International Research Journal of Education and Technology

 Predicting corporate bankruptcy is essential for maintaining financial stability and helping businesses, investors, and policymakers make well-informed and rational decisions. Traditional models, such as Altman’s Z-score, have been relied on for decades, but they often struggle to detect the intricate financial distress patterns that emerge in today’s rapidly evolving economy. With the developing impact of Fake Insights (AI), machine learning is developing as a game-changer, advertising more exact and convenient forecasts by analysing endless sums of budgetary information.   This think about investigates how AI-driven models can improve insolvency forecast and early caution frameworks. AI's capacity to prepare expansive datasets and reveal covered up designs makes it a capable device, but challenges stay. Issues like information quality, need of straightforwardness in AI decision-making, and administrative concerns still got to be tended to some time recently broad selection is conceivable. A overview of 20 youthful experts found that 65lieve AI is more viable than conventional strategies, however concerns approximately unwavering quality and explainability stay key barriers.   The discoveries highlight AI's potential to convert money related hazard appraisal, but victory depends on expanding mindfulness, moving forward show straightforwardness, and guaranteeing moral AI hones. As AI proceeds to advance, budgetary educate must contribute in instruction and administrative arrangement to saddle its full potential. Future inquire about ought to centre on refining AI procedures and guaranteeing compliance to form AI-powered insolvency expectation a trusted apparatus in monetary decision-making.

KEYWORDS
Artificial Intelligence, Bankruptcy Prediction, Early Warning Systems, Financial Distress, AI Adoption