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Using AI as the "Prep Cook" for the Claim Analyst and Underwriter

Most Claim and Underwriting operations are undoubtedly facing the dual-impact of COVID-related productivity challenges and increasing volumes. It may actually be a triple-threat when you account for the increased risk of misrepresentation and fraud during turbulent times. Resources and budgets are stretched, but investigation and risk assessment practices need to be as robust as ever to consistently get to the right decision, and good customer communication in this time of need is critical. In other words, this is no time to relax risk management or customer-facing service standards.

For these organizations, where the medical record remains the richest and most complete source of information for risk management, advanced AI tools can now minimize the time-consuming task of reviewing and absorbing hundreds of pages of complex information. This allows valuable and highly-trained Claim Analysts, Clinical Resources, and Underwriters to focus their time on making and communicating file plans and decisions.

Advanced AI in the form of Natural Language Processing (NLP) is now able to review, understand and accurately summarize hundreds or thousands of pages of typical medical records in minutes, a task that takes these insurance professionals hours of time. The information can be presented in a way that makes the next steps for the user – the analysis and decision – extremely efficient and consistent. Even better, AI tools don’t get tired or bored of the monotony.....they remain perfectly focused on the task of prepping the file in a way that enables the end-user to put his or her best skills to work. AI can do the hard work so people can do more and more of the important work.

It’s like a prep cook for the head chef. The prep cook does the tedious work of gathering, washing, chopping, dicing, and measuring ingredients, and then laying them out for easy access. The chef’s job is to create the final dish with a focus on the important things: quality, consistency, and customer satisfaction. Isn’t that where Claim Analysts and Underwriters should be applying their most valuable skills?

This is a perfect example of what has become known as the AI-Human Interface. For the greatest combination of speed, efficiency, consistency, and effectiveness, keep people focused on the tasks they do best and let the machines do the hard work.

Here are a few common questions about using AI-NLP in this way:

  • Is it accurate and complete? In several case studies using 1500-page medical records, AI-NLP identified twice as many relevant* data points (conditions, treatment, outcomes, etc.) as the insurance company physician. Not surprising at all when you consider how difficult it is for humans to concentrate for hours at a time on anything, particularly complex information. (*relevant means pertinent to the risk being assessed)

  • How fast is it?: It took the AI-NLP 3-4 minutes to review each record and create the summary versus several hours for the physician.

  • How much time can it save our key resources? The comprehensive summary of the records produced by AI-NLP is allowing Claim Analysts and Underwriters to analyze the results and move on to their next task in a fraction of the time – it is becoming common to see 80% gains in efficiency (and a similar reduction in related labor costs).

  • What about integration with existing Underwriting and Claim processes? Utilizing a SaaS model, integration of an AI-NLP solution into operating workflows can be quick and painless. It’s simply a matter of getting the records from point A to point B and back to A.

It's time to bring AI into the kitchen, so to speak, to unleash the full potential of claim and underwriting organizations.

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