Insurance companies sell protection to policy holders against many types of risks: property damage or loss, health and
casualties, financial losses, etc. In return for this risk protection, insurance companies receive a premium from the policy holder,
which is used to cover expenses and the expected risk. For longer-term risk protections, part of the premiums are invested to get
higher yields. Although the protection buyer mitigates the individual risk to the large and better diversified portfolio of the
insurer, it does not mean that the risk is completely reduced since the insurer may default his obligations. Insurers need to have
sufficient equity or buffer capital to meet their obligations in adverse conditions when their losses on the diversified portfolio
exceed the expected losses. Ratings provide an assessment of the ability of the insurer to meet its obligations to policy holders
and debt holders. In this paper, the relationship between financial ratios and the rating is analyzed for different types of
insurance companies using advanced statistical techniques that are able to detect non-linear relationship. The resulting rating
model approach is similar to the approach for a low default portfolio, which uses a common set of explanatory variables (such
as capitalization, profitability, leverage and size) which is generally applicable for all insurance types, and is complemented with
insurance type specific ratios. The resulting model is found to yield a good accuracy, with 75% of the model ratings differing at
most one notch from the external rating.