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Finance and Insurance

Sector · NAICS 52

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Finance and Insurance is a U.S. industry in the NAICS classification. The Bureau of Labor Statistics estimates about 6,226,620 workers across 273 detailed occupations in it. A typical worker earns around $84,015 a year (Singulariki estimate, see below).

The Sector as a Whole The Finance and Insurance sector comprises establishments primarily engaged in financial transactions (transactions involving the creation, liquidation, or change in ownership of financial assets) and/or in facilitating financial transactions. Three principal types of activities are identified: 1. Raising funds by taking deposits and/or issuing securities and, in the process, incurring liabilities. Establishments engaged in this activity use raised funds to acquire financial assets by making loans and/or purchasing securities. Putting themselves at risk, they channel funds from lenders to borrowers and transform or repackage the funds with respect to maturity, scale, and risk. This activity is known as financial intermediation. 2. Pooling of risk by underwriting insurance and annuities. Establishments engaged in this activity collect fees, insurance premiums, or annuity considerations; build up reserves; invest those reserves; and make contractual payments. Fees are based on the expected incidence of the insured risk and the expected return on investment. 3. Providing specialized services facilitating or supporting financial intermediation, insurance, and employee benefit programs. In addition, monetary authorities charged with monetary control are included in this sector. The subsectors, industry groups, and industries within the Finance and Insurance sector are defined on the basis of their unique production processes. As with all industries, the production processes are distinguished by their use of specialized human resources and specialized physical capital. In addition, the way in which these establishments acquire and allocate financial capital, their source of funds, and the use of those funds provides a third basis for distinguishing characteristics of the production process. For instance, the production process in raising funds through deposit-taking is different from the process of raising funds in bond or money markets. The process of making loans to individuals also requires different production processes than does the creation of investment pools or the underwriting of securities. Most of the Finance and Insurance subsectors contain one or more industry groups of (1) intermediaries with similar patterns of raising and using funds and (2) establishments engaged in activities that facilitate, or are otherwise related to, that type of financial or insurance intermediation. Industries within this sector are defined in terms of activities for which a production process can be specified, and many of these activities are not exclusive to a particular type of financial institution. To deal with the varied activities taking place within existing financial institutions, the approach is to split these institutions into components performing specialized services. This requires defining the units engaged in providing those services and developing procedures that allow for their delineation. These units are the equivalents for finance and insurance of the establishments defined for other industries. The output of many financial services, as well as the inputs and the processes by which they are combined, cannot be observed at a single location and can only be defined at a higher level of the organizational structure of the enterprise. Additionally, a number of independent activities that represent separate and distinct production processes may take place at a single location belonging to a multilocation financial firm. Activities are more likely to be homogeneous with respect to production characteristics than are locations, at least in financial services. The classification defines activities broadly enough that it can be used both by those classifying by location and by those employing a more top-down approach to the delineation of the establishment. Establishments engaged in activities that facilitate, or are otherwise related to, the various types of intermediation are included in multiple subsectors, rather than in a separate subsector dedicated to services alone, because these services are performed by intermediaries, as well as by specialist establishments, and the extent to which the activity of the intermediaries can be separately identified is not clear. Financial industries are extensive users of electronic means for facilitating the verification of financial balances, authorizing transactions, transferring funds to and from transactors' accounts, notifying banks (or credit card issuers) of the individual transactions, and providing daily summaries. Since these transaction processing activities are integral to the production of finance and insurance services, establishments that principally provide a financial transaction processing service are classified in this sector, rather than in the data processing industry in the Information sector. Legal entities that hold portfolios of assets on behalf of others are significant and data on them are required for a variety of purposes. Thus, for NAICS, these funds, trusts, and other financial vehicles are the fifth subsector of the Finance and Insurance sector. These entities earn interest, dividends, and other property income, but have little or no employment and no revenue from the sale of services. Separate establishments and employees devoted to the management of funds are classified in Industry Group 5239, Other Financial Investment Activities.

