The credit score gender gap in America continues to narrow, but it hasn't disappeared. In 2026, men hold an average FICO score of 707 compared to 704 for women, a 3-point difference that has been cut in half since 2018, when the gap stood at 6 points.
While the headline scores are converging, structural differences in debt composition persist. Men carry significantly more total debt, averaging $101,934 versus $68,894 for women, driven primarily by larger mortgage balances. Women, however, bear a disproportionate share of student loan debt (18% of total debt vs. 8% for men), reflecting higher college enrollment rates.
Perhaps most striking: women under 35 actually have higher credit scores than their male peers. The gap reverses after age 35, when differences in mortgage debt, income trajectories, and credit account diversity begin to favor men. Despite similar scores, women face a 28% credit application denial rate compared to 22% for men.
This analysis draws on Federal Reserve consumer credit data, Experian's anonymized FICO score data, and Consumer Financial Protection Bureau (CFPB) public reports. All figures represent national averages for 2026.
Grouped comparison showing how the gap reverses for younger Americans.
Women under 35 actually have HIGHER credit scores than men in the same age group. The gap reverses after age 35, likely driven by differences in mortgage debt and income trajectories.
$101,934 total
$68,894 total
The biggest difference: women carry more than double the student loan share (18% vs 8%), reflecting higher college enrollment rates. Men carry significantly more mortgage debt, driven by higher median incomes and home purchase amounts.
8-year FICO score trend: the gender gap narrowed from 6 points (2018) to 3 points (2026).
COVID impact (2020): women's scores jumped as stimulus payments reduced delinquencies.
Автор
Александр Кацман
Основатель Credit Booster и Credit Booster AI
Александр Кацман более 15 лет работает в сфере кредитов и финансов, помогая тысячам людей и владельцев бизнеса оспаривать недостоверные записи, восстанавливать кредитную историю и получать финансирование, в котором им раньше отказывали. Его последний проект, Credit Booster AI, делает весь этот инструментарий доступным каждому, используя ИИ, чтобы исправление, построение и финансирование кредита стали доступны всем.
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