The insurance industry is one that is just beginning to tap into the potential of artificial intelligence.
If you’ve been monitoring the ImageNet challenge over the years, you know that AI’s image classification surpassed human accuracy about 18 months ago, indicating the technology is reaching a stable and mature state. Once a technology is customer-ready, it’s important that it’s also customer-centric — in that it solves an inherent problem. For insurance customers, that problem might center around a fender bender, or roof damage from a hail storm.
Using AI technology to automate a visual task, such as inspecting damage to a car, is a nearly instant way to provide insurance customers with crucial information about the extent of the damage.
For example, the customer could snap pictures of all sides of the car with their smartphone and upload the pictures into a new experimental app we’re creating that detects auto damage. Image classification AI within the app compares the customer’s photos with thousands of other anonymized crash photos to generate a cost estimate for their repair. Not only does this save time for customers, particularly in the case of a minor accident, but it also reduces uncertainty and worry during a stressful time.
After a machine vision algorithm assesses the auto damage, the customer can decide whether to get a repair done immediately or wait. For those who need or want to move forward with repair, AI could assist them through to the time they pick their car up from the auto body shop. Down the road, with the help of another machine learning algorithm, the driver could potentially receive a list…