Analysis of Insurance Company Bankruptcy Predictions Listed on the Indonesian Stock Exchange from 2020 To 2023

Abstract

This study examines the accuracy of bankruptcy prediction models applied to insurance companies listed on the Indonesia Stock Exchange during the 2020–2023 period. The research aims to compare the predictive performance of the Altman Z-Score, Springate, and Zmijewski models in identifying potential financial distress. A quantitative approach is employed using secondary data derived from annual financial statements of insurance firms. The sample consists of eight companies selected through purposive sampling. Data analysis involves normality testing and non-parametric statistical analysis using the Kruskal–Wallis test, supported by accuracy level evaluation through Type I error analysis. The findings indicate a statistically significant difference in bankruptcy prediction results among the three models. The Zmijewski model demonstrates the highest predictive accuracy, followed by the Altman Z-Score and the Springate model. These results suggest that the Zmijewski model is more reliable for predicting bankruptcy risk in insurance companies during periods of economic uncertainty. This study contributes to financial distress literature by providing empirical evidence on the comparative effectiveness of bankruptcy prediction models and offers practical implications for investors, managers, and regulators in assessing corporate financial health.