Analysis of Financial Distress using the Altman Z-Score Model, Springate Model, Zmijewski Model, and Grover Model - Frido Sarita Simatupang; Ikaputra Waspada; Maya Sari; Tia Yuliawati (International Journal of Quantitative Research and Modeling, 2024)
The tight competition in the business world in the automotive industry that occurs in the current era of technology and development means that companies must have broad and clever thinking to keep the company from the brink of failure. During this research period there was a decline in automotive sales and company profits in the automotive and component sub-sectors listed on the IDX for the 2016-2020 period. This research aims to find out which prediction model is the most accurate and precise in predicting financial difficulties using model accuracy tests. The population in this study was 13 companies, then a purposive sampling technique was used to obtain 10 companies that were included in the research criteria. The results of this research show that the Altman Z-Score, Springate, Zmijewski and Grover models have different results, the Altman model predicts that there are 5 companies that are indicated to be healthy, 3 companies are in the Gray area, and 2 companies are indicated to have the potential to go bankrupt, the Springate model predicts that there are 5 companies healthy and 5 unhealthy companies, the Zmijewski model predicts that there are 9 healthy companies and 1 company that is indicated to have the potential to go bankrupt, the Grover model predicts that there are 7 healthy companies and 3 companies that are indicated to be unhealthy. With these results, the financial distress model with the highest accuracy is the Zmijewski model with an accuracy level of 92%, while the accuracy levels of the Altman Z-Score, Springate, and Grover models are 76%, 44%, and 76% respectively. With these results, the Zmijewski model is the most suitable model for use in automotive and component sub-sector companies in 2016-2020.