Title :
Probabilistic estimation-based data mining for discovering insurance risks
Author :
Apte, Chidanand ; Grossman, Edna ; Pednault, Edwin P D ; Rosen, Barry K. ; Tipu, Fateh A. ; White, Brian
Author_Institution :
IBM Thomas J. Watson Res. Center, Yorktown Heights, NY, USA
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 :
data mining; insurance data processing; IBM´s underwriting profitability analysis application; ProbE data-mining kernel; insurance risks; noisy data sets; predictive models; probabilistic estimation-based data mining; risk-characterization rules; Companies; Data mining; Electrical capacitance tomography; Insurance; Kernel; Predictive models; Probes; Profitability; Risk analysis; Sensitivity analysis;
Journal_Title :
Intelligent Systems and their Applications, IEEE
DOI :
10.1109/5254.809568
