Credit Ratings and Bank Policy

By William C. Handorf, Ph.D., Professor of Finance, Banking and Real Estate, George Washington University’s School of Business

Banks are subject to evaluation by financial markets, regulators, accountants and customers, among others in the community. Management and the board of directors must craft strategic plans that maximize returns while maintaining acceptable levels of risk. Otherwise, problems occur, including failures that can trigger a bank run. Such problems are especially likely during a recession, a period of high unemployment or a time of elevated interest rates reflecting restrictive monetary policy. There are many signals of impending financial distress.

Stock prices fall and price-to-book ratios plummet when earnings are erratic or not commensurate with the risk-adjusted returns required by equity investors. Bond prices decline and yields on outstanding securities trading in the secondary market increase if investors perceive that a bank is taking excessive risks. Credit default spreads widen when counterparties perceive that expected losses may increase based on a higher probability of default and/or a larger loss given default (LGD). Regulators impose more restrictions on banks operating in an unsafe or unsound manner. Accountants modify audit opinions if they observe that an institution is no longer a “going concern”. Depositors withdraw funds and borrowers seek loans elsewhere if social media or the press indicate a bank is susceptible to failure.

Bankers must continually assess and respond to varied sources of information. We focus on credit ratings for large banks in the United States issued by one of the Nationally Recognized Statistical Rating Organizations (NRSROs). Why are some banks considered “high grade” (e.g., Aaa or Aa) versus “medium grade” (e.g., A or Baa) or even lower by Moody’s Investors Service? How stable and reliable are credit ratings? Does a rating make any difference to an institution?

Credit ratings

Although each NRSRO has its own framework for evaluating bank risk, they all consider both quantitative financial and economic data and qualitative governance information. Split ratings between and among the agencies are common. Invariably, the assessment considers the following concepts:

• Capital adequacy and solvency,
• Asset quality,
• Managerial expertise, board governance and product and geographic diversification,
• Earnings quality and stability,
• Liquidity and
• Governmental support.

Each area of analysis is supplemented by many financial and economic metrics. We evaluate illustrative ratios for a sample of 15 large US banks.

Each area of analysis is supplemented by many financial and economic metrics. We evaluate illustrative ratios for a sample of 15 large US banks. The sample represents about one-third of one percent of the country’s 4,400 institutions, as of December 31, 2025, but almost 60 percent of the industry’s $25 trillion in assets. As shown in Table 1, the average asset size of the bank sample is almost $900 billion. Bank size ranges from about $160 billion to $3.7 trillion. Asset size affects many financial metrics and the perception of credit-risk exposure.

Moody’s evaluates the short- and long-term debt of a bank and its holding company. The ratings typically range from Aaa to C. All ratings other than the best are adjusted by numerical notches to further differentiate risk. We focus on the unsecured, long-term debt ratings assigned to the largest US banks. The average rating of the sample is A2 (upper-medium grade), ranging from Aa2 (lower-high grade) to Baa1 (lower-medium grade). All sample banks are considered investment quality as of 2026.

We employ statistical correlation analysis to evaluate the associations between each institution’s financial metrics, its credit rating and its size. A letter credit rating is converted to a number whereby 1 is Aaa, 2 is Aa1, 3 is Aa2 and so forth. Correlation analysis provides a measure of the relative, not absolute, relationship between variables and does not suggest causality or economic consequence. Table 2 illustrates correlations that can range from +100 percent, a perfect positive correlation, to -100 percent, a perfect inverse correlation.

As shown in Table 2, the correlation between the credit ratings assigned by Moody’s and the average asset size of each bank within the sample is negative 78.5 percent. The correlation is significant at the one-percent level. Larger banks, on average, are rated more highly than smaller institutions. Despite efforts to remove “too big to fail” from the financial system, there remains an expectation that larger banks will receive congressional or regulatory intervention in the event of potential distress. There is a remote probability that the negative relationship between asset size and rating is random. Size affects the perception of loss.

Financial operations and condition

Capital and solvency: The average Leverage Ratio for the sample is 9.41 percent, with a range of 7.36 to 10.41 percent. The ratio measures the proportion of total assets funded by tangible equity. Stronger banks should have higher Leverage Ratios, leading to a negative correlation. However, the correlation between the Leverage Ratio and credit ratings is positive 74.3 percent, which is significant at the one-percent confidence level. The reason for the apparently anomalous result is bank size. The correlation between the Leverage Ratio and asset size is negative 84.8 percent, which is also significant at the one-percent level.

Investors expect to earn a return on equity commensurate with bank risk. Return on equity equals the return on assets generated by a bank times the equity multiplier.

To satisfy shareholders and earn a sufficient return on equity, banks need to increase profits and/or reduce the amount of funds provided by equity. Large banks leverage their balance sheets.

The average Total Capital Ratio (TCR) for the bank sample is 15.01 percent, with a range of 13.33 to 20.98 percent. The Total Capital Ratio equals the sum of Tier 1 capital (e.g., equity) and Tier 2 capital (e.g., subordinated debt) divided by risk-weighted assets (RWAs), based on the standardized Basel Accord introduced in 1988. The correlation between credit ratings and the Total Capital Ratio is negative 44.9 percent, which is significant at the 5-percent confidence level. Better capitalized institutions are rewarded with stronger credit ratings. The correlation between the Total Capital Ratio and asset size is positive 13.0 percent, which is not significant. Large banks rely on subordinated debt and other sources of Tier 2 capital to enhance solvency. Interest on debt is tax-deductible, and reliance on subordinated debentures does not dilute earnings or control, as with equity financing. Large banks also control the perceived riskiness of assets.

