Unlocking Credit Decisions: Six Financial Metrics That Matter

Using Ratio Analysis & Artificial Intelligence to Enhance Credit Risk Analysis

When reviewing a company’s financial statements to determine an appropriate credit limit, there are a multitude of things to consider. Trends related to revenue, profit, and equity, for example. Reviewing the relationship between key financial factors enables you to dig into the details and have a better perspective on how a company is performing. That is where ratio analysis comes in.

The answer to the following question provides valuable insight into ratios you may find useful when reviewing a company’s financials:

What ratios derived from a customer’s financial statements are the most revealing of creditworthiness?

The following six financial ratios can provide insights into a company’s creditworthiness by assessing its ability to meet its financial obligations. While different ratios can be relevant depending on the industry and specific circumstances, the following ratios are generally considered important indicators of creditworthiness:

1. Debt-to-Equity Ratio: This ratio compares a company’s total debt to its shareholders’ equity, indicating the proportion of debt financing relative to equity financing. A lower debt-to-equity ratio suggests a lower financial risk and greater creditworthiness.

2. Current Ratio: The current ratio measures a company's short-term liquidity by dividing its current assets (such as cash, receivables, and inventory) by its current liabilities (such as payables and short-term debt). A ratio above 1 indicates the company has sufficient current assets to cover its current liabilities, which is typically seen as a positive sign of creditworthiness.

3. Interest Coverage Ratio: The interest coverage ratio assesses a company’s ability to meet its interest payments on outstanding debt. It is calculated by dividing a company’s earnings before interest and taxes (EBIT) by its interest expense. A higher ratio indicates a greater capacity to cover interest obligations, which enhances creditworthiness.

4. Debt Service Coverage Ratio: This ratio evaluates a company’s ability to service its long-term debt by comparing its operating income or EBITDA (earnings before interest, taxes, depreciation, and amortization) to its debt service obligations (principal and interest payments).

5. Operating Cash Flow Ratio: This ratio measures the cash flow generated from operations relative to the company’s total debt obligations. It indicates whether the company’s operating cash flow is sufficient to cover its debt payments. A higher operating cash flow ratio suggests a stronger ability to generate cash for debt repayment.

6. Altman Z-Score: The Altman Z-Score is a formula that combines multiple financial ratios to assess the overall financial health and probability of bankruptcy of a company. It uses working capital, retained earnings, market value of equity, total assets, and total liabilities for its variables. A higher Z-score implies a lower risk of default and higher creditworthiness.

The original formula, designed for publicly traded manufacturing companies, is as follows:

Z=1.2X1+1.4X2+3.3X3+0.6X4+1.0X5Z=1.2X1+1.4X2+3.3X3+0.6X4+1.0X5

Where:

• X1= Working Capital / Total Assets

• X2= Retained Earnings / Total Assets

• X3= Earnings Before Interest and Taxes (EBIT) / Total Assets

• X4= Market Value of Equity / Total Liabilities

• X5= Sales / Total Assets

Each ratio represents a key aspect of a company’s financial health, such as liquidity, profitability, leverage, and operational efficiency

Interpretation

• Z > 2.99: Company is considered financially healthy and unlikely to face bankruptcy soon.

• 1.81 < Z < 2.99: "Gray zone"—some risk, but bankruptcy is not imminent.

• Z < 1.81: High risk of financial distress and potential bankruptcy

Note: The formula coefficients and variables may differ for private companies or non-manufacturing firms, so it is important to select the appropriate version of the Altman Z-Score for the specific company being analyzed

For more information about the Altman Z-Score, click on this link.

Determining an appropriate credit limit for a company requires a thorough analysis of its financial statements, with particular attention to these key indicators of financial health and stability. Each metric provides unique insights into a company’s ability to meet its financial obligations.

The Role of AI in Financial Statement Analysis

The integration of artificial intelligence (AI) into financial statement analysis is transforming this process. AI-powered tools can automatically extract, organize, and interpret vast amounts of a customer’s financial data from complex documents, thereby reducing manual effort and minimizing errors. These systems can analyze historical trends, detect anomalies, and forecast future performance, enabling analysts to make faster, more accurate, and data-driven credit decisions. AI can also process and summarize supplementary information, such as footnotes and regulatory filings, that may impact credit risk, providing a more comprehensive assessment.

By automating routine calculations and data preparation, AI frees credit analysts to focus on deeper interpretation and strategic judgment. As these technologies continue to advance, organizations that leverage AI for financial statement analysis will gain a significant advantage in efficiency, accuracy, and insight, ultimately leading to better-informed credit decisions and improved risk management.