Digital Financial Reporting

Wall Street Journal: FDIC Considers Scrapping Quarterly Bank Reports

The Federal Deposit Insurance Corp. is moving to boost the way it monitors for risks at thousands of U.S. banks, potentially scrapping quarterly reports that have been a fixture of oversight for more than 150 years yet often contain stale data.

The FDIC on Monday is expected to kick off a competition among 20 data and technology firms to develop a new reporting prototype that could provide the agency with more timely and targeted data about banks’ credit exposures and deposit information.

More interesting information here on Facebook.

Here is the actual FDIC press release.

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.