Employment is national May 2024 OEWS. "Typical pay" is Singulariki's own figure — the employment-weighted average of each occupation's national median wage — a rough center of the industry, not an official BLS number.

How exposed this industry is to AI

Weighting every occupation in this industry by its employment and its unified AI-exposure index (the OpenAI "GPTs are GPTs" human-rated task overlap folded with the Felten/Raj/Seamans AIOE index), this industry sits in the High band — 98th percentile across all industries.

Exposure measures how much of the work overlaps with what today's AI can do, not a prediction of automation; high-exposure industries are where AI is most likely to reshape tasks. Employment-weighted across 233 occupations that carry an exposure score. Compare every industry on the AI exposure hub.

How AI is actually used in this industry

Among measured Claude.ai (Free and Pro) conversations mapped to O*NET task statements (Anthropic Economic Index, 2026-01-15), these patterns are most associated with the occupations in this industry, weighted by its employment mix. They are shares of observed AI conversations — not of worker time, revenue, or what could be automated — and reflect one AI assistant's consumer sample, not all AI.

Signal coverage 88.6% of employment · 174/251 occupations have AEI task data
Augmentation vs. automation 45.1% working with AI · 35.3% handed to AI
Most common pattern Directive · AI does it; you give the instruction
Typical AI autonomy 3.3 / 5 · higher = AI acts more independently

Tasks driving the signal

The task families that account for the most AI activity across this industry's occupations (employment × observed usage), each attributed to the occupation it comes from.

Task Occupation How Share of signal
Troubleshoot problems involving office equipment, such as computer hardware and software. Office Clerks, General Feedback loop 13.8%
Participate in the work of subordinates to facilitate productivity or to overcome difficult aspects of work. First-Line Supervisors of Office and Administrative Support Workers Iteration 3.6%
Explain stock market terms or trading practices to clients. Securities, Commodities, and Financial Services Sales Agents Learning 3.0%
Recommend financial products, such as stocks, bonds, mutual funds, or insurance. Personal Financial Advisors Directive 2.9%
Offer advice on the purchase or sale of particular securities. Securities, Commodities, and Financial Services Sales Agents Learning 2.8%
Analyze target companies or investment opportunities to inform investment decisions. Securities, Commodities, and Financial Services Sales Agents Directive 2.5%
Analyze financial information obtained from clients to determine strategies for meeting clients' financial objectives. Personal Financial Advisors Iteration 2.3%
Use computers for various applications, such as database management or word processing. Secretaries and Administrative Assistants, Except Legal, Medical, and Executive Directive 2.3%
Develop or analyze information to assess the current or future financial status of firms. Financial Managers Directive 2.3%
Conduct searches to find needed information, using such sources as the Internet. Secretaries and Administrative Assistants, Except Legal, Medical, and Executive Directive 2.1%
Develop or maintain internal or external company Web sites. Secretaries and Administrative Assistants, Except Legal, Medical, and Executive Directive 1.6%
Explain to customers the different types of loans and credit options that are available, as well as the terms of those services. Loan Officers Learning 1.6%

Occupations behind the signal

The occupations whose AI-touched tasks contribute most to this industry's signal, by employment here.

Occupation Workers Share How they use AI
Customer Service Representatives 487,850 7.8% Directive
Insurance Sales Agents 451,930 7.3% Learning
Securities, Commodities, and Financial Services Sales Agents 447,410 7.2% Directive
Tellers 330,260 5.3% Directive
Financial Managers 255,610 4.1% Directive
Personal Financial Advisors 252,560 4.1% Directive
Loan Officers 244,580 3.9% Learning
Claims Adjusters, Examiners, and Investigators 224,390 3.6% Learning
General and Operations Managers 218,140 3.5% Iteration
First-Line Supervisors of Office and Administrative Support Workers 184,520 3.0% Iteration
Insurance Claims and Policy Processing Clerks 179,320 2.9% Iteration
Financial and Investment Analysts 150,630 2.4% Directive

This rollup is only as complete as the occupation-task matches available for the industry; the coverage figure above is shown so sparse industries do not look falsely precise. AI exposure is not the same as replacement.

