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By Nick Andersen

How artificial intelligence is changing agribusiness insurance claims

April 8, 2024

Artificial intelligence (AI) has made headlines around the world as its utility grows in different industries and economic sectors. Farm and commercial agribusiness insurance are among them.

As the technology evolves, different uses for it are emerging. Artificial intelligence “models” are the systems that analyze massive amounts of data to identify patterns, then make predictions and correlations based on them. Today’s AI models can analyze text, speech, audio and visual data. And generative AI models can generate new ideas based on that analysis.

AI as claims decision support

Specific AI algorithms can refine a model’s focus to a specific industry like agribusiness insurance and enable someone like a claims professional to work smarter. That’s especially important when time is of the essence.

Large language models (LLM) can ingest massive amounts of information through sources like medical bills, police reports and legal demand packages, then quickly summarize those documents to enable an adjuster to make more informed decisions.

“We’re using AI in various claim stages to enable our associates to make better, smarter and faster decisions. We think of them as decision support tools. This process provides direct and indirect benefits to agents and customers by way of better claim outcomes.”

– Brent Hanson, Nationwide Commercial Claims Director

At Nationwide, AI functions in the spirit of better, faster, smarter decisions to drive improved claims outcomes. It isn’t making decisions. Those are up to our claims professionals.

How AI is improving claims efficiency

There are three primary ways AI is creating new efficiencies in agribusiness insurance claims:

1. Severity recognition. In some cases, specific claim types become more severe as time goes on. Severity recognition diagnoses this trend. An AI model can help identify when severity is worsening and get the claim to the right adjuster at the right time. This enables agents to adjust coverage levels to ensure your customers have the right protection.

“Severity recognition with AI allows us to get to the right level of associate experience earlier in the lifecycle of the claim,” Hanson said. “It allows us to look for early settlement opportunities and identify trends.”

2. Litigation modeling. Some insurance claims are accompanied by litigation. When this happens, an AI model can be deployed to ingest legal information and identify the right legal representation for the right outcome.

“No one wants to be sued. We are a protection company and want to provide the best possible representation for the insured,” Hanson said. “An AI model can help us do that.”

3. Summarizing documentation. Insurance can involve a lot of paperwork and documentation. Consuming massive amounts of such information can take a lot of time. An AI model can help summarize data to help claims associates get more efficient.

“An AI model can consume and summarize large amounts of documentation in seconds that might take a human hours or days,” Hanson said. “In this way, AI creates efficiencies for the claims associate and allows them to focus on more technical issues relating to the claim.”

The future of AI in insurance claims

As AI continues to evolve at a quicker pace than any digital technology in decades, models will grow their capabilities by absorbing more data. As they ‘learn,’ they’ll become more predictive, opening doors for new use cases.

Nationwide continues to explore new ways to leverage the technology and its advancing capabilities. We’ll invest in tools that enable our team to drive the right claims outcomes more effectively for your customers.