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Financial services sales agents

Official title Securities, Commodities, and Financial Services Sales Agents (SOC 41-3031)

Also called Stockbroker, Registered representative, Investment banker, Securities sales agent, Equity sales

In brief

In May 2025, BLS counted 489,570 US financial services sales agents, with median pay of $78,660 a year. Of the BLS counts since 2003, the May 2025 count is the highest. The earliest figure here is an estimate of 5,000 from 1900, not measured the same way as today's count. The last full technology era for financial services sales agents: Zero-commission trading, 2013 to 2023. The zero-commission wave eliminated the last economic rationale for paying a broker to execute a simple trade.

What the sources say

Official outlook

BLS projects employment to grow 1.4% from 2025 to 2035.

BLS Employment Projections 2025-35

AI exposure studies

  • 51.9% of this job's tasks are exposed to large language models. Not a forecast of job losses. Eloundou and others, 2023
  • 0.016 estimated probability that the whole occupation could be computerised, over an unspecified number of years. Not a forecast of job losses. Frey and Osborne, 2013

Since the 2013 prediction

In 2013, Frey and Osborne put this job's probability of computerisation at 0.016. BLS counted 325,140 of these jobs in May 2013 and 489,570 in May 2025 (+51%, a change derived by Future History).

Data as of BLS OEWS May 2025; BLS Employment Projections 2025-35. BLS publishes these counts as yearly survey snapshots and cautions against reading them as a precise trend. In May 2021 BLS changed how it estimates these counts (a model-based method using three years of survey data) and moved fully to the 2018 occupation codes, so part of a change across 2021 can come from the method rather than the work.

Last updated .

Cite this page
APA

Future History. (2026, October 11). Financial services sales agents: jobs and pay since 1900 [Data set; data as of BLS OEWS May 2025; BLS Employment Projections 2025-35]. https://futurehistory.earth/timeline/41-3031

Chicago

Future History. "Financial services sales agents: jobs and pay since 1900." Data as of BLS OEWS May 2025; BLS Employment Projections 2025-35. Last modified October 11, 2026. https://futurehistory.earth/timeline/41-3031.

BibTeX

@misc{futurehistory_41_3031, author = {{Future History}}, title = {Financial services sales agents: jobs and pay since 1900}, year = {2026}, month = oct, howpublished = {\url{https://futurehistory.earth/timeline/41-3031}}, note = {Last updated 2026-10-11. Data as of BLS OEWS May 2025; BLS Employment Projections 2025-35}, }

The access date is today's date on your device.

drag to travel through time
180018251850187519001925195019752000now
Country
2026
Known then as Stockbroker / Stock Jobber (NYSE member, informal category)
Known then as Stockbroker / Securities Dealer / Customer's Man
Known then as Registered Representative (post-Securities Exchange Act, fixed commission era)
Known then as Registered Representative / Account Executive (post-May Day negotiated commissions)
Known then as Financial Consultant / Account Executive / Investment Representative (wirehouse rebranding era)
Known then as Securities, Commodities, and Financial Services Sales Agent (BLS SOC 41-3031)
Known today as Securities, Commodities, and Financial Services Sales Agent (BLS SOC 41-3031)
Projected to still be called Securities, Commodities, and Financial Services Sales Agent (BLS SOC 41-3031)
Data from the May 2025 survey
US Employment
490K
Est.

Stated in source: BLS OEWS

Official statistic
Report an error
Median Annual Wage
$78,660

≈ $76,643 in 2024 prices (derived by us, CPI-adjusted)

Official statistic
Report an error
Beat · 1792

May 17, 1792: Twenty-four brokers gather beneath a buttonwood tree at 68 Wall Street in New York and sign the Buttonwood Agreement, two provisions: trade only with each other, and charge no less than 0.25% commission. These are the founding rules of what will become the NYSE. The signatories are mostly commodity and government-bond dealers responding to the panic of 1792, the young country's first financial crisis.

