How do underwriters review an AI agent’s decisions?

Underwriters review an agent's underwriting decisions as they would a peer review file. They read what the agent quoted, referred or declined, find the deciding bound, test the disclosures and the rating factors that drove the outcome, and then decide with a reason. They also sample quotes issued without referral, where drift shows first.

What underwriting decisions does an agent make?

Depending on class and the insurer's limits, an agent may:

• rate and issue quotes for simple, in-appetite risks at depth 3;
• draft quotes, endorsements and renewal terms at depth 2 for an underwriter to send;
• refer risks that fall outside the guide;
• request missing information from brokers;
• draft declinatures for an underwriter to confirm.

Every decision is filed with the verdict, the sources, the brief version and the deciding bound.

What are the steps?

1. Read the record. The proposal, the agent's rating breakdown, the guide sections it applied and its decision.
2. Find the deciding bound. Every action meets five bounds: role scope, certificate, sources, the insurer's own limits and the platform guardrails. For an issued quote, ask how close it came to a referral trigger.
3. Test the disclosures. Note which facts are declared by the client or broker, which are signed by a named party such as a surveyor, and which are sealed from the insurer's own systems. A premium resting entirely on declared facts is only as good as the declaration.
4. Test the rating. Which factors moved the price most? Were loadings and discounts applied for the reasons the guide gives?
5. Decide and record. Approve, edit or decline, with a reason a peer reviewer or claims handler could follow later.

Which reviews matter most?

A worked example

Take a Japanese insurer whose agent issues small commercial property quotes at depth 3 below a sum-insured limit set in the insurer's own rules. In the monthly review, an underwriter notices that a growing share of new quotes from one broker sit just below the limit, and that several share the same building age and construction type.

Each quote is within bounds, and each is correctly rated on its declared data. The underwriter samples five and asks the broker for building surveys. Two show values materially above the declared sum insured. She edits both quotes to referred status, records the reason, and recommends that the insurer's limits hold any quote within a set band below the limit where no survey is on file. The limit owner agrees; the record shows the change and why.

What should underwriters avoid?

Reviewing only the referrals. Referred risks are already getting attention. The unreferred book is where silent errors grow.

Anchoring on the agent's price. On harder risks, form a view from the evidence before reading the agent's rating.

Treating the guide as fixed. If underwriters keep editing the same factor, the guide or the agent's brief needs changing, through the insurer's normal governance.

Reviewing agent decisions is a skill other teams build too; see how operations managers review an agent's decisions and how IT administrators review them. For building the skill across a team, see how to train the operations team to review agent decisions. A market example is in underwriter training in insurance in Japan, and the full role map in AI agent skills by role.

Where the Academy fits

Pryme Intelligence Academy's Operator track teaches human review and reading the workspace, with module tests set in the learner's own industry and role. For underwriters, that means insurance cases. Certified Pryme Operator includes a two-week practicum of real review decisions signed off by a Pryme assessor, and the certificate is valid for 12 months, renewed with an update module and a short quiz.