Integrating Corporate Governance and XBRL Technology to Enhance Financial Crisis Prediction Models

The ability to accurately predict financial crises is of paramount importance for investors, regulators, and corporate management. Financial distress can have cascading effects throughout the economy, leading to significant losses and instability. Traditional financial crisis prediction models have primarily focused on quantitative financial ratios derived from accounting statements. While these models have provided valuable insights, they often fall short by neglecting the crucial qualitative aspects of corporate governance (CG). This research aims to study the impact of integration between corporate governance and Extensible Business Reporting Language (XBRL) technology on the efficiency of financial crisis forecasting models. Many large companies face financial crises due to poor financial disclosure and low governance, which leads to low confidence in the financial markets. The research provides a theoretical framework for the definition of XBRL and its importance in financial disclosure, achieving transparency and reducing the likelihood of errors. It also highlights the impact of corporate governance through indicators such as board independence, ownership of major owners, and institutional ownership, on the quality of financial reports published using XBRL, and shows how this technology can support governance principles, improve the transparency of financial information, enhance the accuracy of financial crisis forecasting models and increase the efficiency of stock markets.