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Altman Z-Score

Altman Z-Score is a credit-risk concept used to measure default exposure, loss severity, or expected lending losses.

The Altman Z-Score is a financial metric used to predict the bankruptcy risk of publicly traded manufacturing companies. Developed by Edward I. Altman in 1968, this score combines various financial ratios to assess a company’s credit strength.

Formula of Altman Z-Score

The Altman Z-Score is calculated using the following formula:

$$ Z = 1.2X_1 + 1.4X_2 + 3.3X_3 + 0.6X_4 + 1.0X_5 $$

Where:

  • \( X_1 \) = Working Capital / Total Assets
  • \( X_2 \) = Retained Earnings / Total Assets
  • \( X_3 \) = Earnings Before Interest and Taxes (EBIT) / Total Assets
  • \( X_4 \) = Market Value of Equity / Total Liabilities
  • \( X_5 \) = Sales / Total Assets

Working Capital / Total Assets (\( X_1 \))

This ratio measures a company’s liquidity by comparing its working capital to its total assets.

Retained Earnings / Total Assets (\( X_2 \))

This ratio assesses how much profit a company reinvests in itself compared to its total assets.

EBIT / Total Assets (\( X_3 \))

This ratio evaluates the company’s operational efficiency in generating profits from its assets.

Market Value of Equity / Total Liabilities (\( X_4 \))

This measures the market perception of a company’s net worth relative to its debts.

Sales / Total Assets (\( X_5 \))

This ratio indicates the company’s asset turnover, showing how effectively it uses its assets to generate sales.

Ranges and Their Meanings

  • Z > 2.99: The company is in the “Safe” zone, indicating a low risk of bankruptcy.
  • 1.81 < Z < 2.99: The company is in the “Gray” zone, indicating a moderate risk of bankruptcy.
  • Z < 1.81: The company is in the “Distress” zone, indicating a high risk of bankruptcy.

Applicability

While the Altman Z-Score is primarily designed for publicly traded manufacturing companies, modified versions exist for private firms and non-manufacturers.

Considerations

  • Industry Variations: The formula’s accuracy can vary across different industries.
  • Economic Conditions: Macroeconomic factors can influence financial ratios, affecting the Z-Score’s accuracy.

Example 1

Company A has the following financial data:

  • Working Capital: $500,000
  • Total Assets: $2,000,000
  • Retained Earnings: $300,000
  • EBIT: $700,000
  • Market Value of Equity: $1,200,000
  • Total Liabilities: $800,000
  • Sales: $2,500,000

Using the Altman Z-Score formula:

$$ Z = 1.2 \left( \frac{500,000}{2,000,000} \right) + 1.4 \left( \frac{300,000}{2,000,000} \right) + 3.3 \left( \frac{700,000}{2,000,000} \right) + 0.6 \left( \frac{1,200,000}{800,000} \right) + 1.0 \left( \frac{2,500,000}{2,000,000} \right) = 2.75 $$

Company A falls into the “Gray” zone.

Financial Ratios

Quantitative measures derived from financial statement data used to assess a company’s performance and financial health.

Credit Risk

The possibility of a loss resulting from a borrower’s failure to repay a loan or meet contractual obligations.

Evidence Priority

Prioritize evidence that shows borrower capacity, collateral coverage, lien priority, covenant status, payment history, pricing, and recovery assumptions. Altman Z-Score should help answer whether repayment probability, expected loss, downside protection, or lender control has changed.

Finance Use Case

Use Altman Z-Score when a credit decision depends on repayment capacity, collateral value, lien priority, covenants, pricing, utilization, delinquency, or recovery. The practical issue for Altman Z-Score is whether it changes approval, monitoring, loss expectations, or workout leverage.

Reviewers should connect Altman Z-Score to borrower cash flow, legal or contractual rights, and the lender’s exposure after collateral, guarantees, or limits. If Altman Z-Score changes default probability, expected loss, availability, or payment priority, treat it as a credit-risk driver. If Altman Z-Score only changes wording in a document, Altman Z-Score still may matter when the wording controls notice, acceleration, remedies, fees, or reporting obligations.

Practical Test

The practical test for Altman Z-Score is whether it changes repayment capacity, collateral coverage, legal priority, covenant status, pricing, utilization, monitoring, or recovery. If Altman Z-Score changes the decision, tie the conclusion to borrower evidence and lender rights, not just the label.

