The scope of this study is to investigate the capability of AI methods to accurately detect and predict credit risks based on retail borrowers' features. The comparison of logistic regression, decision tree, and random forest showed that machine learning methods are able to predict credit...

While previous academic research highlights the potential of machine learning and big data for predicting corporate bond recovery rates, the operations management challenge is to identify the relevant predictive variables and the appropriate model. In this paper, we use meta-learning to combine...

The problem of SMEs in Indonesia as a "high-risk borrower" that has not been resolved until today. The purposes of this study was to analyze the financial literacy as mediating between corporate governance and SMEs' credit risk in Indonesia. This sample method used purposive sampling: 1273 units...