Can you prove the case and operate through stress?

13. Is the pilot representative, controlled and capable of disproving the business case?

• 0 points: The decision rests on a demonstration or supplier accuracy claim.
• 1 point: A trial is planned, but files are convenience-selected or success criteria will be agreed afterwards.
• 2 points: The carrier has approved selection rules, a comparable baseline, reviewer arrangements, acceptance criteria, denominators, measurement methods and stop conditions before testing.
• 3 points: That protocol has been executed; results include rejected, unresolved and exception files, segment-level outcomes, review effort and limitations, and meet the pre-agreed decision criteria.

Evidence to show: A pilot protocol, selection log, results workbook and signed decision record.

We recommend separating tuning examples from evaluation files and including the intended inspection channels and complexity mix. Set sample size from the decision risk and required precision—not a universal file-count rule.

Research context: NIST’s Generative AI Profile cautions against extrapolating capability from narrow, anecdotal assessments and recommends empirical evaluation. It does not prescribe a property-claims pilot sample size. (nvlpubs.nist.gov)

14. Have you stress-tested accepted-file capacity, not just drafting capacity?

• 0 points: Catastrophe capacity is assumed from a supplier’s staffing or technology claims.
• 1 point: Drafting capacity is estimated, but review, exceptions and missing-evidence work are excluded.
• 2 points: A carrier-relevant surge scenario includes sustained arrivals, production, reviewer capacity, exceptions, system constraints, quality thresholds and fallback arrangements.
• 3 points: A simulation, rehearsal or comparable operating record demonstrates the plan, identifies the bottleneck and establishes escalation triggers and recovery responsibilities.

Evidence to show: A queue model, capacity commitments, reviewer roster by relevant capability and a rehearsal report.

Test both a sudden burst and sustained elevated demand. State which commitments concern accepted files and which concern drafts delivered.

Research context: New York DFS recommends incorporating third parties into continuity planning and considering joint testing. Applying that principle to catastrophe production queues is this desk’s operational recommendation, not a prescribed regulatory stress test. (dfs.ny.gov)

15. Could the evidence lead you to improve in-house production—or stop the purchase?

• 0 points: Outsourcing or automation has already been selected regardless of the evidence.
• 1 point: Alternatives are discussed, but the comparison uses different scopes, quality standards or retained-work assumptions.
• 2 points: Improved in-house production, managed production and targeted automation are compared on common acceptance criteria, full costs, implementation effort and retained responsibilities.
• 3 points: Decision-makers have reviewed actual pilot evidence against the internal comparator, agreed the preferred route and approved staged deployment, monitoring, corrective actions and a tested fallback.

Evidence to show: An in-house versus outsourced property claims estimating decision matrix, signed decision and staged operating plan.

A strong answer can be “keep production internal”, “repair inspection inputs first” or “automate only one task”. Do not award success merely because a purchase is approved.

For AI-supported workflows, ongoing oversight is consistent with the NAIC model bulletin’s lifecycle approach; the three-option commercial comparison is our proposed method. (content.naic.org)