Vol. 2 No. 6 (2024): December
Open Access
Peer Reviewed

SYSTEMATIC LITERATURE REVIEW OF ADVANCEMENTS IN CORPORATE BANKRUPTCY PREDICTION

Authors

Mahmoud Elsayed Mahmoud , Taufiq Arifin

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Received: 2024-06-06
Accepted: 2024-08-26
Published: 2024-11-17

Abstract

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.

Keywords:

Corporate Bankruptcy Prediction Logit Analysis Artificial Intelligence Financial Ratios

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Author Biographies

Mahmoud Elsayed Mahmoud, Foreign Students Faculty of Economics and Business, Sebelas Maret University, Egypt

Author Origin : Egypt

Taufiq Arifin, Faculty of Economics and Business, Sebelas Maret University, Indonesia

Author Origin : Indonesia

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How to Cite

Mahmoud Elsayed Mahmoud, & Taufiq Arifin. (2024). SYSTEMATIC LITERATURE REVIEW OF ADVANCEMENTS IN CORPORATE BANKRUPTCY PREDICTION. International Journal of Accounting, Management, Economics and Social Sciences (IJAMESC), 2(6), 1913–1935. https://doi.org/10.61990/ijamesc.v2i6.283

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