Credit to personal consumption is an important activity of the financial system and crucial to the socioeconomic development of a country. It is important, therefore, that the methods and techniques used to evaluate consumer credit risk be as efficient and informative as possible, in order to strengthen decisions to approve or reject credit and promote sustainable economic growth. This study aims to create a multiple criteria expert system which integrates cognitive maps and the measuring attractiveness by a categorical-based evaluation technique (MACBETH) to create a complementary framework for consumer credit risk assessment. The results show that this integrated approach allows the evaluation process of consumer credit risk to be more informed and transparent, providing value for the evaluation processes of this type of credit application as a result of the privileged contact established with a panel of credit analysts. Advantages, limitations, and managerial implications are also discussed.
A random thinning model with a latent factor for improvement of top-down credit risk assessment