Human in the Loop AI for Claims Guidance

With the news of our Series A funding, a spotlight is being thrown on how EvolutionIQ isn‘t just building new tools or a better mousetrap but is instead creating an entirely new technology category. As VentureBeat underscored: EvolutionIQ has developed what it calls the first human-in-the-loop artificial intelligence (AI) claims guidance technology for the insurance industry.

The story, EvolutionIQ unveils its AI-driven tech to reduce the cost of insurance claims, explains how the platform use deep learning, an advanced branch of machine learning, to actively monitor every open short-term and long-term group and individual disability, worker‘s compensation and property and casualty claim under an examiner‘s purview to guide them to those that require more attention, new actions or complex decision-making. It will generate a list of the handful that are most actionable, along with a deep explanation as to why and the outcome they should be aiming for.

EvolutionIQ CEO and co-founder Tom Vyjruta told the publication that adjusters can be overwhelmed with vast amounts of complex cases that can each last for years, be worth hundreds of thousands of dollars, and be hundreds of pages in length with data in both structured and unstructured formats.

Furthermore, These are impossibly complex problems because there is bodily injury, he said. You have to be a doctor in many cases to understand cases of comorbidities. There are way too many complex problems and far too few people to be able to sift through them.

Notes VentureBeat: That said, the deep learning, human-in-the-loop AI system must have people plugged Examiners are not eliminated; rather, they contribute to the system as it constantly learns, evolves and recalibrates based on new data and events.

Dealing with bodily injury is a truly complex task and a huge data problem, Vykruta said. The system has to partner with human experts.

Read the VentureBeat story

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