Thakhani Ravele

You are already at the latest version Extreme wind speed poses significant risks to the economy in areas such as infrastructure and agriculture in South Africa, particularly in semiarid regions such as the Northern Cape. In minimizing such risks, accurate modelling of extreme wind speed is essential for disaster preparedness and climate adaptation.

You are already at the latest version Banking crises pose a constant threat to macroeconomic stability in emerging markets, where standard econometric Early Warning Systems (EWS) often fail to model nonlinear macro-financial relationships. This paper examines whether machine learning algorithms, rather than standard logistic regression, can improve forecasts of banking crisis risk in Nigeria.

You are already at the latest version Credit risk modelling is essential for assessing the likelihood of borrower default and supporting informed lending decisions. Despite advances in predictive algorithms, challenges remain in ensuring model transparency, reliability, and robustness to uncertain inputs. This study investigates integrating explainable AI (XAI) and uncertainty quantification (UQ) to enhance interpretability and confidence in credit risk predictions.