Adaptive Regression and Classification Models with Applications in Insurance

Jekabsons, Gints; Uhanova, Marina

doi:10.2478/acss-2014-0004

Abstract

Nowadays, in the insurance industry the use of predictive modeling by means of regression and classification techniques is becoming increasingly important and popular. The success of an insurance company largely depends on the ability to perform such tasks as credibility estimation, determination of insurance premiums, estimation of probability of claim, detecting insurance fraud, managing insurance risk. This paper discusses regression and classification modeling for such types of prediction problems using the method of Adaptive Basis Function Construction

References

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Adaptive Regression and Classification Models with Applications in Insurance

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