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CNA applies big data technology to analyse unstructured data

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Big Data technology provides CNA with the cost, scalability and statistical advantages that address various challenges related to the claims function

Among its many data-oriented initiatives of 2015, CNA is also applying big data technology to workers’ compensation claims and adjusters’ notes.

“That is a classic, unstructured big data kind of problem,” says Nate Root, SVP of CNA’s shared service organization. “We have hundreds of thousands of worker’s compensation claims, and claims adjuster notes, and there is tremendous value in those notes.”

Root says the insurer recently began identifying workers’ compensation claims that have the potential to turn into a total disability, or partial permanent disability, without the right sort of attention. By examining the unstructured data, CNA has developed a hundred different variables that can predict a propensity for a claim to become serious, and then assign a nurse case manager to help the insured get the necessary treatments for a better patient outcome, get them back to work and lower the overall cost of coverage.

Leveraging Big Data technology provides CNA with the cost, scalability and statistical advantages that address various challenges related to the claims function. CNA is using a variety of technologies, including mainframe-based financial information. “We have enabled text mining off the claims adjusters’ notes, we run that through our predictive modelling approach with SAS and R, the open source statistical analytical software,”  adds Root.



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