Insurers are now embracing and leveraging new innovations that offer customers the choice and speed they're looking for.
Today's insurers must meet the growing customer demands for convenience, choice, a personalized experience, and a faster, automated service across the whole insurance journey, from purchase to first notice of loss (FNOL) to settlement.
At the same time, we've also seen the insurance industry starting its own makeover, from being a late-adopter cautiously eyeing new technologies, to embracing and leveraging new innovations that offer customers the choice and speed they're looking for, with the added bonus of reduced loss adjusting expense and more accurate loss estimates.
What's the end goal for insurers? For straight-forward personal lines claims, the nirvana is touchless claims. Being able to handle a loss from FNOL to settlement with no human intervention. It offers massive claims efficiencies, but the real pay-off is the impact it can have on customer satisfaction.
Last year (2017) highlighted the need for insurers to embrace the technologies that power touchless claims. The string of natural and man-made disasters, such as hurricanes Harvey, Irma, and Maria, and the California wildfires, left the insurance industry reeling from historic losses and competing for loss-adjusting expertise.
Touchless claims offer an answer by reducing the reliance on loss-adjusting resources following a disaster and keeping customers happy.
Insurers have made big strides recently in embracing technology across the value chain. Mobile tools, AI, machine learning, and data engineering are leading the charge.
At FNOL, self-service apps use built-in photos, videos and voice-to-text features, for near-instant claim notification and coverage verification. They can also prompt for images and annotations to verify the loss as part of the intake process.
Next up, the FNOL data feed is automatically fed into the carrier's claim platform and validated to create a loss report in line with carrier protocols. The platform's in-built analytics then trigger any further inspection needed. This could be using a drone, an inspection app, or even a field inspector. Drones have, notably, come into their own in catastrophe situations where aerial imagery is essential for external damage assessment but the location in is inaccessible to humans.
Recent innovations in the mobility and drone space have led to integrated measurement capabilities, as well augmented reality for 3600 views and 3D model creation in real-time. This is invaluable for the estimator and drastically reduces cycle times. For straight-forward claims, the business rules engine in the claims platform can adjudicate on the claims value, and set up payments or deny the claim as appropriate.
Computer vision in auto claims is getting a lot of press right now. With key machine learning players like Google opening up their open source software libraries, carriers, estimatics companies, and insurtechs are all getting involved.
Computer vision offers a way for carriers to train models to generate estimates (for repairs, parts or labor) for auto accident losses using images gathered by a third party, without the need for human intervention.
Insurers should be excited about this technology's impact. Pictures of an auto accident that show vehicle damage and repair needs, combined with algorithms trained on large volumes of image estimate data can confirm the damage, as well as the likely severity of the loss. Using computer vision, therefore, can help significantly improve cycle times and loss accuracy.