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Dec 9, 2021
Min Read

AI for Claims Processing: Computer Vision Is a Super Power for Insurance Adjusters

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super.AI
Chief AI for Everyone Officer
SUMMARY

Claims processing is a core activity for every property and casualty insurer. After all, most people don’t think much about their insurance company until they need to file a claim. Typically, claims are filed when customers are at their most vulnerable, such as after a traffic accident or house fire. As a result, insurers have a short window of opportunity to make good on their promise to policyholders.  

Companies that are strategic in their efforts to improve insurance claims processing can expect higher levels of operational efficiency. While these efficiency gains are very real, an even greater advantage is the customer experience improvements that provide a competitive edge in the market. Happy policyholders are loyal customers, and that ultimately improves financial results over time.  

Claim an AI advantage

How can you build that advantage? While each claim is different, standardized elements of claims processing can be streamlined with the strategic implementation of new technologies like computer vision. Traditionally, after a policyholder files a claim with their insurance company for roof damage, for example, a property adjuster must go to that location and climb a ladder to assess the damaged roof in person. This process of inspection and claim settlement is time-consuming and potentially dangerous for adjusters. According to the US Department of Labor, property adjusters experience an average of  

78 injuries per million site working hours, which is almost four times the injury rate of the average construction worker.  

Computer vision is transforming claims adjustment  

Computer vision has the potential to significantly transform the claims adjustment process. Through the use of photographs, video, satellite images and even drones, computer-assisted inspections are now possible. Overall, computer vision can augment the effort of human adjusters to engage in more precise underwriting, reduce the need for adjusters to physically inspect properties, reduce human error and fraud, and significantly speed up the application and claims processes.

According to McKinsey’s Insurance 2030 Report, computer vision has emerged as a solution to transform the entire claims process. The approach guides customers through the process of capturing visuals while behind the scenes AI technology recognizes objects within those images, classifies the images, and routes the claims to the right agents or adjusters for immediate analysis and incident assessment.

Automate vehicle damage detection with AI image processing

One example is a photo claim service that allows drivers to submit photos of their vehicle’s damage on-site through their mobile phones. After a customer is involved in an accident, they can open the app on their smartphone and upload photos of both the damage and their entire vehicle. From there, AI-enabled applications, using tools like Super.Image, process the unstructured data using a combination of AI, Machine Learning software, and humans to highlight damaged areas of the vehicle. The system provides annotated images and converts the damage information into the text to power claims processing automation, ultimately cutting processing time and costs for insurers and their customers.

Automate property damage detection with AI video processing

Some insurance companies are using drones to deploy computer vision to perform property damage inspections. This helps automate damage identification and classification and provides the added value of reducing the risk of harm to adjusters. Since an inspection of the damage to a rooftop can be hazardous, especially in bad weather conditions or for large commercial properties located in remote or dangerous locations. A drone can easily capture detailed images of the roof, including parts of the structure that are difficult to access.

Using video captured with drones, AI-enabled applications are used to assess and classify property damage. Tools like Super.AI handle the complex job of analyzing thousands of images and video footage of claims damage and often expedite the claims adjustment process from a week to just a few days. Estimating an exact dollar amount for loss is still somewhat challenging for AI to predict, but there are many situations where relatively simple geometry is used to estimate the loss. Damage to a pre-fabricated home fabricated using a set amount of building materials, for example, is easily referenced, and the application quickly predicts the cost of a replacement.

Benefits of computer vision for insurance adjusters

It’s not surprising that analysts see computer vision as a prominent feature in the future of insurance. The claims process improvement benefits are many, for example:

  • Real-time validation and more accurate appraisals.
  • Expedited claim settlements, often after the First Notice of Loss.
  • Increased levels of customer satisfaction and loyalty.
  • Greater adjustor efficiency; reduced risk to adjusters.
  • Reduced fraud with secure photo/video evidence.

Additional AI for insurance resources

Computer vision technology is a powerful tool, allowing insurance adjusters to perform their jobs faster, more accurately and efficiently, and with greater safety than ever before. The approach helps insurers improve the process to determine damages, estimate necessary repairs, and identify and control risks. Look for providers and partners with the right combination of capability, experience and vision in order to make the most of your efforts. There are also more applications of AI in the insurance sector, for more information check out these resources:

  • Book a personalized demo to see how AI can benefit your specific insurance scenario.
  • Check out a case study that explores how a top U.S. insurance company leveraged super.AI.
  • Read our blog about how automated claims processing is changing the insurance world
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