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The objective of this research is to determine the optimal rating philosophy for the rating of SMEs, and to describe the consequences of the chosen philosophy on several related aspects. As to our knowledge, this is the first paper that studies the considerations of financial institutions on what rating philosophy to adopt for specific portfolios.The importance for banks to have a solid risk framework to predict credit risk of their counterparties is well reflected by the quality and the quantity of research on this subject. Moreover, a good risk framework is vital to become compliant with the new Basel II framework.Problem is that financial institutions nearly always neglect the first step in the rating model development process: the determination of the rating philosophy. It is very important for financial institutions to decide whether they want their internal rating systems to grade borrowers according to their current condition (point-in-time), or their expected condition over a cycle and in stress (through-the-cycle), because the rating philosophy influences many aspects such as: credit approval, pricing, credit and portfolio monitoring, the regulatory and internal capital requirements and the competitive position of a bank. This makes the question which rating philosophy to use very important.Moreover, many different modelling techniques exist to determine credit risk, but few attempts have been devoted to credit risk assessment of small commercial loans, although SME exposures are relatively important for European banks. SMEs have specific characteristics that influence the rating philosophy and therefore the development and use of credit risk models. These SME characteristics are taken into account in the analysis to determine the optimal rating philosophy.

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The objective of this research is to develop a structural form probability of default model for small and medium-sized enterprises, dealing with the methodological issues which arise in the modelling of small commercial loan portfolios. Other motivations are to provide an extensive overview of the characteristics of SMEs, and to provide a list of characteristics for an SME PD model, e.g. time and cost efficiency, broad applicability, limited data requirements, and powerful in predicting default. The structural form model is developed and tested on a unique dataset of private firm's bank loans of a Dutch bank. The results are promising; the model output differs significantly between defaulted and non-defaulted firms. The structural form model can be used on its own, or as an additional variable in a credit risk model. A second PD model is developed using logistic regression with a number of financial ratios, including the structural form measure. This variable is significant in default prediction of SMEs and has some additional predictive power, next to the popular financial ratios. Overall, the results indicate that the structural form model is a good indicator for default of SMEs.