Critical analysis of bankruptcy risk using Altman’s Z-score model of India Cement Ltd. (2020-2024)
Kartik S. Mhavarkar
What the paper says
Analyzing bankruptcies is a crucial aspect of studying finance. Determining the likelihood that a company won’t pay its bills is the primary objective. With the use of advanced statistical techniques, researchers can predict the financial distress of companies. Such statistical models can enhance prediction, improve accuracy, and increase the interpretability of results. It is essential for stakeholders, investors and lenders who thoroughly rely on such predictions for decision-making. Numerous studies have identified mathematical models that are used to interpret the bankruptcy conditions of companies. This research is primarily focused on a notable approach used in bankruptcy prediction. The creator of this approach gave it the name Altman Z-Score model. Given that India Cement Ltd. is one of the most well-known cement companies in the country, the researcher decided to focus their attention on the company for the study. The likelihood of India Cement Ltd.’s bankruptcy has been assessed by analyzing its financial records, particularly its five-year profit and loss statement and balance sheet. By applying the Altman Z score formula and analyzing several factors, the researcher determined that the company’s Altman Z score is 0.717. This is a clear indication that India Cement Ltd. is facing financial challenges. The main reason affecting the Z score of the company was the ratio between working capital and its total assets. It indicates the company’s poor management practices in handling working capital. Hence, the study concludes that India Cement Ltd. is in the “Distress Zone” and has a high likelihood of entering financial bankruptcy in the future due to its unstable Z score.
Evidence weight
Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40
| F · citation impact | 0.50 × 0.4 = 0.20 |
| M · momentum | 0.50 × 0.15 = 0.07 |
| V · venue signal | 0.50 × 0.05 = 0.03 |
| R · text relevance † | 0.50 × 0.4 = 0.20 |
† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.