The current standardized approach for assessing credit risk under Basel III depends on ratings assigned by credit rating agencies (CRAs). However, this approach presents three problems. First, the definitions of ratings used by CRAs to assess the likelihood of default and recovery rates are not...

A firm's current leverage ratio is one of the core characteristics of credit quality used in statistical default prediction models. Based on the capital structure literature, which shows that leverage is mean-reverting to a target leverage, we forecast future leverage ratios and include them in...

FinTech online lending to consumers has grown rapidly in the post-crisis era. As argued by its advocates, one key advantage of FinTech lending is that lenders can predict loan outcomes more accurately by employing complex analytical tools, such as machine learning (ML) methods. This study...

In this paper, we use a logit model to predict the probability of default for Korean shipping companies. We explore numerous financial ratios to find predictors of a shipping firm's failure and construct four default prediction models. The results suggest that a model with industry specific...

Predicting default probabilities is at the core of credit risk management and is becoming more and more important for banks in order to measure their client's degree of risk, and for firms to operate successfully. The SVM with evolutionary feature selection is applied to the CreditReform...

The current standardized approach for assessing credit risk under Basel III depends on ratings assigned by credit rating agencies (CRAs). However, this approach presents three problems. First, the definitions of ratings used by CRAs to assess the likelihood of default and recovery rates are not...