Viewpoint: Reinventing Injury Claims Processes

There’s no denying that COVID-19 accelerated the digital transformation already well underway throughout the property/casualty insurance industry.

Although many carriers hesitated to digitize various aspects of their claims process prior to COVID-19 – primarily due to challenges with their legacy systems among other issues – their positions changed as individual states began issuing stay-at-home orders in the early months of the pandemic.

Shortly thereafter, a growing number of carriers began implementing digital solutions to facilitate omnichannel customer communication and remote claims processing to safeguard employees and customers from exposure to COVID-19.

Yet even though the use of these new technologies helped improve customer experiences and compressed claims cycle times, launching digital interfaces didn’t completely automate the claims management process. For instance, claims handlers still had to manually validate information through online searches about claimants, third parties, and vendors.

Now, however, by leveraging artificial intelligence (AI) and publicly available data on the web, some carriers are enhancing their digital claims capabilities by automating these searches. This allows them to verify key claims information earlier than previously possible.

Breaking paradigms: Reinventing the FNOL process for validating claims

Before performing automated damage assessments or launching digital interactions, claims handlers historically telephoned claimants at first notification of loss (FNOL) to verify and update policyholder information.

Claims handlers also had to gather additional information when third parties were involved. Before reaching out, adjusters typically performed manual online searches to verify claimants’ identity, phone numbers, addresses, accident details, and other pertinent information.

Similarly, adjusters may have manually gathered critical information about medical and other service providers not part of the carrier’s network, including: their ability to provide appropriate medical treatment or address other needs; reputation; proximity to claimant; hours of operation, and accessibility.

In following such a regimen, once this information had been collected and verified, adjusters could then proceed to develop and implement strategies to move the claim forward.

Besides being time-consuming and frustrating for claims adjusters, this process often resulted in sub-optimal customer experiences as claimants may have been required to repeat their stories or verify information multiple times.

Tapping social media, web data to automate claims intake

Today, new and emerging data sources are revolutionizing this process. Notably, claims handlers have been able to gather the information needed on claimants, third parties, providers and service vendors by accessing the tremendous volume ofpublicly available data online through such sources as: Facebook, Instagram, Twitter, Yelp, White Pages, news outlets, blogs, and online forums.

An analysis of more than 15 million injury claims found individual claimant information posted on an average of 32 uniform resource locators, or URLs. These URLs contain a treasure trove of information, including work history, phone numbers, email addresses, financial status, fitness activity and accident reports.

Using advanced AI models and data analytics, carriers can leverage this data to create efficiencies in the injury claims intake process by automatically verifying and validating information, such as: type of phone (burner, mobile, etc.); language preferences; financial and medical issues; email addresses associated with multiple individuals or claims; accident details, and other relevant data.

Significantly, data gathered from various external sources can supplement historical claims data. They can also enhance in-house models by facilitating more precise claim segmentation and faster decision-making.

Based on the experience of several leading U.S. regional property/casualty insurers, injury claims can be automatically segmented using new and emerging data sources into the following buckets:

• Low risk. Roughly, 80% to 82% of all injury claims fall into this category. Even if facts are clear, the standard historical process for validating these claims involves multiple phone calls and interactions to gather information required to move the claim forward. Yet, using alternative data sources, carriers can automatically identify low-risk (and otherwise high-touch) claims and promptly take appropriate action, such as: paying the claim and closing it; automatically routing claims to less-experienced adjusters; launching digital interactions and generating automated assessments.

• Intervention: Nearly 20% of claims require some sort of intervention. For instance, claimants may have been interviewed in the media about their accident or published blog posts documenting their recuperation from injuries. Carriers may be able to avoid litigation by automatically routing these claims to adjusters with experience resolving these types of claims.

• Hard fraud: As many as 2% of all injury claims involve cases of hard fraud. As an example, a third party provides a burner phone number and an email address tied to multiple individuals. These claims can be automatically routed to special investigative units for thorough evaluation.

The combination of advanced AI, data analytics, and publicly available data sources is providing a wide range of carriers in the U.S. and other parts of the world with a consistent and scalable way to validate incoming injury claims, reduce loss adjustment expenses, compress claims cycles and accelerate claim resolutions and payments. In addition, by leveraging AI and new data earlier in the claims cycle, carriers also can maximize their overall digital return on investment.