The main contribution of this paper is the construction of a cyclical systemic risk indicator from early warning indicators of banking crises (EWIs) used in Finland. Previous research has shown that combining EWIs can enhance their early warning properties. This study evaluates the indicator's...

This study utilizes machine learning models, including Logistic Regression, Support Vector Machine, Decision Tree, and Random Forest, in the early warning system for debt group migration in a Vietnamese commercial bank. In predicting customers' overdue debt migration (B Score), the RF model...

Abrupt changes are a prevalent feature of financial data sets, such as prices of financial assets, returns of stocks, exchange rates, etc. An early warning system (EWS) can detect existing changes and predict possible future changes before they occur. Two important statistical models for change...