If you head on a road trip without first considering traffic reports, weather forecasts or recommendations from travel websites, you could end up stuck in a traffic jam, caught in a thunderstorm or visiting some place you didn’t intend to along the way.
Similarly, processing an auto insurance claim without collecting and considering key data and analytics, asking the right questions and using the right tools early on, can send the claim down a path filled with wasted time, extraneous expenses and a lot of headaches.
To process claims smoothly, effectively and efficiently, it is important to focus on collecting and analyzing the right data from the start – good data upfront supports good decision making throughout the claim lifecycle, ultimately enabling better auto insurance claim results. By using insights derived from early data collection and analytics, insurance carriers can appropriately triage the claim, send it down the right path and make data-driven decisions for both the physical damage and bodily injury portions of the claim.
Getting accurate information at FNOL prevents some problems with the claim later on in the process. (Photo: iStock)
Gathering information at First Notice of Loss (FNOL)
The best way for an insurer to get as much information as possible early in the process is simply to ask for it. The right technology solutions and adjuster best practices are a powerful combination. Adjusters should ask questions to gather complete information about the accident scenario and use insight to inform and customize smart questioning included in mobile or web-based FNOL solutions. These questions, whether from adjusters or automated tools, help to filter and properly triage claims as they move through the system.
Insurers should ask for the facts of loss, injury information and vehicle information, using adjuster inquiry as well as data collected from automated tools and as many accident photos as possible. Mobile FNOL tools, for example, can be configured to ask questions about the incident or guide customers through taking needed photos, while telematics and diagnostics systems can gather vehicle data and inform repair or settlement decisions.
Photos, contact information and other details will help streamline the process for insurers and policyholders alike. (Photo: Shutterstock)
Sending the claim down the right path
Once all of the important data points are collected during FNOL, insurance companies should use that information to help understand the exposures and send the claim down the right path. Early intervention can significantly streamline the auto repair claim by:
- Automating or assisting the shop and appraisal assignment process.
- Efficiently managing field appraiser schedules, travel time and workload.
- Routing vehicles to appropriate facilities for diagnostic scanning and proper repairs.
- Identifying vehicle or accident data not detectable with visual inspection.
- Streamlining the repair workflow and communication with the insurer and the claimant, improving overall satisfaction.
When it comes to the injury portion of the claim, the data collected at FNOL can help triage the claim based on injury type and expected severity. This helps route the claim to the right injury team from the start, preventing transfers down the line, costly potential delays and unnecessary rework.
Insurers can utilize data analytics to help determine hard costs and realistic damage estimates for claims. (Photo: Shutterstock)
Data-driven decisions in the claim outcome and settlement process
While collecting data and information at the onset of a claim is important, it is even more critical to use that data wisely, utilizing analytics throughout the end-to-end claims process to reach fair and accurate outcomes. One way to surface data insights is through an adjuster workspace which is designed to present the right data at the right time, specific to claim type and status and without information overload. This improves adjuster efficiency and helps decision-making with expert guidance and fact-based, easy-to-explain findings such as the likelihood of injury, relatedness, or expected and actual treatment timelines.
Increasingly, insurance carriers and solution providers can use smart technology solutions including machine learning and artificial intelligence to develop advanced analytics around the claim, the injuries, the auto repair estimate and the claim review process. This can help improve efficiency and inform decisions throughout the claims journey, while providing important insights that drive business decisions and instill confidence in the estimate process.
By focusing more heavily on early information gathering and gaining claim insights, an insurer can appropriately triage both auto damage and casualty claim severity, automate segments of the claims workflow, shorten cycle times, and provide adjusters with deep and actionable insights, ultimately achieving better claims outcomes.
Norman Tyrrell (Norman.Tyrrell@mitchell.com) is director of product management, Mitchell Casualty Solutions. Tyrrell directs the product management and strategic planning activities for the Auto Casualty Solutions division. Chris Bainer (Chris.Bainer@mitchell.com) is the director of product management, Mitchell Auto Physical Damage. Bainer leads new customer implementation initiatives and the claims product roadmap.
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