Digital Financial Reporting

Pierre Hamon did a great presentation on Data Quality at XBRL Europe Digital Week. Have a look.

The following is an updated version of what used to be called Intelligent XBRL-based Digital Financial Reporting. This will be the version of this information which I will use going forward:

• Mastering XBRL-based Digital Financial Reporting
  • Table of Contents
• Section 0: Introduction
  • Introduction
  • Accounting, Reporting, Auditing, and Analysis in a Digital Environment
  • XBRL Primer
  • Computer Empathy
  • Essence of Accounting
• Section 1: Important Background Information
  • Conceptual Overview of XBRL-based Digital Financial Report
  • Principles
  • Artificial Intelligence and Knowledge Engineering in a Nutshell
  • Digitizing Financial Reports
  • Overview of Professional Accountant’s Interests, Perspective, Position, and Risks
  • Distributed Ledgers
  • Lean Six Sigma
  • Other Moving Parts of Digital
• Section 2: Logical Conceptulization of Financial Report
  • Exchanging Complex Financial Information
  • Logical Systems
  • Logical Theory Describing Financial Report
  • Terms
  • Associations
  • Structures
  • Rules
  • Facts
  • Representing Structures Using Hypercubes
  • Concept Arrangement Patterns
  • Member Arrangement Patterns
  • Structure Arrangement Patterns
  • Fundamental Accounting Concepts and Reporting Styles
  • Disclosure Mechanics
  • Disclosure Rules (a.k.a. Reporting Checklist)
  • SEC-type XBRL-based Digital Financial Report
  • ESEF-type XBRL-based Digital Financial Report
  • Reference to Logical Theory Terms
  • Reference to Logical Theory Semantics
  • Advanced Aspects of Logical Conceptulization of Financial Report
  • Additional Resources
• Section 3: Working with XBRL-based Digital Financial Reports
  • Viewing Reports
  • Controlling Report Quality
  • Querying Report Information
  • Creating Reports
  • Digital Financial Report Creation Best Practices
  • Workflow and Process Control
  • Auditing XBRL-based Digital Financial Reports
• Section 4: Examples and Samples
  • Hello World Example
  • Concept Arrangement Pattern Examples
  • Member Arrangement Pattern Examples
  • Business Use Case Examples
  • Comprehensive Example
  • Reference Implementation of XBRL-based Report for SEC
  • Reference Implementation of XBRL-based Report for ESMA
  • Mastering Examples
  • Template Examples
  • Exemplar Examples
• Section 5: Technical Details
  • XBRL Technical Syntax Details
  • Special and Specific Considerations
  • Reconcilation of Models
  • Financial Report Object Properties
  • Report Element Properties
  • Analysis of 6,751 XBRL-based 10-Ks
  • XBRL Technical Syntax Modeling Tips
  • Profiles

 Stay tuned here for more information.

The Enterprise Knowledge Graph Foundation has published a set of principles for an Enterprise Knowledge Graph (EKG).

A knowledge graph is one approach to storing information within a knowledge base.  The article, What is a Knowledge Graph? is an explanation of what a knowledge graph is (and isn't) and the difference between a knowledge base and a database.  You can download the knowledge base GraphDB here. This is a quick start guide for GraphDB.  Or, you can fiddle around in the Neo4j Sandbox here.

This is an excellent article that explains why graph databases are the future of databases.  This is excellent information aboug GSQL which is a graph query language.

Ontology + Data = Knowledge Graph

A Brief History of Knowledge Graph's Main Ideas: A Tutorial

Emerging Landscape

Introduction to Knowledge the Graph

Creating a small knowlege graph video series: 

• Part 1
• Part 2
• Part 3
• Cayley

This blog post makes you aware of the Explore example application that I am making available that helps those interested understand how to extract and analyze information from XBRL-based financial reports.  Go to the Explore web page to read the documentation, download the database application and Excel information extraction tools, etc.

Read the documentation to get a good overview of what the database application is and does.  Or, watch this video walk through.

Essentially, there are 109,778 financial reports from 3,600 public companies that use 17 different US GAAP reporting styles to submit information to the SEC.

This is an excellent starting point (i.e. training data) that can be used to create machine learning applications related to US GAAP financial reporting.  I might create a similar set for IFRS.  There is lots of VBA code that helps you understand the proper steps of extracting information from XBRL-based reports.  Don't make the mistake of focusing on the actual code (i.e. I am not really a very good programmer); focus on the necessary steps to be effective.

Note that if you want to update the database with additional reports, you can use the SEC's RSS feed of reports to do so.

If you cannot open a Microsoft Access database but you want the data, email me and I can get you a copy of the data in Excel.

This explaination is for the benefit of computer scientists/software engineers.  Accountants learn this stuff in Accounting 101.

At the end of an accounting cycle which is usually a year and at the end of a calendar year (i.e. December 31) for most companies; you "close the books" for that period.  Note that companies can, and many do, have year ends other than December 31.  Further, an accounting cycle could be a 52/53 week period.  Retailers use this approach to enhance comparibility.

If you want to understand the accounting cycle and closing entries, this is a good explaination.  This YouTube video explains closing entries. (This YouTube channel has lots of good information about accounting.)

So this is the entire accounting cycle (with some helpful videos that explain specific steps): 

• Journalize Transactions
• Post Transactions to General Ledger
• Trial Balance
• Adjusting Entries
• Adjusted Trial Balance
• Preparation of Financial Statements
• Closing Entries

How do you explain all this to a computer?  It amazes me how dumb computers really are.  They understand none of this.  Each detail of each step needs to be explained.

It seems that what I need to do is use the fundamental accounting concepts to define the high level concepts like "Assets", "Liabilities", "Equity", "Revenue", "Expenses", "Net Income (Loss)", "Net Cash Flow", and so forth.  I need to explain which of those are REAL (permanent) accounts and which are NOMINAL (temporary) accounts to enable the closing process to be automated. These relations can all be expressed using XBRL definition relations.

How the chart of accounts is mapped into those high level concepts is done using the roll up relations represended by XBRL calcuations.

I created all of this for the not-for-profit XBRL taxonomy. See here for human readable information.  See here for machine readable information.