Abstract
Past research studies have documented the failure of the Insurance Regulatory Information System (IRIS) to provide adequate warning of insurer financial distress or insolvency. As a result, scholars have examined alternative parametric and nonparametric models to predict insurer insolvency. This study uses a neural network, a non-parametric alternative to past techniques, and shows how this methodology more effectively predicts insurer insolvency than parametric models.
Recommended Citation
Gross, Ernest P. and Vozikis, George S., "Prediction of Insolvency of Life Insurance through Neural Networks" (2000). ECIS 2000 Proceedings. 17.
https://aisel.aisnet.org/ecis2000/17
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