The product allows the policyholder to submit photos of the damaged vehicle following the first contact with their insurer. The system then utilizes machine learning algorithms trained to predict damage severity and offer the most suitable next step – booking a repairer, total loss settlement or further inspection needed – and generates a confidence rating for such decision based on Solera's extensive database of historical claims.
Key points of Qapter Intelligent Triage include:
- Identifying probable total losses earlier in the claims journey
- Saving loss adjusters´ time for more complicated cases
- Determining whether vehicles are potentially unsafe to drive
- Contributing to policyholders' safety and increasing satisfaction with the claims experience
- Continuously refining the AI with a huge image database
- Enabling API integration with claims management systems
Solera's research indicates that FNOL calls typically take up to 30 minutes plus follow-ups and subsequent administrative work. Qapter Intelligent Triage can reduce this substantially, with more accurate outcomes and improved customer satisfaction.
The API-based solution can be integrated with most claims management systems, with simple implementation and easy, flexible use.
Qapter Intelligent Triage goes further in its image-based analysis. Beyond identifying total loss vehicles using images in just a few seconds, Qapter Intelligent Triage checks damage against a database of safety-critical parts to identify if the vehicle is safe to drive or needs towing service. It also checks for potentially fraudulent claims by matching geolocation, vehicle model and sub-model, and photos downloaded from the internet.
"This product provides actionable insights, which can save precious time for claims handlers and loss adjusters and keeps drivers safe by preventing unsafe vehicles from returning to the roads," says Marcos Malzone, Solera's Vice President of Product Marketing.
Qapter Intelligent Triage enables insurers to progress claims more efficiently.
Up to two-thirds of total loss vehicles are currently sent to body shops before the vehicle is written off. This involves unnecessary transport, delays, and inspection costs. Qapter Intelligent Triage will boost accuracy in determining total loss cases from the initial imagery.
The artificial intelligence is complemented by machine learning. The intelligence engine becomes more skilled and accurate with every claim processed. Total loss thresholds are also constantly updated.
"Our AI is fed new training data every two weeks," says Malzone. "This refines the algorithms and ensures that total loss predictions are in sync with changes in market conditions."
"This is a timely product as insurers are facing a higher proportion of total loss claims, as well as greater than ever complexity in vehicle design leading to more expensive repairs," says Malzone. "Total loss thresholds also change frequently in response to the value of used vehicles."
"Insurers need their systems to be automated, efficient, and as accurate as possible. Audatex's solutions help provide that accuracy and speed at every touchpoint of a vehicle lifecycle," Malzone added.
Overcoming skills shortage
The industry faces an unprecedented shortage of claims professionals, with recruitment and retention challenges. As a result, many claims handlers require extra time to learn and process cases efficiently.
"Qapter Intelligent Triage provides the speed and insights to boost triage efficiency," says Malzone. "It gives insurers expert eyes on the case from the outset, reducing cycle times and increasing renewals."