Richard A. Derrig

FRAUD CLASSIFICATION USING PRINCIPAL COMPONENT ANALYSIS OF RIDITs (2009)

Patrick L. Brockett, Richard A. Derrig, Linda L. Golden, Arnold Levine, Mark Alpert

This article introduces to the statistical and insurance literature a mathematical technique for an a priori classification of objects when no training sample exists for which the exact correct group...

ACOMPARISON OF STATE-OF-THE-ART CLASSIFICATION TECHNIQUES FOR EXPERT AUTOMOBILE INSURANCE CLAIM FRAUD DETECTION (2009)

Stijn Viaene, Richard A. Derrig, Bart Baesens, Guido Dedene

Several state-of-the-art binary classification techniques are experimentally evaluated in the context of expert automobile insurance claim fraud detection. The predictive power of logistic...

APPLICATIONS OF RESAMPLING METHODS IN ACTUARIAL PRACTICE (2008)

Richard A. Derrig, Krzysztof M. Ostaszewski, A. Rempala

Actuarial analysis can be viewed as the process of studying profitability and solvency of an insurance firm under a realistic and integrated model of key input random variables such as loss frequency...

Dedene, “A case study of applying boosting Naive Bayes to claim fraud diagnosis (2004)

Stijn Viaene, Richard A. Derrig, Guido Dedene

Abstract—In this paper, we apply the weight of evidence reformulation of AdaBoosted naive Bayes scoring due to Ridgeway et al. [38] to the problem of diagnosing insurance claim fraud. The method...

A comparison of state-of-the-art classification techniques for expert automobile insurance fraud detection (2002)

Viaene, Stijn, Derrig, Richard A., Baesens, Bart, Dedene, Guido

Several state–of–the–art binary classification techniques are experimentally evaluated in the context of expert automobile insurance claim fraud detection. The predictive power of logistic...