What To Verify

Verify Altman Z-Score against the loan document, borrower financials, collateral support, covenant certificate, payment history, and monitoring file. The key check is whether lender exposure, borrower capacity, availability, pricing, or recovery has actually changed.

Analysis Boundary

The analysis boundary for Altman Z-Score is crossed when borrower capacity, collateral support, lender rights, covenant status, pricing, availability, and recovery do not change. Then Altman Z-Score belongs in documentation, not as a separate credit-risk driver.

Practical Signal

The practical signal for Altman Z-Score is a changed credit decision: approval, limit, pricing, covenant response, collateral treatment, reserve, collection strategy, or monitoring frequency. When that signal appears, tie Altman Z-Score to borrower evidence rather than a general credit label.

Use Boundary

The use boundary for Altman Z-Score is reached when repayment capacity, collateral support, contractual priority, covenant status, pricing, reserves, and collection strategy are unchanged. In that case, use Altman Z-Score for classification but avoid changing the credit view without stronger evidence.

Decision Marker

The decision marker for Altman Z-Score is the moment borrower risk changes: repayment capacity, collateral support, lien priority, covenant cushion, delinquency probability, recovery value, or pricing. If those inputs are unchanged, keep Altman Z-Score out of the credit decision.

Source Check

The source check for Altman Z-Score is the credit file: application data, borrower financials, covenant certificate, collateral record, payment history, credit memo, or collection note. Prefer file evidence over generic risk language when Altman Z-Score affects approval, pricing, or monitoring.

Decision Evidence

Decision evidence for Altman Z-Score should show borrower capacity, collateral support, contractual rights, covenant status, pricing impact, and monitoring owner. Altman Z-Score can change a credit decision only when those facts alter probability of repayment, loss severity, or collection strategy.

Review Evidence

Review evidence for Altman Z-Score should make the credit-and-lending evidence traceable, not just definitional. For Altman Z-Score, tie the evidence to the borrower file, facility agreement, repayment schedule, collateral record, and covenant package and explain why that evidence is reliable enough for the finance decision.

Before relying on Altman Z-Score, document the decision context: the draw date, maturity, amortization period, reporting date, and default measurement date. Keep the Altman Z-Score evidence trail visible: approval authority, covenant test, collateral perfection, servicing note, and exception log. In Credit and Lending work, Altman Z-Score matters when it changes credit availability, pricing, loss severity, borrower capacity, security ranking, or workout strategy.

  • Source: cite the record, filing, contract, model input, system log, or policy that supports Altman Z-Score.
  • Timing: record when Altman Z-Score is measured: date, period, jurisdiction, market condition, or processing window that could change the financial conclusion.
  • Boundary: distinguish Altman Z-Score from nearby concepts that require different evidence or support a different finance decision.
  • Decision use: identify the approval, valuation input, allocation step, control, disclosure, or risk decision affected if the evidence for Altman Z-Score were different.

The practical risk for Altman Z-Score is that credit terms become misleading when the borrower, facility, collateral, and covenant evidence are separated from the analysis. If those facts are unavailable, keep Altman Z-Score in the explanatory layer instead of treating it as decision-grade evidence.

Materiality Check

Altman Z-Score is material when it can change a finance conclusion, not just when Altman Z-Score appears in a document. For Altman Z-Score, test whether the evidence affects borrower capacity, facility pricing, collateral value, covenant pressure, repayment timing, recovery prospects, or loss severity. If those decision points are unchanged, keep Altman Z-Score explanatory and avoid overweighting it in the final decision.

A practical materiality check is to name the decision that would change if Altman Z-Score is wrong, stale, missing, or tied to the wrong period. Altman Z-Score warrants deeper review only when credit approval, monitoring intensity, workout strategy, or risk rating would change.

FAQs

What does a low Altman Z-Score signify?

A low Altman Z-Score indicates a high risk of bankruptcy, suggesting that the company may face financial distress.

Can the Altman Z-Score be used for non-manufacturing companies?

Yes, but the original formula is tailored for manufacturing companies. Modified versions exist for other types of companies.

How often should the Altman Z-Score be calculated?

It should be calculated regularly, such as quarterly or annually, to monitor a company’s financial health over time.
Revised on Sunday, June 21, 2026