A new study has found that artificial intelligence-enabled workers compensation claims management reduced legal involvement for lost-time claims by 15 percent.
Gradient AI, a software provider of artificial intelligence (AI) for the insurance industry, announced the results of a comprehensive research study indicating the reduction translates into a 5 percent savings in lost-time claim costs, equating to an estimated annual savings of $3.5 million based on the study’s insurers managing an average of $70 million in lost-time claims.
Lost-time claims are those where an injury is severe enough to require the injured employee to remain out of work for an extended period of time.
The savings was the result of early alerts to adjusters regarding injury severity and changes in claims status. The early alerts allowed claims staff the opportunity to pay additional attention and take proactive steps to arrange for additional medical treatment, Gradient AI said.
“Our goal was to better understand AI’s potential to deliver value and shape critical decisions around workers compensation claims,” said Stan Smith, CEO and founder of Gradient AI. “This study reaffirms that AI is a valuable tool in managing these claims, especially in avoiding costly legal fees and time-consuming litigation. The results not only show substantial cost reductions but also highlight AI’s potential to streamline the claims process, benefiting injured workers, employers, and insurers. It’s a win-win-win, making the results of the study particularly gratifying.”
To better understand the efficacy of AI models trained on industry data lakes, Gradient AI conducted analysis of over 200,000 lost-time workers compensation claims, collecting from a diverse pool of more than 60 insurance carriers over a 10-year period. Within this dataset, half of the 200,000 claims underwent assessment prior to the integration of AI, while the remaining half were evaluated after AI implementation.
The study also found that lost-time workers comp claims involving lawyers cost three times more than claims without legal involvement and lasted nearly twice as long.
In addition, the researchers found that insurers leveraging AI effectively reduced legal involvement by 15 percent because AI models were able to assess claim complexities, predict the likelihood of legal involvement and provide early warnings to claims adjusters.
Also identified by the study were three key factors that drive claimants to seek legal representation. They include:
Erosion of Trust: Trust between claimants and insurance adjusters may erode over time when claims are prolonged. AI mitigated this by expediting the process, reducing the need for claimants to seek legal assistance.
Fear of the Unknown: Claimants often seek legal counsel as a safety net when facing severe injuries or doubts about recovery. AI provided insurers with the ability to proactively address concerns, avoiding legal escalation.
Intent to Litigate: Some claimants are determined to pursue legal action. AI empowered insurers to intervene early, averting the potential for costly litigation.
The study demonstrated that the AI-generated early warnings enabled insurers to proactively manage claims much more efficiently and effectively.
“This research unveils how AI insights empower insurers to take proactive measures,” said Jeff Snider, GM of Property & Casualty, Gradient AI. “As an attorney, I recognize the importance of minimizing the cost of legal involvement. This study demonstrates how AI’s predictions provide adjusters with an early warning, enabling them to significantly mitigate legal involvement.”