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Insurance signals

What an attested healthcare deployment can actually emit toward the insurance market — named signal families, how much each can be trusted, and the one sentence of honesty that holds the whole page together.

The signal catalog defines typed, content-minimized metrics — enums, numerics, and hashes, never free text, so nothing PHI-shaped crosses the boundary — in two tiers. GROUNDED · Labs

Tier 1 — operational signals (direct reads of governed behavior):

Signal What it tells an underwriter
Verified Coverage Ratio What fraction of the system’s actions were attested — the honesty metric about the denominator itself.
Exposure Windows When governed inference was actually occurring — the temporal shape of the exposure.
Response Latency Whether controls run in-line at production speed (a control that gets bypassed for speed is not a control).
Retention Integrity Whether the evidence trail itself is intact and tamper-evident.

Tier 2 — actuarial signals (statistics computed over the population):

Signal What it tells an underwriter
Statistical Violation Rate Upper Bound A confidence-bounded ceiling on how often the system violates its baseline — an actuary-shaped number, stated with its uncertainty.
Override Frequency How often humans overrode the system — a proxy for real-world trust in the model.
Consent Coverage Fraction of interactions with attested consent — a direct HIPAA-adjacent liability signal.
Review Completion Rate Whether flagged items actually get human review, or pile up.
Correction Rate How often output needed correction — a leading indicator of loss frequency.

GROUNDED · Labs

Every signal above is a fraction, and every fraction has a denominator — so the first underwriting question is always: who counted it? The ladder, weakest to strongest GROUNDED · Labs:

operator-declared "we handle about a million inferences a month" — a management assertion customer-observed the deployer's own logs say so — better, still self-maintained Arbiter-observed the runtime proxy counted every governed inference — mechanically counted, single party Notary-bounded counts bounded by an independent, tamper-evident receipt chain — third-party verifiable

Only the strong end of the ladder is underwriting-grade, and OVERT classifies the denominator source explicitly rather than letting everything blur into “our data shows.” A signal is only as strong as the rung its denominator stands on. GROUNDED · Labs

The honest boundary — this sentence is the lesson

Section titled “The honest boundary — this sentence is the lesson”

These are emerging governance signals, not yet actuarially validated evidence.

Say it exactly that plainly. The signal families are real, typed, and designed for the purpose; but the market has not yet accumulated the paired claims experience that would make them validated pricing inputs — that is the whole actuarial pathway, still to be walked. A seller who presents these as proven actuarial evidence today is manufacturing basis risk out of enthusiasm, and any underwriter worth selling to will notice. The credible pitch is the honest one: here is the signal, here is exactly how far you can trust it today, and here is the mechanism by which it strengthens. GROUNDED · Labs

22 Personas and stakeholders

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