Models of Credit Risk for Emerging Markets

Abstract

The problem of accurate credit risk evaluation is well-known in the world of financial markets. This paper develops a series of credit risk models using multiple discriminant analysis (the MDA) for selected emerging markets within which Financial company A (FcA) provides credit. This paper investigates the discriminating power of various explanatory variables to distinguish between good and bad credit risks within each selected market in order to develop new market-specific credit scoring models for FcA. A comparative analysis of the classification accuracy of these new models and the existing model used by FcA is conducted. This analysis shows that the new models are robust and classify credit risks significantly more accurately than the existing model.