How Will AI Change FNOL and Damage Detection?

Posted on

September 28th, 2020


When a person initiates a claim following a car accident, they trigger a series of events beginning with first notice of loss (FNOL). Prior to AI, FNOL intake required a lot of back and forth between the insured and their insurance provider. Determining the extent of the damage, if a vehicle was salvageable, and the estimated cost took time and could cause delays. Further complicating matters, the inspection process is tedious and a common source of contention for underwriters—does it really cost that much for the repair? Harnessing the power of AI expedites the process and removes doubt regarding the true cost.

Using AI for Damage Detection

When tooling a machine to detect damage, the AI must first learn what a fully functional vehicle and its parts look like as well as varying degrees and types of damage. It absorbs sets of data and uses that knowledge to compare images of the damaged car components to their unblemished counterparts. The goal is to teach the machine to grade dents and scratches based on severity. It can then compute the estimated cost to repair it.

Reducing Costs with AI

Another helpful, money-saving feature is that the AI can determine if a part is actually damaged or not. Surface scratches and dents may look severe, but a machine can examine the part from all angles and rely on the historical data it learned previously. It may report that the scuffs are cosmetic, meaning it doesn’t need replacing during the repair. This translates to cost savings for all parties involved.

The AI does all this through a process called computer vision. It imitates how human eyes work while surveilling the damaged vehicle. It can perform a vehicle inspection and determine the severity of the damage at remarkable speeds as well as produce a full report to provide to the insured. Faster turnaround, precise reporting, and reduced costs benefit both the insured and the insurance provider.

FNOL is the most significant factor that affects customer satisfaction during a claim. However, delays and doubts about damage reporting accuracy can erode insureds’ trust and faith in their insurance provider. AI can eliminate those issues while resolving claims on a faster timeline. To learn more about improving customer satisfaction and FNOL, contact the experts at Actec.