Proactively monitoring and assessing the economic health of financial institutions has
always been the cornerstone of supervisory authorities. In this work, we employ a series of …

We examine the failures of 132 US banks over the 2002–2009 period using discriminant
analysis and successfully distinguish between banks that failed and those that didn't 92% of …

We propose a new approach based on a generalization of the logit model to improve
prediction accuracy in US bank failures. Mixed-data sampling (MIDAS) is introduced in the …

Failures and FDIC losses for community banks during the banking crises of the late 1980s
and late 2000s are compared. Despite increases in risky commercial real estate (CRE) …

In this study, we test the predictive power of several alternative measures of bank capital
adequacy in identifying US bank failures during the recent crisis period. We find that an …

This study compares the predictive accuracy of a set of machine learning models coupled
with three resampling techniques (Random Undersampling, Random Oversampling, and …

This paper develops an early warning system for predicting distress for large European
banks. Using a novel definition of distress derived from banks' headroom above regulatory …

Utilizing a simple time‐varying hazard model, we incorporate nationwide and state‐level
economic variables with banking‐industry and bank‐level data to examine US bank failures …

Credit risk is associated with the banking activity and is the most important type of the risk to
which banks are exposed. Bankruptcy risk assessment is based on models using the …

The main purpose of this paper was to investigate the relationship between banks' credit risk
and profitability and liquidity shocks in Namibia for the period 2009 to 2018 using the SVAR …