Probabilistic estimation-based data mining for discovering insurance risks
IEEE Intelligent Systems and their ApplicationsPublished 1 November 1999
Chid Apte, Emiliano Grossman, Edwin Pednault, Barry K. Rosen, Fateh A. Tipu, Brandyn White
Citations36
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TL;DR
IBM's underwriting profitability analysis application mines property and casualty insurance policy and claims data to construct predictive models for insurance risks and UPA uses the ProbE data-mining kernel to discover risk-characterization rules by analyzing large, noisy data sets.
Abstract
IBM's underwriting profitability analysis application mines property and casualty insurance policy and claims data to construct predictive models for insurance risks. UPA uses the ProbE data-mining kernel to discover risk-characterization rules by analyzing large, noisy data sets.
Keywords
Computer Science
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