:quality(75))
Underwriting
Pricing risk on today's data, not last year's manual review
Underwriting still runs on manual submission review, risk appetite checks done by hand, and rating tables that update on a slow cycle. A submission can wait days for a decision an underwriter could make in minutes with the right data in front of them.
AI brings the data to the decision. Models price risk from telematics, claims history, and external data, not only the standard rating factors. Generative AI drafts the risk report and summarizes a submission against your appetite. Agents clear routine submissions and escalate only what needs an underwriter's judgment. Underwriters spend their time on the risk that needs a person, running on infrastructure you control.
5 use cases
Automated underwriting risk scoringAutomated underwriting risk scoring gives each new insurance application a risk score and explains it, so your underwriter decides every application with the reasons in front of them.Personalized rate managementAI personalized rate management estimates each policyholder's risk from individual behavior and context, not just broad rating classes, so pricing and actuarial teams can set rates that track real risk more closely.Policy and endorsement document intelligencePolicy and endorsement document intelligence reads your policy forms, endorsements, and contracts, then answers coverage questions with a citation to the exact wording, for underwriting, claims, and servicing teams.Premium audit validationPremium audit validation uses AI to read payroll reports and records, check them against the exposure a policyholder declared at binding, and send each variance to your premium auditor.Turning broker submissions into clean risk dataAI reads broker submissions, loss runs and prior policies into clean, normalized risk data, checks it against your appetite, and drafts the clearance file for your underwriter.
Start owning your AI