Skill & tool metabolism

What this industry's work actually runs on. Each figure is the share of the industry's workers in occupations that significantly rely on a skill, knowledge area, or ability (O*NET importance ≥ 3 of 5), or that use a tool category — its employment reach. This is a measure of how widespread a requirement is across the workforce, not how intensively any one worker uses it. Shares are independent and need not add to 100%.

Based on 94.6% of this industry's employment that maps to a detailed occupation with an O*NET skill profile.

Skills

Skill Employment reach Workers
Active Listening 94.5% 5,884,270
Reading Comprehension 94.4% 5,877,390
Speaking 94.4% 5,879,800
Critical Thinking 94.2% 5,867,720
Writing 93.9% 5,844,200
Time Management 91.2% 5,681,120
Social Perceptiveness 87.6% 5,454,860
Service Orientation 82.8% 5,158,450
Monitoring 80.3% 5,002,840
Judgment and Decision Making 75.5% 4,699,880
Complex Problem Solving 72.8% 4,534,440
Active Learning 70.9% 4,412,040

Knowledge areas

Knowledge area Employment reach Workers
English Language 94.5% 5,883,320
Customer and Personal Service 90.7% 5,648,050
Mathematics 75.9% 4,723,350
Administration and Management 67.4% 4,194,460
Computers and Electronics 61.5% 3,829,340
Administrative 50.5% 3,141,840
Economics and Accounting 48.2% 3,002,650
Law and Government 40.0% 2,493,370
Sales and Marketing 35.3% 2,197,730
Education and Training 22.2% 1,382,110
Personnel and Human Resources 19.1% 1,187,600
Communications and Media 16.5% 1,024,680

Abilities

Abilitie Employment reach Workers
Oral Comprehension 94.6% 5,890,820
Oral Expression 94.6% 5,890,560
Near Vision 94.5% 5,887,060
Written Comprehension 94.5% 5,882,370
Speech Recognition 94.4% 5,880,230
Speech Clarity 94.3% 5,873,810
Written Expression 94.1% 5,857,470
Problem Sensitivity 94.0% 5,850,920
Information Ordering 93.5% 5,820,900
Deductive Reasoning 93.0% 5,788,340
Inductive Reasoning 92.9% 5,786,440
Category Flexibility 84.0% 5,229,100

Tool categories

Tool category Employment reach Workers
Office suite software 98.8% 6,152,510
Spreadsheet software 98.8% 6,152,970
Electronic mail software 98.7% 6,145,800
Presentation software 98.4% 6,127,770
Word processing software 98.3% 6,121,300
Data base user interface and query software 98.1% 6,107,750
Document management software 93.5% 5,819,180
Enterprise resource planning ERP software 90.8% 5,651,870
Internet browser software 82.8% 5,153,010
Financial analysis software 80.8% 5,031,320
Customer relationship management CRM software 77.9% 4,848,840
Operating system software 77.6% 4,834,740
Accounting software 74.1% 4,610,880
Project management software 58.8% 3,663,940
Information retrieval or search software 58.3% 3,629,170

Reach = share of industry employment in occupations where the requirement is significant; it is not a per-worker usage or proficiency measure. Skill, knowledge, and ability importance is from O*NET; tool use is reported presence of a technology category.

Largest occupations

Exposure quadrant: AI task-overlap percentile vs Median pay AI task-overlap (horizontal) versus median pay (vertical), each as a percentile across all scored occupations, for 40 occupations in Finance and Insurance. Overlap measures shared tasks with AI, not automation. Lower overlap · higher pay Higher overlap · higher pay Higher overlap · lower pay Lower overlap · lower pay Registered Nurses General and Operations Managers Managers, All Other Tellers Compliance Officers Office Clerks, General Business Operations Specialists, All Other Computer User Support Specialists First-Line Supervisors of Office and Administrative Support Workers New Accounts Clerks Executive Secretaries and Executive Administrative Assistants Bookkeeping, Accounting, and Auditing Clerks Data Scientists AI task-overlap percentile → ↑ Median pay
The largest occupations in this industry with both an AI task-overlap score and a wage, plotted by task-overlap percentile (horizontal) and median-pay percentile (vertical). Overlap measures shared tasks with AI, not automation.

