The state of credit for American workers

Credit is not just a personal-finance topic—it is a labor-market and workforce issue. Wages, volatility, benefits, and how credentials translate into job quality shape whether workers can keep utilization low and payments on time, which mainstream scores weight heavily. For working Americans, credit also shapes whether a car is affordable enough to get to work, whether a short income gap turns into revolving debt, and whether the next step in training stays within reach.

What changed since 2018

The big-picture balance-sheet story is straightforward: total household debt rose from roughly $13.2 trillion in early 2018 to about $18.8 trillion by the end of 2025. Mortgage debt still dominates the total, but some of the fastest balance growth came in revolving debt and transportation debt, which are also the places where workers feel stress first.

That combination matters. Mortgage debt is large but comparatively low in serious delinquency. Credit cards and auto loans are much smaller as categories, yet they carry far more repayment stress and are more directly exposed to unstable wages, interest-rate pressure, and thin household buffers.

Where workers feel the pressure most

Credit card balances often rise when paychecks and expenses no longer line up. Auto loans are effectively job-retention credit in car-dependent labor markets. Student loans sit in a different category because policy changes can abruptly alter how delinquency and default appear on the file. What workers experience is not an abstract credit score. It is the cost of bridging instability.

The broad all-debt delinquency rate can look stable while worker-facing debt types become meaningfully more fragile.

Severe delinquency steepens sharply in lower score bands

Aggregate delinquency rates describe the whole file. FICO's account-management lens shows how differently existing accounts behave by score band: on bankcards, 90+ day delinquency within a year after scoring reaches roughly half of accounts in the lowest FICO Score 8 bands, versus a fraction of a percent for high scores. Auto finance shows the same pattern on the Auto Score scale. That gradient is why “sub-700” is not a cosmetic label—it tracks very different default risk across products.

Credit access is not distributed evenly

The Federal Reserve, Opportunity Insights, and industry score reporting all point in the same direction: credit access and credit costs differ sharply by race, household income, age, and geography. Some households are excluded from mainstream credit entirely, while many others are included only on terms that are far more expensive.

One especially useful distinction is between inclusion and affordability. A group can be fairly likely to have a credit card and still be carrying balances at a rate that implies sustained interest burden and lower resilience to shocks.

Average scores rose, but the underlying gaps remain large

FICO's published FICO Score 8 average climbed from the high 600s toward a peak near 718, then eased as household budgets tightened—while segmentation remained sharp. Published averages from Experian and others tell a related story but use different timing and populations. None of these series replace distributional facts: linked data still show large gaps by race, parental income, and place by early adulthood.

Why this matters for skills and employer practice

Skills and credentials do not appear directly inside a credit model, but they shape the variables that do matter: wages, employment stability, and the ability to make on-time payments without relying on high-cost revolving debt. Employer decisions matter too, especially where scheduling volatility, credit checks, or poor-quality tuition pathways create avoidable strain.

That is why this topic belongs in a workforce conversation. If credit acts like labor-market infrastructure, then job quality, credential quality, and employer policy all become part of the credit story rather than adjacent topics.

What organizations can do with this

The most useful response is not to treat workers as individually deficient. It is to improve the systems around them: job design, credential transparency, smoother repayment support, and fairer credit reporting rules for debts that say more about shocks than about willingness to repay.

Limits and source notes

The strongest public evidence is product-level and geography-level. Public sources are weaker when the question requires bureau microdata, occupation-specific credit outcomes, or exact national ROI estimates for employer programs. Student loan comparisons across 2020 to 2025 also need extra caution because the pause and restart changed what counted as delinquent.

• Credit bureau data is strong for debt and delinquency trends, but weak on race and income without linked datasets.
• Average-score series should always be labeled clearly because observation windows and covered populations differ across publishers.
• Student-loan trend lines are informative, but they are not perfectly comparable across the pause and restart period.

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