First review asks handlers to check multiple data points, identify gaps, apply policy and process, assess recovery and decide the next action all at once. A missed detail means rework, extra customer contact, delayed decisions, and lost recovery. As volumes and complexity grow, maintaining speed and consistency gets harder without adding pressure to the team.
Claims Review AI Agent brings the claim information together and returns a structured first assessment: a summary, your configured pre-checks, missing information, warnings and recommended next actions. The handler reviews the assessment, checks the supporting information and decides what to approve; the agent does the groundwork.
Retrieves approved claim information from configured systems and data sources.
Organises the key details into a clear summary and applies agreed business rules and AI-assisted checks.
Highlights missing details, warnings, deadlines and areas needing attention.
Recommends next actions based on the claim context and configured process.
Presents the assessment for the handler to approve, change or reject.
Completes approved actions, prepares communications where enabled, and retains the record for audit and process improvement.
Faster decisions, because handlers start from a clear picture instead of assembling it across screens.
Lower cognitive load, with key facts, warnings and actions in one structured view.
More consistent pre-checks, applying the same agreed rules to every suitable claim.
Missing information surfaced early, before it causes delays or repeated follow-up.
Support for recovery and leakage control, with third-party and other configured commercial checks brought to the handler's attention.
A stronger audit trail of the information considered, recommendations made and actions approved.
The product supports claims handling and operational decision-making. It does not replace the claims professional responsible for assessing the claim, applying policy or approving an outcome.
Handlers must be able to see the claim information, warnings and reasoning behind a recommendation. Access, retention, privacy and audit controls must reflect the sensitivity of customer and claim information, and performance should be monitored after deployment as claim scenarios, business rules and source systems change.
Claims Review AI Agent suits insurers whose handlers work across several systems to review a claim, who use standard pre-checks or assessment rules, and who want missing information surfaced earlier, with less cognitive load and people still in control.
Tower tested the claims-review approach in a non-production proof of value focused on the initial review of a claim. Tower reported:
An indicative 70% reduction in the time and effort required for claim summaries and next actions.
Over 80% accuracy in claim summarisation during the test.
Positive feedback from claims testers on faster delivery and clearer automated summaries.
Here are some FAQs for our Claims pre-check AI agent.
No. It prepares an assessment and recommendations for a claims professional to review. Any automated action must be separately configured, approved and governed.
A claim summary, configured pre-checks, missing information, warnings, deadlines and recommended next actions.
Yes, with suitable rules, examples, integration and testing for each claim type.
It can prepare or complete approved communications where that capability has been configured with appropriate human review and controls.
That depends on the insurer's systems, available interfaces and security requirements. The Tower proof of value used a controlled non-production environment.
Summaries, warnings and recommendations should be tested against agreed scenarios before release, then monitored in production for accuracy, consistency and suitable outcomes.
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