Name: Yogita Kumawat & Monty Kanodia
Country: India

Year: 2025
Volume: Volume-12, Issue-2 (July-December)
Page Number: 233-246
DOI: https://doi.org/10.5281/zenodo.17646222

ABSTRACT
Financial distress refers to a situation where a company struggles to meet its financial
obligations, which may eventually lead to bankruptcy if not addressed. Accurate prediction
of financial distress becomes essential for stakeholders to make informed decisions and
manage financial risks effectively. The primary objective of this study is to predict the
financial distress of Indian automobile companies by applying the Altman, Springate, and
Grover models, and to evaluate the predictive accuracy of these models for firms listed on the
National Stock Exchange (NSE) during the period 2014–15 to 2023–24. Adopting a
descriptive research design, the study employs both quantitative and panel data approaches.
Descriptive statistics, normality tests, and one-way ANOVA were used in the analysis. The
empirical findings reveal that the Grover model demonstrates the highest predictive accuracy
at 96%, followed by the Springate model at 92%, while the Altman model records a
comparatively lower accuracy rate of 68%.
Key Words: Financial Distress, Altman, Springate, Grover