SME default prediction is a long-standing issue in the finance and management literature. Proper estimates of the SME risk of failure can support policymakers in implementing restructuring policies, rating agencies and credit analytics firms in assessing creditworthiness, public and private...

Credit-risk models that are designed for general application across sectors may not be suitable for the construction industry, which has unique characteristics and financial risks that require specialised modelling approaches. Moreover, advanced bankruptcy-prediction models are often used to...

SME default prediction is a long-standing issue in the finance and management literature. Proper estimates of the SME risk of failure can support policymakers in implementing restructuring policies, rating agencies and credit analytics firms in assessing creditworthiness, public and private...

Latin America is a growing financial market. The performance of its private sector corporations is critical, as inadequate performance and financial distress can result in losses for many people. This study analyses the efficacy of Logistic Regression (LR) and Random Forest (RF) techniques for...

Banks have a vital role in the financial system and its survival is crucial for the stability of the economy. This research paper attempts to create an efficient and appropriate predictive model using a machine learning approach for an early warning system of bank failure. This paper uses data...

This paper proposes a methodology for default probability estimation for low default portfolios, where the statistical inference may become troublesome. The author suggests using logistic regression models with the Bayesian estimation of parameters. The piecewise logistic regression model and...