AI Browser Controls for Finance Evidence
Level automation controls
Approve the tenant, source, dates and read-only objective before collection
Sam Yang, Level
Approve collection and stop conditions
Specify which signed-in tenant and account may be read, the exact report and dates, the permitted output and the conditions that require stopping. Logging in, collecting a file, reconnecting a bank and posting an entry have different consequences. Collection approval should not silently expand into write authority.
A browser workflow must verify native state after a navigation or date change. A selected header can render before its table. A successful download can still be the wrong company or prior period. Stop when account identity or full scope cannot be proved. Keep prompts bounded to evidence collection and hand uncertain interpretations to a finance reviewer.
Financial evidence in practice
How do you bound an AI browser finance workflow?
Approve the tenant, source, dates and read-only objective before collection. Stop when account identity, population or authority cannot be established. Export automation may organize evidence; it does not authorize posting, reconnecting accounts or changing payroll.
Run the check
- Define allowed screens and the permitted output.
- Require current tenant, account, date and basis read-back.
- Stop on unresolved filters, partial pages or authentication handoff.
- Separate collection approval from any later financial write.
Fictional example: Equal totals with different bank occurrences
Both fictional lists total a $26 outflow. Only occurrence A matches. The second bank row is September 29; the unresolved ledger row is October 2, so the lists span different cutoffs. Equal totals and repeated $13 values cannot prove the second match.
Invented teaching inputs; downloadable files store these dollar amounts in USD cents. Incoming amounts are positive and outgoing amounts negative. A card charge credits its liability account.
Inspect the expected output
{
"fictional": true,
"unit": "USD cents",
"id": "bank-identity",
"totalsTie": true,
"matchedIds": [
"A"
],
"unmatchedBank": [
"B"
],
"unmatchedLedger": [
"C"
],
"decision": "Same amount and equal totals do not prove occurrence identity",
"limitation": "This is teaching arithmetic from supplied invented inputs, not source authenticity, financial assurance or authority to post."
}Reproduce this calculation
Download the code and input into one folder, then run:
node reproduce.mjs bank-identity.input.jsonThe code checks declared units and identities and refuses unsupported inputs. No browser or customer account is used. Source authenticity and accounting approval require separate evidence.
Reviewed 2026-10-06. Level financial-control guidance, with visibly fictional teaching examples. The example shows a control boundary, not a measured customer outcome or industry benchmark.
Read this content revision history
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Open the related financial check when the next question concerns that workflow. The Financial Systems Field Guide holds the named-system collection notes, pitfalls and bounded prompts.
Sources and method
Field Guide. This guide shows how to check whether the numbers are ready to use. The examples use made-up numbers, clearly labeled and available to download. They do not include private customer documents or measured customer results. Before using the method, check that your account has the required access and that your reports count the same things.
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About the author
Sam Yang
Founder & CEO
Founder of Level, the always-on finance team for contractors, service businesses, and ecommerce brands. Ex-CFO across trades, SaaS, and service businesses. 4 years as Director of Growth Product at BuildOps, building financial tooling used by 1,000+ commercial contractors. Four years in PE and investment banking rolling up and acquiring service businesses, $2.5B in total transactions including M&A and IPOs. Stanford MBA, Brown undergrad. The Level founding team's analysis of 2,200+ contractors ($13.25B in job revenue) across operating, private-equity, and CFO roles anchors the Level Index benchmark research.
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