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Anticipating financial distress: Leveraging financial information, financial ratios, and corporate governance for proactive risk management

Author

Listed:
  • Youssef Jouali
  • Sara El Aboudi
  • Reda EL AFI
  • Jamila Jouali

Abstract

This article presents significant findings from a logistic regression model that analyzes the factors contributing to corporate financial distress. It emphasizes the crucial role of financial information quality, financial ratios, and corporate governance in predicting financial distress. The study's results show that high-quality financial information can significantly reduce the likelihood of distress by enhancing investor confidence and facilitating access to capital. Effective corporate governance, on the other hand, can mitigate financial vulnerability through robust risk management and ethical leadership. The study also highlights the risk of distress associated with high debt levels, underscoring the importance of prudent debt management. Profitability, it finds, can bolster financial resilience by generating healthy cash flows. The study also identifies certain industries more susceptible to risk due to specific factors such as competition and technological disruptions. Interestingly, the study reveals that larger companies may present a slightly higher risk of distress due to the complexity of their management. In light of these findings, the study provides actionable recommendations for companies to enhance their financial reporting, adopt good governance practices, manage debt prudently, and assess sector risks to reduce the likelihood of financial distress, thereby empowering finance professionals, researchers, and stakeholders with practical tools to manage and mitigate financial risks effectively

Suggested Citation

  • Youssef Jouali & Sara El Aboudi & Reda EL AFI & Jamila Jouali, 2024. "Anticipating financial distress: Leveraging financial information, financial ratios, and corporate governance for proactive risk management," Edelweiss Applied Science and Technology, Learning Gate, vol. 8(4), pages 683-696.
  • Handle: RePEc:ajp:edwast:v:8:y:2024:i:4:p:683-696:id:1444
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