Financial Services

What's in this cluster

A career cluster is a navigational grouping, not a measured score. The counts below come from the framework's official crosswalk; employment and pay are aggregated from BLS OEWS (national, cross-industry, May 2024) across the occupations in the cluster.

Across occupations with wage data, the middle range (25th–75th percentile of occupation medians) runs $50,540 – $81,148. This describes the cluster, not any one job or person.

Sub-clusters

The framework splits each cluster into sub-clusters — tighter families of related work. The count is the number of occupations the crosswalk places in each.

Largest occupations in this cluster

Occupations in this cluster with the most workers nationally (BLS OEWS, May 2024), each linked to its full profile. Employment and pay describe the occupation, not an individual.

AI exposure across this cluster

Two published studies estimate how exposed each occupation is to today's AI. The OpenAI "GPTs are GPTs" study rates the share of an occupation's tasks a large language model (with tools) could speed up by half or more; averaged across this cluster it is 55% — 89th percentile of the 14 clusters. The independent Felten/Raj/Seamans AI Occupational Exposure index averages 1.25 here.

Computed across the 38 of 40 occupations in this cluster that carry a published exposure score.

Exposure measures where AI could assist tasks — it is not a prediction that these jobs will be automated. High exposure most often means augmentation (faster work), and many high-exposure occupations are also projected to grow.

Where the work sits

The framework anchors each cluster to one or more NAICS industry sectors — the parts of the economy where this work concentrates.

• Finance and Insurance · NAICS 52
• Real Estate and Rental and Leasing · NAICS 53

Education programs that lead here

A sample of the 66 CIP 2020 instructional programs the framework crosswalks to this cluster — the fields of study that prepare people for this work.

• Accounting
• Accounting Technology/Technician and Bookkeeping
• Accounting and Business/Management
• Accounting and Computer Science
• Accounting and Finance
• Actuarial Science
• Applied Mathematics, General
• Applied Mathematics, Other
• Applied Statistics, General
• Art History, Criticism and Conservation
• Auditing
• Autobody/Collision and Repair Technology/Technician
• Banking and Financial Support Services
• Business Administration and Management, General
• Business Statistics
• Business and Personal/Financial Services Marketing Operations
• Business/Commerce, General
• Business/Managerial Economics
• Communication Management and Strategic Communications
• Communication, General
• Computational Mathematics
• Computational Science
• Computational and Applied Mathematics
• Credit Management

Sources for this page

Every figure above traces to a named public dataset and the exact release below — not hand-written opinion. See the full methodology for what each measure does and does not mean.

• O*NET 30.3 U.S. Department of Labor / National Center for O*NET Development
• BLS Occupational Employment and Wage Statistics (OEWS) May 2024 U.S. Bureau of Labor Statistics
• Census NAICS 2022 U.S. Census Bureau
• CIP-2020 2020 U.S. National Center for Education Statistics
• “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130 OpenAI / academic
• AI Occupational Exposure (AIOE) Felten, Raj & Seamans academic

Data compiled June 3, 2026. Figures are estimates, not advice.

@misc{singulariki-financial-services,
  title  = {Financial Services},
  author = {{Singulariki}},
  year   = {2026},
  note   = {O*NET 30.3; BLS Occupational Employment and Wage Statistics (OEWS) May 2024; Census NAICS 2022; CIP-2020 2020; “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130; AI Occupational Exposure (AIOE) Felten, Raj & Seamans. Accessed June 7, 2026},
  url    = {https://singulariki.com/clusters/financial-services}
}