Due to the growing complexity and unpredictability of contemporary markets as evidenced
by the financial crisis of the past ten years, the field of financial distress prediction (FDP) …

This systematic review examines the evolution of corporate bankruptcy prediction models,
synthesizing insights from a wide array of high-quality studies. Statistical methods, notably …

Predicting financial distress accurately is not only important for the financial health of listed
companies but also vital for investors, regulators, and other stakeholders. Recent studies …

Imbalanced datasets are one of the main issues encountered by artificial intelligence
researchers, as machine learning (ML) algorithms can become biased toward the majority …

Soumya Ranjan SETHI* Dushyant Ashok MAHADIK Abstract. Financial distress prediction
has been an important area of discussion in the recent years. In this context, the paper …

An effective enterprise financial distress prediction system is one of the key measures to
prevent and resolve enterprise debt risk. However, it lacks enough and deep research on …

This article takes the interactive platforms of the Shenzhen Stock Exchange and the
Shanghai Stock Exchange as a vertical domain-specific dialogue platform. Firstly, it …

This study provides a comparative analysis of two widely used bankruptcy prediction models—
Altman's Z-Score Model and Zmijewski's X-Score Model—applied to companies listed on the …

The prediction of financial distress in companies, due to its adverse effects on debt holders
such as financial institutions, has been extensively studied in the field of finance. In this …

This study utilizes deep learning in natural language processing to predict financial distress
by analyzing concealed qualitative information in corporate annual reports. Word2Vec and …