Can EWS, Altman, and Ohlson Models Comparatively Predict PT Garuda Indonesia’s Distress?

Abstract

This study aims to compare three bankruptcy prediction models—Early Warning System (EWS), Altman Z-Score, and Ohlson O-Score—in detecting early bankruptcy risk at PT Garuda Indonesia (Persero) Tbk during the 2020–2024 period. The research method employed is a quantitative descriptive comparative approach using secondary data obtained from the Indonesia Stock Exchange (IDX) in the form of annual financial reports. The analysis was conducted by calculating financial ratios and applying the three models to assess the predictive accuracy level of each. The results of the study show that the EWS model has the highest accuracy rate in detecting financial distress conditions at PT Garuda Indonesia, reaching 100%, followed by the Altman Z-Score model at 80% and the Ohlson O-Score model at 60%. These findings indicate that the EWS model is more sensitive to changes in financial ratios, particularly liquidity and solvency ratios, making it more relevant for the aviation sector, which is characterized by high-cost structures and a strong dependence on operational cash flow stability. The comparison among the three models also emphasizes that the choice of prediction model should align with industry characteristics to ensure more valid results. This research is expected to serve as a reference for management, investors, and regulators in monitoring corporate financial stability and strengthening bankruptcy risk mitigation policies in the future.