Asset quality: Banks typically fail due to unexpectedly large losses on loans or high-risk securities. There are many measures of asset quality within a bank. We focus on Non-current Loans and Other Real Estate Owned (OREO), divided by total loans and OREO. Non-current loans include loans more than 90 days past due, non-accrual and classified loans exhibiting losses. OREO represents foreclosed commercial and residential real estate on loans that have previously defaulted. The average amount of problematic loans and OREO is 1.03 percent, with a range of 0.63 to 1.75 percent. We expect a positive correlation between bank credit ratings and the Non-current Loan ratio. The correlation is positive 33.7 percent, which is significant at the 10-percent confidence level. In contrast, the correlation between problem loans and asset size is negative 19.1 percent, which is not significant. Large banks apply superior risk management, diversify losses across products and geographic regions and efficiently underwrite credit.

Earnings: The average return on assets (ROA) earned by banks over the past business cycle is 1.17 percent, ranging from 0.82 to 1.89 percent. The sample period included a recession accompanied by low interest rates, followed by high inflation associated with elevated interest rates. The correlation between the mean return on assets and the credit rating is negative 17.3 percent, which is not significant. A similar relationship exists between credit ratings and bank size. Although large money center banks earn a lower return on assets than regional banks, the mega institutions operate with proportionately less equity capital and generate the high returns on equity favored by the market.

Banks that take excessive risks or continually change business plans invariably generate erratic profits. Stable income and operating cash flow promote liquidity and solvency. We measure earnings risk by calculating the sample standard deviation (Sigma) of return on assets over a recent business cycle. The average sample ROA Sigma is 0.24 percent, ranging between 0.04 and 0.54 percent. The average large bank earned a 1.17-percent ROA, with a variability of 0.24 percent. Banks that originate high-risk loans or operate with greater interest rate or liquidity exposure generate a high ROA Sigma. The correlation between Sigma and credit ratings is positive 33.5 percent, which is significant at the 10-percent confidence level. Banks unable to post stable profits are penalized with lower credit ratings. The correlation between Sigma and size is negative but not significant. Large banks benefit from economies of scale and scope, as well as from diversification of products and geography.

Liquidity: The Net Non-Core Funding Ratio provides an illustrative measure of liquidity. Non-core funds include insured deposits exceeding $250,000, federal funds purchased, insured broker deposits and comparable sources. Non-core funds are especially sensitive to perceptions of bank distress. The Net Non-Core Funding Ratio equals non-core funds minus short-term investment securities that could be easily sold, all divided by long-term assets. What portion of long-term assets is financed by funds easily susceptible to withdrawal or non-renewal? The average Net Non-Core Funding Ratio for the bank sample is 7.63 percent and ranges from negative 6.54 to positive 31.12 percent. Banks operating with a positive ratio are taking on more liquidity risk. The correlation between the funding ratio and credit ratings is negative 63.3 percent, which is significant at the one-percent level. If the ratio measures liquidity risk, we would expect a positive correlation. The unforeseen result is easily explained. The largest banks rely more on non-core funds. Short-term funding through federal funds purchased or broker deposits allows large banks to avoid the incremental interest costs associated with long-term debt, including liquidity and credit-spread premiums that increase with maturity. More importantly, given the high credit ratings enjoyed by the largest US banks, their perceived strength allows them the ability to tap the market in a wide range of adverse scenarios.

Table 1: Credit Ratings and Financial Metrics of Large US Banks

Sources: Moody’s Investors Service and the “Uniform Bank Performance Report” (UBPR) compiled by the Federal Financial Institutions Examination Council (FFIEC).

Table 2: Correlation of Bank Operations and Condition

Significance: *** @ 1%, ** @ 5% and * @ 10%

Credit-rating transition

Credit ratings provide investors with an informed opinion of risk to complement traditional financial analysis and the pricing of credit default swaps, bonds and equities.

Credit ratings are not stable; they change over time. Ratings decline as the economy deteriorates and bank operations and conditions exhibit more issues. Based on the actual experience of bank ratings over recent one- and three-year periods of transition, Moody’s data show:

• Aa2-rated bank ratings did not decline over one year, but 11 percent fell over three years.
• A2-rated bank ratings declined 2 percent over a one-year horizon and 4 percent over three years.
• Baa2-rated bank ratings declined 7 percent over one year, climbing 9 percent over three years. Importantly, one percent of lower-medium-grade banks defaulted on their debt within one year.

To compensate for a higher probability of default, medium-grade debt yields more than high-grade bonds. The average spread between high- and medium-grade corporate bonds over the recent business cycle is 0.89 percent. The credit spread increases during periods of economic weakness.

The US banking system experienced several surprise credit-rating adjustments in 2023.

The bank’s closure triggered a renewed assessment of bank liquidity and interest-rate risk exposure.

Summary

Credit ratings provide investors with an informed opinion of risk to complement traditional financial analysis and the pricing of credit default swaps, bonds and equities. Generally, banks with higher levels of total capital to risk-weighted assets, fewer problem loans, more stable profits and better operating cash flow are regarded more highly. The largest banks can substitute Tier 2 capital for equity and take on more liquidity risk, given the perception that public policy will not allow them to default. Smaller institutions can and do fail and are especially prone to economic stress when rated with lower-medium grades. Bank-policy plans should consider crafting strategies to achieve an A or higher rating. It is important to remember that models, intuition and analysis are not infallible when assessing risk.

ABOUT THE AUTHOR

William C. Handorf, Ph.D., is a professor of finance, banking and real estate with the George Washington University’s School of Business. In addition to more than 50 years as an academic, he has 60 years of experience as a banker, regulator, accountant, consultant and corporate bank director.