Predicting losses and risks are a keystone of the insurance industry. In addition, insurance companies usually have large amounts of data to sift through in a limited amount of time. The following case study reveals how two leading insurance companies impleted H2O in their data environments and developed faster and more accurate models a a result.DOWNLOAD THE GUIDE
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