SYSTEMATIC LITERATURE REVIEW OF ADVANCEMENTS IN CORPORATE BANKRUPTCY PREDICTION - Mahmoud Elsayed Mahmoud; Taufiq Arifin (ZILLZELL MEDIA PRIMA, 2024)
This systematic review examines the evolution of corporate bankruptcy prediction models, synthesizing insights from a wide array of high-quality studies. Statistical methods, notably logit analysis and discriminant analysis, are predominant in bankruptcy prediction, but there is a discernible rise in the adoption of artificial intelligence techniques. Accounting-based methodologies, particularly accrual-based approaches, are prevalent, emphasizing the importance of financial ratios in assessing companies' financial health. By elucidating key trends and methodologies, this review aims to inform future research and enhance the effectiveness of bankruptcy prediction models in corporate finance.