examples) of US GAAP disclosures.
• Facts: (Human | Machine) Reports that contain facts which are reported.
• Facts: (Human) Reports per XBRL Cloud EDGAR Dashboard.

Example Financial Report Using this Scheme and Model

• Download All Files
• Download XBRL Cloud Evidence Package (review tool)
• Raw XBRL
• Human Readable (review tool)
• Human Readable (Report)

Information Extraction Prototypes

• Information Extraction Prototype (Comparison)
• Information Extraction Prototype (Extraction)
• Fundamental Accounting Concept Relations Rules Testing (Proof)

Lists of Financial Reports for Testing

• Microsoft 10-K for Last 10 Years Submitted to SEC
• All Microsoft Reports Submitted to SEC
• 85 Reports, all 10-Ks, Submitted to SEC for Testing
• All 5,555 10-K Reports, Last Report Subitted as of March 31, 2019
• Extract System Metadata

Other Useful Information

• Disclosure mechanics rules for ALL disclosures. (Note that not all of these disclosure rules are properly functioning yet)
• US GAAP Test Data. (This is helpful if you want to figure out how all this works)
• Quarterly XBRL-based Public Company Financial Report Quality Measurement (March 2019). (Results of testing XBRL-based public company financial reports against this logical system)