The Influence of Corporate Governance Quality on Financial Distress Prediction Models

Abstract

This study examines how corporate governance quality enhances the predictive power of financial distress models beyond traditional accounting and market based indicators. While ratio based and Altman type models remain widely used and effective as early warning tools, they tend to overlook institutional and governance related drivers of distress. Using a systematic literature review, this study synthesizes evidence from research that incorporates board structure, ownership configuration, and board diversity into financial distress prediction frameworks. The review shows that stronger governance, reflected in board independence, effective monitoring committees, and well-designed ownership structures, is generally associated with lower distress likelihood and better model classification accuracy. However, the effect of ownership concentration and gender diversity on distress risk is context dependent, varying across legal, cultural, and market environments. Overall, the findings indicate that corporate governance quality is a critical non-financial input for improving financial distress prediction, but it should be treated as a multidimensional construct rather than a single “good governance” proxy. The study highlights the need for integrated models that combine financial indicators with multiple governance mechanisms and calls for future research to test interaction effects and compare traditional, augmented, and advanced modelling approaches.