Published Online:April 2026
Product Name:The IUP Journal of Applied Finance
Product Type:Article
Product Code:IJAF020426
DOI:10.71329/IUPJAF/2026.32.2.33-53
Author Name:Chinmay Vibhute, Siddharth Phadtare, Vidi Panwar, Abhay Kumar and Rajneesh Ranjan Jha
Availability:YES
Subject/Domain:Finance
Download Format:PDF
Pages:33-53
Prediction of bankruptcy is a part of financial risk evaluation, especially in the retail industry, which is highly competitive. A comparison of three popular financial distress prediction models—Altman Z-Score, Springate S-Score, and Grover G-Score—through cross-model comparison is made in the present study to assess their suitability in predicting bankruptcy in the retail industry. Based on a sample of financially healthy and financially distressed retail firms, the present study applies each of the above-named models to assess their predictability, sensitivity, and specificity. The results show different degrees of reliability among the above-named models, with high overall performance by Altman’s Z-Score, while Springate S-Score and Grover G-Score models show different performances with different sensitivity. The present study also points out the drawbacks of ratio-based bankruptcy prediction and the possibility of improvement through hybrid modeling techniques with integration of machine learning techniques. The results offer useful suggestions for investors, financial analysts, and policymakers for the detection of early warning signals. The results show different predictive performances of the said three models, with each showing different prognosis in respect of financial distress in the retail industry. Though each of the models shows utility in predicting bankruptcy, their performance is different with the financial indicators used and the particular characteristics of the firms analyzed.
The retail sector is of great importance to the Indian economy and is a very significant contributor to its GDP. The country’s labor resource formation is faced with the problem of heterogeneity of the target market, process of urbanization, and expansion of online trade.