[Finance & business intelligence]() / [Use cases]() / [Governed answers]() [How it works]() [What you get]() [Scope]() [Start a review]() [Finance & business intelligence]()[Reporting & decisions]() # Answer finance questions on agreed definitions. Plain-language questions answered on agreed definitions, each with an as-of date and a status, and “unavailable” when the data isn’t there. [Start with a finance review]() [How it works]() What did returns cost on creator-led TikTok Shop orders in October? Unavailable. Returns are recorded by order, not by creator, so this can’t be answered yet. Returns on Canvas field jacket orders on TikTok Shop cost $4,400 in October. Returns · definition v3 · as of Nov 23 · status: unavailable A question the data can’t answer yet. The answer says so, and gives the part that is known. ## Sound familiar? - Two people ask the same question and get two numbers. - A change to the model waits in a queue for weeks. - The chatbot answers with confidence, and nobody can tell whether it’s right. A confident wrong answer travels faster than a late right one. ## What changes. ShowTodayWith the engine Definitions Buried in each analyst’s query Agreed once, versioned and reused Answers A number with no context A number with its definition, as-of date and status Missing data A confident zero “Unavailable,” and what would be needed Questions A queue for the data team Self-serve on supported questions, a queue for the rest ## How it works. 5 steps, 4 stages. - AI**2** - Rules and automation**1** - Your team**2** - Approval 1. 1 Define 1. Your team Approval ### Agree the definitions Finance and data approve each measure, its version and its owner. 2. 2 Ask 1. AI ### Plan the question Turns a plain-language question into a query on approved measures, and asks when it’s ambiguous. - Power BI - Metabase 3. 3 Answer 1. Rules and automation ### Calculate on governed measures Queries run on the agreed definitions. Missing data returns “unavailable”, never zero. - Snowflake - dbt 2. AI ### Draft the explanation Says what the numbers show and what they don’t, without inventing a cause. 4. 4 Review 1. Your team ### Review the misses Wrong, partial and unsupported answers are reviewed, then become new tests or new measures. Every miss becomes a test ## What you get. Real work, every week. Response record Answered Nov 23 TikTok Shop contribution was 12% in October. Definition v3 · after fulfillment, fees, returns and commission As of November 23 Status Closed, October Evidence October true-ups Owner Finance lead Every answer carries its record: the definition, the date, the status and who owns it. Tested before it answers - Ambiguous period: asks which month - Restated actuals: uses the closed figure - Missing attribute: returns “unavailable” - Plausible but wrong join New test added The tests every answer passes first, including the questions it should refuse. ## How you’ll know it’s working. 1. Accepted answers Answers that reviewers agree with, out of the questions asked. 2. Questions answered as unavailable A healthy count shows the system says so when it doesn’t know. 3. Reviewer corrections How often a person changes an answer, and why. Baselines agreed before we build. ## Works with what you have. Planning & BI - Power BI - Snowflake - Metabase - dbt Commerce - NetSuite We configure first Your BI tool’s own copilot and your existing metrics. If your measures are already defined there, we test the questions you really ask against them. We build when Definitions live in people’s queries, and questions that need finance’s judgment wait for days. ## What a first build includes. Built in your accounts, around your team. Scope, fee and baseline agreed before we start. 1. 1 Design 2. 2 Build 3. 3 Run it, or hand it over [Start with a review]() [Scope this build]() ### We build - A set of agreed measures, with versions and owners - A test set of real questions, including unanswerable ones - Answers that carry definition, as-of date and status - A review loop for misses ### We start from - The questions your team really asks - Existing metric definitions and reports - Read access to the governed data ### From your team Owner Finance lead, with the data lead Involves - Finance - Data - Business owners ## Questions teams ask. Why not let the model do the math? Models are unreliable at arithmetic across many records. In a 2026 research benchmark (FinBalance), the best model got 46.5% of balances exactly right. So queries and code do the calculating, and AI plans the question and explains the result. Does governing the measures really help? It did in one test. In an experiment run by dbt, answers were 98.2% accurate on governed measures against 90.0% without them, on a small set of questions. It’s a vendor’s own test, so we run yours on your data. Who owns it once it’s running? You do. It’s built in your accounts, documented, with training for the people who run it. Ownership usually sits with your finance lead, with the data lead. We can keep running it with you, or step back. How do we start? Usually with a finance review: two to four weeks, a fixed fee credited to the build, and a plan that’s yours. If the job is already clear, we can scope the build directly. ## Part of your finance engine. One of 11 use cases, in 5 parts. [See the whole finance engine]() 1. [Trusted records **2**]() 2. [Margin **2**]() 3. [Cash & commitments **2**]() 4. [Payables & receivables **2**]() 5. [Reporting & decisions **3**]() In reporting & decisions - [**Trading brief**Run a weekly trading brief that ends in decisions]() - [**Management pack**Produce the monthly management pack from verified figures]() - **Governed answers**You’re here Works with - [**Contribution diagnosis**Explain contribution margin by product and channel]() ## Get answers you can trace. Start with a finance review. [Start with a finance review]() [**Talk it through first**15 minutes]() We reply within one business day. --- Source: [https://www.thekeating.co/use-cases/governed-answers/]() [Contact Keating & Co](mailto:nelson@thekeating.co) · [Agent guidance](https://www.thekeating.co/llms.txt)