Patrick L. Brockett

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Claims fraud is an increasingly vexing problem confronting the insurance industry. In this empirical study, we apply Kohonen's Self-Organizing Feature Map to classify automobile bodily injury (BI) claims by the degree of fraud suspicion. Feed forward neural networks and a back propagation algorithm are used to investigate the validity of the Feature Map(More)
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 membership is known. The article also provides an example of the empirical application of the methodology to fraud detection for bodily injury claims in(More)
This article introduces a neural network artificial intelligence model as an early warning system for predicting insurer insolvency. In order to investigate a firm's propensity toward insolvency, a feed forward, back-propagation methodology is applied to financial data two years prior to insolvency for a sample of U.S. property-liability insurers that(More)
Solvency is a primary concern for regulators of insurance companies, claims paying ability is a primary concern for policyholders, and return on investment is a primary concern for investors. These interests potentially conflict, and the decision-makers for the firm must trade off one concern versus another. Here we examine the efficiency of insurance(More)
This paper examines the relationship between risk, return, skewness and utility based preferences. Examples are constructed showing that, for any commonly used utility function, it is possible to have two continuous unimodal random variables X and Y with positive and equal means, X having a larger variance and lower positive skewness than Y, and yet X has(More)
This study examines the effect of the statistical/mathematical model selected and the variable set considered on the ability to identify financially troubled life insurers. Models considered are two artificial neural network methods (back-propagation and learning vector quantization (LVQ)) and two more standard statistical methods (multiple discriminant(More)
The causes of insurance cycles and liability crises have been vigorously sought, claimed, and debated by academic investigators for years. The model provided here partially synthesizes several stands of this literature and provides an additional cause. In addition to causes such as the loss-shocks and interest-rate changes included as explanations in the(More)