The occupations that employ the most people in this industry, with their share of the industry's workforce and national median pay for the occupation (not industry-specific pay).

Occupation Workers Share National median pay
Customer Service Representatives 487,850 7.8% $46,660
Insurance Sales Agents 451,930 7.3% $60,400
Securities, Commodities, and Financial Services Sales Agents 447,410 7.2% $77,550
Tellers 330,260 5.3% $39,280
Financial Managers 255,610 4.1% $164,940
Personal Financial Advisors 252,560 4.1% $103,200
Loan Officers 244,580 3.9% $73,640
Claims Adjusters, Examiners, and Investigators 224,390 3.6% $75,830
General and Operations Managers 218,140 3.5% $135,860
First-Line Supervisors of Office and Administrative Support Workers 184,520 3.0% $72,590
Insurance Claims and Policy Processing Clerks 179,320 2.9% $48,980
Software Developers 160,000 2.6% $132,880
Financial and Investment Analysts 150,630 2.4% $106,740
Loan Interviewers and Clerks 146,110 2.3% $48,760
Management Analysts 120,400 1.9% $98,710
Accountants and Auditors 118,140 1.9% $87,980
Office Clerks, General 112,260 1.8% $45,560
Insurance Underwriters 101,320 1.6% $79,960
Bookkeeping, Accounting, and Auditing Clerks 85,770 1.4% $49,570
Secretaries and Administrative Assistants, Except Legal, Medical, and Executive 82,100 1.3% $48,380
Market Research Analysts and Marketing Specialists 82,040 1.3% $84,990
Computer and Information Systems Managers 78,960 1.3% $176,570
Business Operations Specialists, All Other 76,760 1.2% $83,480
Computer Systems Analysts 63,990 1.0% $104,910
Sales Managers 61,040 1.0% $173,230
Executive Secretaries and Executive Administrative Assistants 58,370 0.9% $80,050
Credit Analysts 48,610 0.8% $82,170
Human Resources Specialists 48,250 0.8% $83,060
Registered Nurses 48,100 0.8% $89,650
Compliance Officers 46,410 0.7% $79,920
First-Line Supervisors of Non-Retail Sales Workers 45,030 0.7% $91,970
Managers, All Other 44,890 0.7% $162,780
Project Management Specialists 41,690 0.7% $111,350
Data Scientists 41,020 0.7% $123,570
Financial Specialists, All Other 40,340 0.6% $78,030
Financial Examiners 40,260 0.6% $86,490
Computer User Support Specialists 37,300 0.6% $62,420
New Accounts Clerks 36,790 0.6% $46,600
Marketing Managers 36,620 0.6% $167,610
Bill and Account Collectors 36,050 0.6% $47,600

Showing the top 40 of 273 occupations by employment.

Most distinctive occupations

The occupations most unusually concentrated in this industry compared with the economy as a whole. The location quotient is how many times more common an occupation is here versus its economy-wide share (a value of 5 means five times as concentrated).

For a sector this broad, the location quotient has a ceiling set by the sector's own share of national employment, so the top values tend to cluster near that limit.

