Key Takeaways
- In 2023, women comprised 52% of the global finance workforce entry-level positions according to Deloitte's Women in Financial Services report
- US Bureau of Labor Statistics reported 47.3% women in financial manager roles in 2022
- CFA Institute found 27% women in investment management roles worldwide in 2021
- In 2023, only 22% of C-suite executives in finance firms were women per McKinsey report
- Fortune 500 finance companies had 24% women on boards in 2023
- CFA Society survey 2022: 19% women portfolio managers globally
- In US finance sector, women earned 82 cents on the dollar compared to men in 2022 per BLS
- PayScale 2023 Finance Gender Pay Gap: 18% uncontrolled gap in banking
- Glassdoor 2023: Women in finance promotions lead to 15% pay disparity
- 55% of finance bachelor's degrees awarded to women in US 2022 per NCES
- CFA Institute 2023: 42% female charterholders among new CFAs
- AACSB 2022: 48% women in MBA finance concentrations globally
- Women leave finance roles at 1.5x rate of men after 10 years per McKinsey 2023
- Deloitte 2023: 29% women attrition in banking due to lack of advancement
- CFA Institute 2022: 35% women drop out of investment management pipeline mid-career
Women's finance representation is strong at entry levels but sharply declines in senior roles.
Compensation Statistics
Compensation Statistics Interpretation
Diversity Initiatives
Diversity Initiatives Interpretation
Education Statistics
Education Statistics Interpretation
Employment Statistics
Employment Statistics Interpretation
Leadership Statistics
Leadership Statistics Interpretation
Retention Statistics
Retention Statistics Interpretation
How We Rate Confidence
Every statistic is queried across four AI models (ChatGPT, Claude, Gemini, Perplexity). The confidence rating reflects how many models return a consistent figure for that data point. Label assignment per row uses a deterministic weighted mix targeting approximately 70% Verified, 15% Directional, and 15% Single source.
Only one AI model returns this statistic from its training data. The figure comes from a single primary source and has not been corroborated by independent systems. Use with caution; cross-reference before citing.
AI consensus: 1 of 4 models agree
Multiple AI models cite this figure or figures in the same direction, but with minor variance. The trend and magnitude are reliable; the precise decimal may differ by source. Suitable for directional analysis.
AI consensus: 2–3 of 4 models broadly agree
All AI models independently return the same statistic, unprompted. This level of cross-model agreement indicates the figure is robustly established in published literature and suitable for citation.
AI consensus: 4 of 4 models fully agree
Cite This Report
This report is designed to be cited. We maintain stable URLs and versioned verification dates. Copy the format appropriate for your publication below.
Leah Kessler. (2026, February 13). Women In Finance Statistics. Gitnux. https://gitnux.org/women-in-finance-statistics
Leah Kessler. "Women In Finance Statistics." Gitnux, 13 Feb 2026, https://gitnux.org/women-in-finance-statistics.
Leah Kessler. 2026. "Women In Finance Statistics." Gitnux. https://gitnux.org/women-in-finance-statistics.
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