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10 Data Fields That Predict Litigation in Commercial Auto Claims

After years of record losses, commercial auto insurance carriers experienced a reprieve at the beginning of the COVID-19 pandemic as many drivers reduced time on the road. However, 2021 saw loss ratios shoot high once again, often surpassing pre-pandemic levels.

There are a multitude of factors that impact loss ratios, including increased severity of accidents and rising repair costs, as well as escalating litigation. Profitability depends on risk management, especially identifying and implementing viable strategies for commercial auto claims adjusters to prevent or reduce the impact of attorney involvement and litigation.

Artificial intelligence (AI) can analyze claims data to improve these outcomes.

While most experienced adjusters would know that certain claims details are signs of likely attorney involvement and potential eventual litigation, AI can improve the speed and accuracy with which this data is assessed. There are five types of structured data adjusters need to look for to determine probable attorney involvement and impending litigation described in the free white paper that you can download below.

Structured data isn’t the only data that has value. Unstructured data can be used to predict attorney involvement and litigation. We outline five key unstructured data indicators in the database.

Download the white paper now

Tyler Jones

Tyler Jones, Chief Customer & Marketing Officer of CLARA Analytics, is an experienced leader in using data, analytics and AI to solve complex business problems. He oversees the company’s customer success team whose primary goal is to drive customer AI adoption and measure the value generated by CLARA's leading commercial casualty insurance models.

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