Media Round-up: Deep Learning AI and the Transformation of Insurance Claims

Our news about $21 million in Series A funding sparked coverage across an array of publications specializing in insurance, technology, and venture capital investments.

The financial experts such as Wall Street Journal Pro VC, Fortune Term Sheet, Pitchbook, Fintech Global and more focused on the substantial dollar amount, market timing, and key players involved, such as round leader Brewer Lane Ventures. Meanwhile, insurance industry outlets such as Reinsurance News, Insurance Journal, Coverager, The Insurer, Inside P&C – as well as business publications such as VentureBeat, The AP, Axios, and others – highlighted the distinct approach and technology that EvolutionIQ is bringing to carriers.

As VentureBeat writes: “EvolutionIQ has developed what it calls the first human-in-the-loop artificial intelligence (AI) claims guidance technology for the insurance industry.”

Their story, EvolutionIQ unveils its AI-driven tech to reduce the cost of insurance claims explains how the system will “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.”

They underscore that “the deep learning, human-in-the-loop AI system must have people plugged in…Examiners are not eliminated; rather, they contribute to the system as it constantly learns, evolves and recalibrates based on new data and events.”

Meanwhile, an array of technology publications including TechCrunch, Techio, iTechNews, Global FinTech Series, TechNews 247 and more zeroed-in on the deep learning powering EvolutionIQ’s platform and how the insurance industry is undergoing a transformation thanks to that kind of next generation AI.

As TechCrunch reports: “Informed by its predictive algorithms, EvolutionIQ spotlights dozens of claims from tens of thousands that are most likely to have the greatest outcome for claimants, carriers and clients. EvolutionIQ also monitors open claims to guide workers to those that require more attention or new actions, including claims that have potentially fallen through the cracks.”

As EvolutionIQ CEO and co-founder Tomas Vykruta told TechCrunch, the key to AI adoption is “building ‘explainable AI’ systems in tight collaboration with the users. There [must be] two systems: one that makes predictions [and] one that explains the forecasted outcomes in [plain] language.” The explainability approach makes it clear to the adjuster what sort of factors led to the platform’s decisions.

EvolutionIQ’s platform evaluates the history of claims, asking questions such as, “Is this a claim on which we can take action?” and “Is there going to be an outcome that makes sense?” TechCrunch writes. “[I]nformed by its predictive algorithms, EvolutionIQ spotlights dozens of claims from tens of thousands that are most likely to have the greatest outcome for claimants, carriers and clients. EvolutionIQ also monitors open claims to guide workers to those that require more attention or new actions, including claims that have potentially fallen through the cracks.”

“Claims examiners want to focus on the cases that have the greatest impact on customers and carriers,” Tom added. “But claims handling involves archaic and manual processes that require examiners to review too much information or to evaluate data on their own, despite the fact that each claim involves multiple people and systems. Therefore, we built a decision intelligence platform that acts as an AI-enabled copilot to identify high-opportunity claims early in the lifecycle and cases most likely to be referred to adjusters.”

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