摘要：This study is a follow-up to two other studies carried out with other scholars in 2012 and 2014 respectively. While the two studies combined principal component analysis (PCA) with discriminant analysis (DA),this study extends its fron tier by developing an integrated early warning signal which pools PCA with three standard statistical models including DA,logit and probit models to determine the health status of Nigerian banks. The results show that discriminant analysis,logit and probit models are credible predictors of a bank’s financial status. The results indicate key variables that are significant to the performance of a bank including variables that measure profitability,liquidity,credit risk and capital adequacy because their coefficient estimates exhibit consistently statistical significance in the three models. It can thus be concluded that an early warning model predicated on a comprehensive analysis of a bank’s financial opera?tions concomitant with an adoption of discriminant and logit cum probit estimations could serve as a device for effec?tive supervision to maintain a safe and sound banking system. Applying the research methodology employed in the study to a more all-inclusive data set that enables the estimation of these prediction models could reveal additional insights into the processes that engender financial distress of Nigerian banks.