Occupation Concentration Workers
Tellers 24.1× 330,260
New Accounts Clerks 23.96× 36,790
Insurance Sales Agents 23.84× 451,930
Securities, Commodities, and Financial Services Sales Agents 23.46× 447,410
Insurance Underwriters 23.27× 101,320
Insurance Appraisers, Auto Damage 23.17× 7,290
Personal Financial Advisors 23.12× 252,560
Brokerage Clerks 21.8× 35,300
Loan Interviewers and Clerks 20.9× 146,110
Loan Officers 20.85× 244,580
Insurance Claims and Policy Processing Clerks 19.38× 179,320
Actuaries 18.26× 20,900
Claims Adjusters, Examiners, and Investigators 18.22× 224,390
Credit Analysts 17.87× 48,610
Financial Examiners 15.87× 40,260
Financial Risk Specialists 15.34× 34,880
Financial Clerks, All Other 15.19× 22,720
Financial and Investment Analysts 10.95× 150,630
Title Examiners, Abstractors, and Searchers 8.74× 17,000
Credit Authorizers, Checkers, and Clerks 8.12× 3,920

Sub-industries

More detailed industries within Finance and Insurance.

Write a report on thisheadline · factoids · citation

The Finance and Insurance workforce sits at the 98th percentile of AI task overlap — 6,226,620 U.S. workers

  • Weighting every occupation by its real share of Finance and Insurance employment, the industry's workforce ranks in the 98th percentile (High band) for AI task overlap — overlap with what AI can attempt, not a measure of jobs at risk.Eloundou et al. + Felten AIOE, weighted by BLS OEWS
  • The industry employs about 6,226,620 U.S. workers across 273 occupations.BLS OEWS (May 2024)
  • Employment-weighted typical annual pay is about $84,015.BLS OEWS (May 2024)
  • Of AI use observed across this industry's occupations, 45% looks like augmentation rather than automation — from a Claude.ai sample, not a census.Anthropic Economic Index
Copy the whole kit
The Finance and Insurance workforce sits at the 98th percentile of AI task overlap — 6,226,620 U.S. workers

• Weighting every occupation by its real share of Finance and Insurance employment, the industry's workforce ranks in the 98th percentile (High band) for AI task overlap — overlap with what AI can attempt, not a measure of jobs at risk. (Eloundou et al. + Felten AIOE, weighted by BLS OEWS)
• The industry employs about 6,226,620 U.S. workers across 273 occupations. (BLS OEWS (May 2024))
• Employment-weighted typical annual pay is about $84,015. (BLS OEWS (May 2024))
• Of AI use observed across this industry's occupations, 45% looks like augmentation rather than automation — from a Claude.ai sample, not a census. (Anthropic Economic Index)

Source: Singulariki — "Finance and Insurance". https://singulariki.com/industries/52
Note: AI task overlap measures what today's AI can attempt, not automation, job loss, or a forecast.

AssetsShare imageMethodology & sourcesPress & newsroomThe newsroom

Every line is built only from figures this page already shows and cites. AI task overlap means what today's AI can attempt — not automation, job loss, or a forecast.

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.

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

Cite this page
Plain

Singulariki. "Finance and Insurance." Singulariki: a source-backed encyclopedia of work. Built from O*NET 30.3; BLS Occupational Employment and Wage Statistics (OEWS) May 2024; Census NAICS 2022; Anthropic Economic Index v4 (2026-01-15) + v2 (2025-03-27); “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130; AI Occupational Exposure (AIOE) Felten, Raj & Seamans. Accessed June 7, 2026. https://singulariki.com/industries/52

APA

Singulariki. (2026). Finance and Insurance. Singulariki: a source-backed encyclopedia of work. Retrieved June 7, 2026, from https://singulariki.com/industries/52

BibTeX
@misc{singulariki-52,
  title  = {Finance and Insurance},
  author = {{Singulariki}},
  year   = {2026},
  note   = {O*NET 30.3; BLS Occupational Employment and Wage Statistics (OEWS) May 2024; Census NAICS 2022; Anthropic Economic Index v4 (2026-01-15) + v2 (2025-03-27); “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130; AI Occupational Exposure (AIOE) Felten, Raj & Seamans. Accessed June 7, 2026},
  url    = {https://singulariki.com/industries/52}
}

Citations name the underlying public dataset releases — they reflect what this page is built from, not just the URL.