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.