Abstract
Past 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 non-parametric models to predict insurer insolvency. This study uses a neural network, a non-parametric alternative to past techniques, and shows how this methodology predicts insurer insolvency more effectively than parametric models.
Original language | English (US) |
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Pages (from-to) | 1-18 |
Number of pages | 18 |
Journal | Journal of Economics and Finance |
Volume | 19 |
Issue number | 3 |
DOIs | |
State | Published - Sep 1 1995 |
All Science Journal Classification (ASJC) codes
- Finance
- Economics and Econometrics