Building a Mindful Machine for Accountancy

Burroughs build the first accounting machine (sales poster) in about 1928. That has since been improved upon.  It is time for another improvement. To best understand the possibilities here, I would suggest reading the article Using logic programming for theory representation and scientific inference.

In another blog post I described the notion of what some people refer to as a "mindful machine". People use other terms to describe what I am talking about, but I like "mindful machine" which "smartens you up" and I am particularly interested in accountancy.

By "accountancy" I mean accounting, reporting, auditing, and analysis; external compliance reporting, internal management and cost reporting, tax reporting, and special purpose reporting; for profit, not-for-profit, state and local government reporting, federal financial reporting.  Basically, the full meal deal.

There is a big difference between a line cook and a chef.  Similar to how a chef transforms a recipe using kitchen equipment into an unforgettable meal; informatics transforms the use of information and knowledge into a successful experience.  Or using another analogy; there is a difference between a framer who can wield a hammer and an architect that transforms a building into a livable space by placing doors, windows, and utilities with functionality and ease; informatics improves “digital livability”.

What if accountants had a new type of tool?

Imagine a global open standards based, scalable knowledge based mindful machine specific to accountancy.  That machine is easy to use because complexity has been carefully managed.  Imagine a human accountant and an computer-based "artificial mind" interacting within a single common ecosystem which that mindful machine can interpret. That common ecosystem provides a shared conceptualization and has theories, knowledge, reasoning, governance (i.e. curation, checks and balances, scrutiny).  The knowledge is curated by subject matter experts that have a stake in the community of practice.

The knowledge in that common ecosystem is discernable because it is clearly specified. Knowledge is testable so that agreement can be confirmed by the subject matter experts (SMEs) in that community of practice. 

The knowledge is extensible, elastic; the ecosystem is flexible where it needs to be flexible. There are guardrails or "bumpers" associated with that extensibility/elasticity/flexibility that keep both the machine and human within boundaries; preventing wild behavior.  Knowledge is represented in a global open standards based form that is understandable by a machine-based process but then from that computer-based representation, a human understandable representation can also be generated.  Why?  Humans need to confirm that the global open standards machine-based representation is complete, consistent (e.g. free from contradictions), precise and accurate (e.g. properly reflects the beliefs of the community).  Having two different representations (one for machines, a different one for humans) can result in inconsistencies.

This common ecosystem can result in a virtuous cycle. Unprecedented reductions in system friction caused by rekeying of information, multiple versions of information which could be different, copying/pasting of information is minimized or even perhaps eliminated.

There are others that make suggestions on how one might go about building something like a "mindful machine".  Here are some suggestions that I am aware of: (in no particular order)

1. Jessica Talisman has the notion of the "ontology pipeline" which points out that librarians have a lot of experience with metadata management and that building out all the metadata you might need is a process and that there are a number of different forms that the metadata can take.
2. Semantic Arts in general and Dave McComb in particular and their open source GIST upper ontology helps one understand the role of upper level or top level ontologies.
3. Giancarlo Guizzardi has a lot of ideas related to "carving up reality" and how to guarantee intra-worldview consistency and inter-worldview interoperability. 
4. John Sowa and his work with common logic which has become an ISO standard logic framework.
5. Ora Lassila and all his work related to making the Semantic Web work.
6. Mike Dillinger and all his work related to understanding knowledge graphs.
7. Bill McCarthy and all his work related to REA and the notion of the "business event".
8. Dave McComb and Cheryl Dunn for taking REA to the next level with their Data Centric Accounting (DCA) and their notion of the "core event".
9. Willi Brammertz and his work to create ACTUS and his insights related to Luca Pacioli's Venetian Method of double entry bookkeeping.
10. XBRL International's and in particular Campbell Pryde and his work related to the Open Information Model (OIM) and XBRL Rule and Query Language 3.0.
11. The Object Management Group, and in particular Pete Rivet, and their efforts to create the Standard Business Report Model (SBRM).
12. The work of HL7 FHIR. Excellent example of what is possible.
13. The U.S. Securities and Exchange Commission (SEC) for making all those XBRL-based public company financial reports available and for taking a chance on XBRL; excellent test cases, very helpful in understanding those reports.
14. The European Single Market Authority (ESMA) and their European Single Electronic Format (ESEF) used by listed companies.
15. The FASB, and in particular Louis Matherne and all their work to create the US GAAP XBRL Taxonomy which is important financial reporting metadata.
16. The IFRS Foundation and IASB for their work with digital financial reporting and creating the IFRS XBRL Taxonomies.
17. Last but not least, Wayne Harding and all the others on the AICPA High Tech Task Force that got this show on the road; Barry Melancon and the AICPA for taking the risk to create what became XBRL; and all the members of XBRL International during the "cowboy days" when we turned this idea into reality. Extensible Business Reporting Language (XBRL) 2.1

If you want to study XBRL-based digital financial reporting I would encourage you to start small and then build, and build, and build.  Here are working proof of concepts: (Seattle Method Resources)

• Accounting Equation
• SFAC 6
• SFAC 8
• Common Elements
• MINI
• MINI with Business Events (Record to Report)
• PROOF
• AASB 1060
• IFRS for SMEs (Enhanced, Enriched, Augmented)
• Canonical Accounting Working Papers
• Office of Comptroller of Currency 1906
• Fundamental Accounting Concepts

After you understand the above, THEN fiddle with US GAAP and IFRS.  While no one software vendor has put all the puzzle pieces together yet, you can see what is possible by looking at several different software applications that provide pieces of the capabilities of a mindful machine for accountancy:

• IFRS for SMEs Model Financial Statement (work in progress)
• Inline XBRL financial statement
• Basic report viewer
• Pesseract working proof of concept (video)
• Verification results
• All files
• Linking directly to a specific piece of a report or a specific view of that  report.  Here is XBRL Cloud's evidence package that links directly to a balance sheet rendering or links directly to the business rules of the income statement.
• The ability to "pivot" a report and to navigate between the individual pieces leveraging the logical links between those report pieces.
• Track, Trace, Walk (a.k.a. “Audit Trail” and “Drill Down”), general journal to trial balance to lead schedules to audit or accounting working papers to financial statement to financial analysis model.  Track from detail to summary or drill down from summary back to the detail.  Really.
• World's first expert system for creating financial reports (video playlist)
• Creating financial statements using a model-driven approach, loading IFRS for SMEs templates.
• Creating an entire financial report using IFRS for SMEs model-driven templates.
• Model IFRS for SMEs financial statement generated using model-driven approach.
• Model IFRS for SMEs, all files.
• Accounting and audit working papers and schedules (video). Here is a working proof of concept.
• Viewer that lets you look at accounting and audit working papers.
• Autogenerated Inline XBRL of accounting and audit working papers.
• Constructing a financial report piece-by-piece by importing the report pieces from a set of Excel spreadsheets.

Additional Information:

• Universal Global Standard Logical Spreadsheet (Professional Spreadsheet)
• No Kludge
• The Vision
• Rethinking Financial Reporting: Model-driven Financial Statement
• Platinum Examples of Financial Reporting Schemes
• Platinum Business Use Cases, Test Cases, Conformance Suite
• Showcase of Reports
• Project for Graduate Accounting Students
• Mastering XBRL-based Digital Financial Reporting
• Computational Professional Services
• Process Engine
• Workflow Engine