- Top challenges mentioned by respondents include lack of sufficient data and limited numbers of skilled modelers.
- Using additional data attributes is the most promising avenue seen by survey respondents to increase the power and quality of models built today.
- The most common use of predictive analytics is for pricing, where 71 percent of respondents use predictive modeling either always or frequently.
- Companies spend considerable time on data preparation and deployment before and after actual modeling work. More than half of survey respondents (54 percent) spend more than three months on data extraction and preparation, and more than two-thirds of the respondents (69 percent) take more than three months to deploy new models.
- The role of big data in modeling initiatives is predominantly a big company affair at this point. Of the companies with more than $1 billion in gross written premium (GWP), 51 percent either currently use big data or are evaluating or implementing big data initiatives, compared with 30 percent of the companies with less than $1 billion GWP.
Majority Of North American Insurance Companies Use Predictive Analytics To Enhance Business Performance, New Earnix/ISO Survey Shows
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