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A claims adjuster inspecting a damaged car

Insurance
Use Cases

Each part of an insurer has its own problems, data, and regulators. Start with your department.

Insurance overview

24 use cases

Search use casesAll departments

Actuarial

1 use case

Personalized rate managementAI personalized rate management estimates each policyholder's risk from individual behavior and context, so actuaries can set rates that track real risk.

Claims

6 use cases

Claims fraud detectionMachine learning scores every insurance claim for fraud risk from first notice of loss onward, so the SIU works the claims most likely to be fraudulent.Claims scoring, routing and denial reviewMachine learning that scores each insurance claim on arrival, routes it by risk and complexity, and explains every score and denial with reason codes.FNOL intake and claims triageAI that reads a first notice of loss packet, checks it against the policy, flags special handling, and drafts the routing for your claims team to approve.Policy and endorsement document intelligencePolicy and endorsement document intelligence reads your policy forms and endorsements, then answers coverage questions with a citation to the exact wording.Subrogation identification and recoveryAI reads each claim file for third-party recovery potential, judges evidence against your guidelines and drafts a recovery package for your team to review.Telematics-based insurance modelsMachine learning models that use vehicle driving data to score claims fraud, customer churn and billing risk for each policyholder, with reasons attached.

Distribution

3 use cases

Agent and broker performance and next best actionPredictive models that score leads, compare producer performance, and suggest a next best action for each agent, broker or household, with reasons attached.Personalized product bundling for insurersMachine learning that predicts which policy or coverage each household is likely to need next, with a reason code, so agents offer one relevant bundle.Telematics-based insurance modelsMachine learning models that use vehicle driving data to score claims fraud, customer churn and billing risk for each policyholder, with reasons attached.

Documents

1 use case

Legal research and aid assistantsAn AI assistant that finds the statutes and cases behind a legal question and answers with citations a lawyer can check, giving information, not advice.

Engagement

4 use cases

Call summary and resolutionGenerative AI reads every recorded customer call, writes a summary of what happened, and flags whether the issue was resolved so your team can follow up.Content and product personalization for marketingPredictive models score which message, image, offer and product each customer is most likely to respond to, so every channel shows content built for them.Customer retentionAI customer retention for insurers predicts which policyholders may lapse or switch at renewal, and why, so your team spends offers on those worth keeping.Next best action and offerMachine learning that ranks the offer, message or channel most likely to move each customer forward, so marketing sends one relevant action per customer.

Finance

2 use cases

Accounting and auditingAI accounting and auditing scores every journal entry and balance for unusual patterns, so auditors test the riskiest items first instead of a random sample.Strategic insight summarizerAn AI assistant that reads annual reports, earnings releases and company websites and returns strategic priorities, key results and opportunities, all cited.

Fraud

4 use cases

Application and account opening fraudApplication and account opening fraud detection scores each application for stolen identities, synthetic identities and mule risk before the account opens.Claims fraud detectionMachine learning scores every insurance claim for fraud risk from first notice of loss onward, so the SIU works the claims most likely to be fraudulent.Collusion fraud detectionMachine learning that links shared devices, addresses and payment paths across accounts to expose collusion rings that look normal one account at a time.Verifying identity documents at onboardingAn AI assistant reads an identity document uploaded at onboarding, checks each field for gaps, expiry and tampering, and returns a verified or flagged result.

Marketing

5 use cases

Content and product personalization for marketingPredictive models score which message, image, offer and product each customer is most likely to respond to, so every channel shows content built for them.Customer retentionAI customer retention for insurers predicts which policyholders may lapse or switch at renewal, and why, so your team spends offers on those worth keeping.Lead scoringAI lead scoring ranks every lead by how likely it is to become an opportunity and revenue, learning from the leads that converted and the ones that did not.Next best action and offerMachine learning that ranks the offer, message or channel most likely to move each customer forward, so marketing sends one relevant action per customer.Smart segmentationAI smart segmentation groups customers into microsegments by shared behavior and intent, so marketers can target and explain who is most likely to respond.

Underwriting

5 use cases

Automated underwriting risk scoringAutomated underwriting risk scoring scores each new insurance application and explains it, so your underwriter decides with the reasons in front of them.Personalized rate managementAI personalized rate management estimates each policyholder's risk from individual behavior and context, so actuaries can set rates that track real risk.Policy and endorsement document intelligencePolicy and endorsement document intelligence reads your policy forms and endorsements, then answers coverage questions with a citation to the exact wording.Premium audit validationPremium audit validation with AI: read payroll records, check them against the exposure 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 risk data, checks it against your appetite and drafts your underwriter's clearance file.

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