- Complexity: Advanced
- Deployment: HeyQuinn recommended
The problem
Claims processing is high-volume and full of exceptions. Adjusters review documents by hand, investigate possible fraud and apply policy terms case by case. Delays frustrate customers, and insurers carry large claims teams to absorb seasonal surges.
- Claim documents arrive as PDFs, emails and photos that someone has to read
- Repair estimates are checked manually against what actually happened
- Fraud screening against watchlists and past claims takes time on every file
- Straightforward claims wait in the same queue as complex ones
The solution
A layered claims workflow reads the file, assesses the damage, screens for fraud and applies the policy, then routes anything complex or high-value to an adjuster.
- Extracts data from claim documents, emails and images using OCR and document parsing
- Assesses damage from photos and compares the repair estimate against the vehicle's telematics data
- Screens for fraud indicators such as duplicate claims and watchlist matches
- Applies policy terms, exclusions and deductibles to the claim
- Sends the customer real-time status updates and keeps an audit trail of every decision
Where people stay in control
- A claims adjuster reviews flagged or high-value claims before approval
- Complex claims and policy exceptions always escalate to a person
- Every decision is logged with its evidence for audit and compliance
Systems and data
The workflow reads unstructured claim documents and images through OCR, uses telematics data from insured vehicles, and checks fraud watchlists and prior-claim records. It writes decisions and status updates back to the claims system and to the customer.
- OCR
- telematics
- watchlists
Results
- Processing time reduced from weeks to hours in the documented deployments
- Low-risk auto claims approved in as little as 6 minutes at one mid-size auto insurer
Why HeyQuinn is recommended
Several agents coordinate across intake, assessment, fraud and adjudication, on regulated personal and financial data, with escalation and audit at each step. That combination of multi-agent coordination, permissions and audit is why HeyQuinn is recommended.
Frequently asked questions
Can AI approve insurance claims on its own?
Only straightforward, low-risk claims inside rules the insurer sets. Flagged, complex or high-value claims go to a claims adjuster for review before approval.
How does AI help detect claims fraud?
It screens every claim for indicators such as duplicate submissions, unusual patterns and watchlist matches, and flags them for an adjuster with the evidence attached.
What is telematics data used for in a claim?
It shows how the insured vehicle was actually driven and impacted, so the repair estimate can be checked against what the data says happened.