A Nonparametric Approach to Evaluating Reinsurers' Relative Financial Strength

There have been a number of past attempts aimed at using financial data of individual companies to produce predictive models of insurance company solvency. These models have come in two forms: parametric and nonparametric. For example, the NAIC, with its Insurance Regulatory Information System, is taking a nonparametric approach to this problem, which the AIA has used a parametric approach in producing its formula for assessing an insurer’s financial strength. However, when used to evaluate a reinsurer’s financial strength, these two systems have several shortcomings. For example, these models were developed by analyzing a primary company data base, and it is not clear whether a model created for primary companies will be effective when applied to reinsurance companies. Additionally, the criteria against which the models measure a company’s financial strength are fixed, and thus do not reflect each year’s changing economic conditions. Since economic conditions alter the value that a ratio can have, this could be a serious defect. The model that is presented in this article uses properties of a ranking distribution. The Wilcox on rank sum test is initially used to determine which financial ratios have historically discriminated between "strong" and "weak" companies. For those ratios that are selected as good discriminators, the test ranks are summed for each company. This statistic is then used as a measure of relative financial strength. Since each year is considered separately, it is assumed that economic conditions of that year will affect all the companies’ ratios similarly. It is hoped that this procedure will self-adjust in response to these variable conditions, and provide a more accurate and consistent indicator of a reinsurer’s relative financial strength. Reinsurance Research - Risk Loads/Profitability