For more on the application of predictive analytics and Insurance, attend PAW Business in San Francisco March 31-April 2, 2015, where there is a sequence of insurance-focused presentations. In my last article, I discussed how attention to data detail is even more paramount when building claim risk models for insurance companies. The attention to detail with the data is done, as our modeling objective is to optimize the differentiation of loss cost across the entire portfolio. The result of this data rigor is significant as the magnitude of savings in building predictive analytics solutions for insurance risk is much larger
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