The main purpose of this paper is to study the problem created by the lack of information about the credit history of some debtors in the databases used to develop credit scoring models and the use of information about behavior compiled by a credit risk register as a potential solution to the...

This research shows the application and performance of three models for the classification of credit applicants: discriminant analysis, logistic regression and neural networks; techniques used by financial institutions for the calculation of credit scoring. The results show a better performance...

The literature that examines structural gender differences in behaviour and contributes to understand the lower rates of non-performing loans of women compared to men concerns different disciplines, such as sociology, psychology, law and economics. Although there are still critical gaps in this...

The purpose of this paper is to estimate the default probabilities in infrastructure projects. For that, we analyze the exposure of the lenders to a state of default. This application is made by assuming the debt service coverage ratio (DSCR) dynamic itself and the payment profile determined by...

Facing an hypothetical, but increasingly, case of default risk on a mortgage or a fall in interest rates, an important issue raised by the borrower is the possibility of minimizing that risk by selecting the best refinancing option. In this paper, a mortgage refinancing model is presented,...

In this paper, we explore the impact of the COVID-19 pandemic on the credit risk of large European companies. We selected corporations belonged to the EuroStoxx 50 Index and whose CDS (Credit Default Swap) may be found in the iTraxx Europe Index. Then we applied the methodology of event studies...