Utopia AI, the one that successfully mimics (good) human behaviour.

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Welcome to the future

The future is machines taking care of responsible duties, including the treatment of insurance claims. In fact, the future is here, and it’s bright. Artificial intelligence (AI) is able to handle claims ethically, fairly, transparently, and with greater consistency than humans can. But not everything sold with an AI label is real AI. How do you spot a fake?

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The most advanced AI is machine learning. A high-quality AI system mimics human behaviour. Unlike humans, however, AI doesn’t do anything on its own. The actions of AI should be based on how humans work at their best. This means that AI has the skills to model the actions humans take in processing claims and related documents.

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We humans have an amazing ability to use all the information we’ve learned in our lives and apply that to decision-making. For example, in the insurance industry, field experts know in detail how legislation and regulation impacts decisions. They can interpret the inaccurate and misleading language sometimes used by policyholders. They’re capable of noticing when something isn’t right, or when something is missing or even fraudulent.

Advanced AI, trained through the decisions made by the experts, doesn’t need to be fed with a lawbook. Such an AI model uses the business rules on a level only a human can.

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Higher quality and faster claim handling

Why AI? And why Utopia AI Claim Handler?

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For the insurance industry, this is easy to answer. AI automates tasks that are rather simple in nature but high in volume. Utopia AI is the only AI on the market that learns solely from humans and works in any language. It frees human resources for activities that are more important for the company and its customers. It increases both the level of quality and the speed of service. It’s user-friendly, tailor-made, trustworthy, ethical, future-proof, and fast.

Utopia’s latest white paper “Utopia AI Claim Handler automates insurance claim process in 2 weeks” got more in depth on this discussion.