An Assessment of Financial Health and Prediction of Financial Distress in Selected Steel Companies Listed on the National Stock Exchange of India Using Altman's Z-score and Springate's S- Score Models
This study evaluates the financial health and predicts potential distress of four major Indian steel companies (JSW, Tata Steel, SAIL, and JSPL) from 2021 to 2025 using Altman's Z-Score and Springate's S-Score models, revealing a predominantly challenging landscape marked by widespread operational and liquidity issues that necessitate strategic interventions for long-term stability.
Original paper licensed under CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/). This is an AI-generated explanation of the paper below. It is not written or endorsed by the authors. For technical accuracy, refer to the original paper. Read full disclaimer
Imagine the economy as a massive, bustling city where every company is a building. Some buildings are skyscrapers made of steel and glass, standing tall and proud, while others are older structures that might be cracking under pressure. In the world of finance, "financial health" is simply the ability of a building to pay its bills, keep the lights on, and not fall down. When a building starts to struggle, it enters a state called "financial distress," which is like a warning siren blaring that the roof might leak or the foundation might crumble. If things get bad enough, the building faces "bankruptcy," which is the financial equivalent of the structure collapsing entirely.
To figure out which buildings are safe and which are in trouble, experts use special tools called "prediction models." Think of these like high-tech health checkups for companies. Two of the most famous tools are the Altman Z-Score and the Springate S-Score. You can imagine the Z-Score as a doctor who checks your blood pressure, heart rate, and how much money you have in the bank to guess if you'll get sick. The S-Score is like a nutritionist who looks specifically at what you eat and how you move to see if you're strong enough to run a marathon. Both tools look at numbers from a company's report card—like how much profit they make, how much debt they owe, and how fast they sell their products—to give a score. A high score means "safe," a low score means "danger," and a score in the middle means "be careful."
The Steel City Checkup
In this study, a researcher named R. Sivakumar decided to play the role of a financial detective for the steel industry in India. Steel is a heavy, capital-intensive business, meaning it requires a lot of money to build factories and buy raw materials, kind of like trying to build a giant castle out of gold bricks. The researcher picked four famous steel companies listed on the National Stock Exchange of India: JSW Ltd., Tata Steel, SAIL Ltd., and Jindal Steel and Power Ltd. (JSPL). The goal was to see how these companies were doing between the years 2021 and 2025 by running them through both the Altman Z-Score and the Springate S-Score tests.
The Results: A Tale of Two Scores
When the researcher ran the numbers, the story wasn't the same for every company, and sometimes the two tests gave different answers, like two doctors disagreeing on a diagnosis.
SAIL Ltd.: This company was the clear "patient in critical condition." Both the Altman Z-Score and the Springate S-Score agreed that SAIL was in deep trouble for all five years. The scores were consistently low, ranging from 0.760 to 1.709 on the Z-Scale (where anything below 1.81 is a danger zone) and 0.486 to 0.740 on the S-Scale (where anything below 0.862 is a danger zone). It suggests that SAIL's problems are deep-rooted and not just a temporary bad day.
Tata Steel: This giant was also struggling. From 2021 to 2024, both models screamed "Distress." However, in 2025, the Altman Z-Score showed a slight improvement, moving the score to 1.877, which puts it in a "Grey Zone" (a middle ground between safe and dangerous). But the Springate S-Score stayed low at 0.626, still flagging distress. This suggests that while the market might be feeling a bit more optimistic about Tata Steel, the company's internal operations are still shaky.
JSW Ltd.: Here, the two models started to argue. The Altman Z-Score said JSW was in the "Grey Zone" (scores between 1.81 and 2.99), suggesting moderate risk. But the Springate S-Score was much stricter, keeping JSW in the "Distress" zone every single year with scores like 0.514 and 0.583. The researcher suggests this gap happens because the Altman test looks at the company's stock market value (what investors think it's worth), which seemed positive, while the Springate test looks strictly at the company's internal accounting, which showed real operational struggles.
Jindal Steel and Power Ltd. (JSPL): This company had the most dramatic plot twist. In 2021, the Springate S-Score said they were "Healthy" (0.868), but the Altman Z-Score said "Distress" (1.03). By 2025, the Altman Z-Score showed a strong recovery, jumping to 2.662 (getting close to the "Safe" zone), while the Springate S-Score dropped back into the "Distress" zone at 0.755. It seems JSPL has improved its reputation and market value, but it is still fighting internal battles with making enough profit from its daily operations.
The Common Thread: A Liquidity Leak
Despite the different scores, the researcher found a common problem across almost all these steel giants: a struggle with "Working Capital." You can think of working capital as the cash a company needs to keep the lights on and pay for daily supplies. The study found that the ratio of "Working Capital to Total Assets" was often negative or very low. This suggests that the entire steel sector is having a hard time managing its day-to-day cash flow, likely because the industry is so expensive to run and takes a long time to turn raw materials into sold products.
What This Means
The study concludes that the financial health of these Indian steel companies is a mixed bag, but generally challenging. While some companies like JSPL and JSW look better to the outside world (investors), their internal engines might still be sputtering. The researcher suggests that these models are great "early warning systems"—like a smoke detector that beeps before the fire spreads—but they aren't perfect. They can't see things like how good the management team is or if a new technology will save the day. So, while the numbers tell us who is in the "Distress" zone, fixing the problem will require more than just math; it will need smart strategies to fix those cash flow leaks and boost profitability.
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