Default risk prediction using Merton's model and Altman's Z-score

This research focuses on predicting the default risk of a financially distressed firm with KMVMerton's model and Altman's Z-Score model. Part of the objectives of this research were to estimate the probability of default with Merton's model and to compare and validate this probability with Altman's Z-Score. Merton's model, which is a structural model, was used to estimate default probability, while Altman's Z-Score model, a reduced-form model, was used as a verification tool. The research involved collecting past financial data from the company's financial statements. The result indicated an extremely high degree of correspondence among the models. Merton's model estimated a default probability of 100%, while Altman's Z-Score model gave a default risk forecast of -4.018, which is an exceptionally high bankruptcy likelihood. These were expected results within the known standards of both models. Challenges in research were encountered primarily in obtaining effective data and achieving a final comparability tool for model accuracy. Future research can explore variations of model comparison to further evaluate the predictive ability of Merton's model to predict default risk and review enhancements to Altman's Z-Score model to enhance prediction accuracy. The practical significance of this study lies in providing a comparative study on two of the most used default risk models and highlighting the importance of solid financial distress assessment for companies with a history of financial distress.