Posts

The Financial
Data Platform

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Numeric has this notion of " the financial data platform ".  Numeric was recently introduced in a press release just a few days ago on September 22, 2026,  Numeric Launches Financial Data Platform, the ERP Replacement Built for the Agent Era .  Also, a co-founder of Numeric posted a question on LinkedIn, " Is the Financial Data Platform an ERP? " The purpose of this post is to help me get my head around what Numeric is, what a financial data platform is, to compare and contrast Numeric and the Accounting & Audit by Design Framework , and to otherwise get my head around what accounting is going to become and how the heck to get there effectively. Here are some facts from the Numeric press release and a video from that financial data platform page. This, a paragraph from the press release summarizes the problem of accounting pretty succinctly, "Historically, general ledgers were built to do one job well: produce GAAP-compliant financial statements. To do i...
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Seeking Talent Alpha

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Why do different hedge funds with access to identical market information and which use pretty much the same analytical models and analytical tools have dramatically different performance outcomes? If you have a business degree you probably understand what "seeking alpha" means when it comes to financial investments. For those not familiar with this idea, let me explain. "Seeking alpha" in financial investing means trying to earn investment returns above what the market would normally give you for the amount of risk you’re taking.  Seeking alpha implies that you believe the market is not perfectly efficient; that superior skill, superior insight, superior judgement, or superior information can produce superior returns; you accept that "superior" means more effort, higher uncertainty, and perhaps higher fees to obtain that advantage; and that it is in fact possible to beat the market. This Forbes article,  When Everyone Has AI, What Wins? Talent Alpha. , int...
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Example of Accounting & Audit by Design

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This blog post provides an example of using the  Accounting & Audit by Design (A&AD) Framework . Here is the set of XBRL artifacts and projections created from those artifacts. The ultimate intent of this example is to provide a beginning to end example of an implementation of Accounting & Audit by Design. You can follow this beginning to end example here on GitHub . This exercise combines two working proof of concepts.  This is  my original record to report working proof of concept .  To that, this JSON-LD example was added. General journal in JSON LD Schema for that general journal  (you can use this viewer to understand schema) These general journal entry types should be expanded to experiment with the Project Tavi specialized cube types that relate to journal entries and events. It might also be useful to experiment with which cube type to use for audit evidence and/or if a new cube type should be proposed for that. What I am trying to do is t...
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The Minimal Ontology Principle

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In a LinkedIn post , Animesh Kumar articulated an interesting way to look at LLMs. Paraphrasing, every LLM carries a π₯𝐚𝐭𝐞𝐧𝐭 𝐨𝐧𝐭𝐨π₯𝐨𝐠𝐲: some understanding of business concepts, how those business concepts relate to each other, and other knowledge that it uses to provide you with answers.  That understanding is distilled from millions of documents. Your information platform doesn't need to re-explain all this.  What your information platform needs to explain is the DELTA between what the LLM already gets right and what you consider the perfect answer. Kumar sees this as the "inversion of traditional data governance".  Instead of a governance committee deciding upfront what everything means, you let the AI's misinterpretations surface which concepts actually need formal definition. The area of confusion the LLM experiences is the methodology . This is a clever idea.  This idea also helps you understand how to understand the capabilities of generative artifi...
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Example of Discrete Stable Units

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In another blog post, Structuring Systems into Discrete Stable Units , I described a system of what amounted to information "Lego Bricks".  In this blog post, I want to walk you through what I am talking about. I will use my PROOF working  proof of concept. Here is the machine readable and machine interpretable global standard XBRL. That is XML which machines can easily read and interpret.  That first link is the "instance" or the facts of a report. Here is the model which a machine can get to from the report itself. Here are some of the "conditions" (a.k.a. assertions, restrictions, constraints) such as the accounting equation which the report MUST be consistent with. And here is the underlying base reporting framework with which the report is described and "fenced" or "bounded", the "guardrails" that specifies what the report MUST adhere to. This is the same information in machine readable form. Now this is what a huma...
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The Quantum Field Database

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I remember when I heard that light is both a "wave" and a "particle" (a photon). Wave-particle duality . Well, it is not. Light, per quantum mechanics, is actually a single quantum field. "Wave" and "particle" are not two kinds of light. They are two measurement outcomes of one underlying reality. The field doesn't choose to be one or the other. The measurement apparatus determines what you observe. The field simply is. Now, apply this thinking to a database. So why is a database forced to be SQL, or RDF, or a property graph, or XBRL? Why do we build separate systems for each paradigm, store the same facts in different formats, and then struggle to keep them synchronized? The data doesn't choose to be relational or graph. We choose how to query it. The query paradigm is the measurement apparatus. The substrate should just be. The Problem The root cause is that SQL , RDF , LPG , and XBRL were each designed around a different "atomic...
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Audit Evidence Graph

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The result of the past fifty to seventy five years of constructing accounting information systems is craft-based processes where data integrity depends on human discipline, human bucket brigades which move information,  rather than based on good system design.  The question is not whether there are better alternatives; there are.  The question is why the accounting and audit profession has tolerated this current situation for so long, and what it will take to transition to something fundamentally more sound. Imagine being able to click on a link to view the audit evidence knowledge graph which attests to the fairness of a financial statement. Imagine an artificial intelligence (AI) agent or a human being able to interpret that information reliably.  Why imagine it? Why not build it? The Nature of the Problem Gartner points out  (page 2) that the typical Fortune 1000 company uses about 800 electronic spreadsheets to create its compliance report.  Each of t...
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