An examination of the efficiency of the marketing distribution channel and organizational structure for insurance companies is presented from a framework that views the insurer as a financial intermediary rather than as a "production entity" which produces "value added" through loss payments....

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...

This paper presents a class of utility functions (class A_\infty) that contains all of the utility functions commonly used for mathematical modeling: the class consisting of those utility functions whose derivatives alternate in sign. A simple representation via mixtures of exponential utilities...

The most important new development in the past two decades in the personal lines of insurance may well be the use of an individual's credit history as a classification and rating variable to predict losses. However, in spite of its obvious success as an underwriting tool, and the clear actuarial...

Customer-side influences on insurance have been relatively ignored in the literature. Using the household as the unit of analysis, this article focuses on the behavior of households having multiple policies of different types with the same insurance company, and who cancel their first policy....

This paper presents a definitive description of neural network methodology and provides an evaluation of its advantages and disadvantages relative to statistical procedures. The development of this rich class of models was inspired by the neural architecture of the human brain. These models...

Managerial efficiency is as important in social profit enterprises (SPEs) as it is for more traditional financial-profit organizations. In this regard, both donors and SPE executives use efficiency information in making decisions. Here, we suggest a linked, two-stage Data Envelopment Analysis...