How AI Can Help Reduce Litigation and Severity

Private passenger claims collision severity has reached a record of $5,743 in Q1 2022, up 36% in the same period in 2020, while the average verdict for a lawsuit with more than $1 million awarded had increased 10-fold in the last decade to $22.3 million according to American Transportation Research.

Artificial intelligence (AI) combined with natural language processing (NLP) can be a critical intervenor in this space, identifying actionable insights to lower severity and prevent litigation. The industry is significantly feeling the heat of such huge payouts, and the top reason for such numbers is social inflation specific to bodily injury claims. Avoiding litigation is critical to the bottom line, and InsurTech can be the real game-changer in understanding past claims data and making calculated, insightful decisions to avoid litigation. Putting together data-driven decisions by looking at unstructured data and understanding severity prediction can help the entire decision-making process if the industry is keen to address this soon.

Claims Examiners are responsible for documenting the status of open claims under investigation and are the most crucial cog in the wheel. They are the decision-makers, and while they may not have the scope to go through humungous amounts of data and understand nuances, they can benefit from having an ‘AI-Led Cyber Supervisor’ helping them in the process.

The NLP insights follow the Rule of Three for InsureTech best practices :

  1. Cut the claims cycle times.
  2. Reduce claims expenses.
  3. Manage reserves and risks better.

By helping the claims adjuster make data-driven decisions based on artificial intelligence-generated insights, the outcomes help reduce claims expenses, cut short claims cycle times, and avoid litigation, all of which can improve the insured’s claims experience.


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