Beat · 1929

October 24-29, 1929 ("Black Thursday" through "Black Tuesday"): NYSE volume reaches 16.4 million shares on Black Tuesday, October 29, as the market collapses. Thousands of brokers and dealers, who had built their businesses on the 1920s retail investor boom, are wiped out alongside their clients. The crash destroys an estimated $30 billion in market value and triggers the Great Depression. The aftermath will produce the most comprehensive securities regulation in US history.

Beat · 1934

June 6, 1934: President Franklin Roosevelt signs the Securities Exchange Act of 1934, establishing the SEC and requiring all broker-dealers to register with it. Section 15 of the Act creates the framework for licensing securities salespeople: the foundation of what will become the Series 7 examination administered by FINRA. For the first time, being a securities sales agent is a licensed profession, not simply a business activity.

Beat · 1975

May 1, 1975: "May Day": The SEC mandates negotiated commission rates for all securities transactions, ending 183 years of the NYSE's fixed-commission system that dated to the 1792 Buttonwood Agreement. The same day, Charles Schwab & Co. begins aggressively discounting commissions. In September 1975, Schwab opens its first Sacramento branch with commissions cut in half: the first discount brokerage. The commission economics that had sustained the full-service wirehouse model will never recover.

Beat · 1999

November 12, 1999: The Gramm-Leach-Bliley Act repeals the Glass-Steagall separation between commercial banking, investment banking, and insurance. Banks can now underwrite securities; investment banks can accept deposits. The result is a wave of consolidation that creates the modern wirehouse model (Citigroup, BankAmerica-Merrill Lynch) where securities sales agents work within vast financial supermarkets offering products across every category simultaneously.

Beat · 2008

September 15, 2008: Lehman Brothers files for the largest bankruptcy in US history ($639 billion in assets). Bear Stearns, Merrill Lynch, and multiple smaller broker-dealers collapse or are acquired in distress. FINRA records the largest single-year loss of registered representatives in its history: 72,564 people leave the industry in 2009. The financial crisis accelerates the migration of assets and advisors from commission-based broker-dealer models to fee-based RIA structures.

Beat · 2019

October 2019: Within days of each other, Schwab (October 1), TD Ameritrade, and E*TRADE all announce the elimination of online trading commissions, matching Robinhood's zero-commission model that had been in place since 2013. The commission-based retail broker (the defining figure of 20th-century personal finance, the person who once charged $49 to place a trade) becomes economically obsolete as a pure execution agent. The survivor occupation is the advisor, the relationship manager, the institutional specialist: people whose value cannot be replaced by a mobile app.

Beat · 2023

September 2023: Morgan Stanley fully deploys AI @ Morgan Stanley Assistant, a GPT-4-powered chatbot giving 16,000 financial advisors instant search across 100,000 research documents. Within months, 98% of FA teams actively use it. The tool is followed by AI @ Morgan Stanley Debrief, a meeting-summarization system saving ~30 minutes per client interaction. The first large-scale documented AI deployment in securities sales represents the next inflection: the research and documentation layer, previously the broker's core intellectual property, begins to be automated.

How to read this number

OEWS is a point-in-time survey snapshot, not a continuous time series; BLS advises against using it for year-over-year trend comparison.

Each dot is a cited figure over time; the dotted line only links them (values between aren't measured). Hollow dots are estimates.

Official statistic: Copied by a script from a statistics agency table or a published study's table, not retyped by hand. BLS figures and the forecast and exposure tables are also re-checked against that table on every data run. Researched context: Researched from the cited source rather than copied from it by a script, so it is not machine-checked yet. Spot a mistake? Each figure has a “Report an error” link.

Cited forecasts · present → 2035

Will AI replace financial services sales agents? What the research says

Each figure is stated by the named source; we publish no forecasts of our own. Where sources disagree, we show the disagreement rather than an average.

Each figure is stated by the named source; we publish no forecasts of our own. Where sources disagree, the spread is the honest signal.

What published forecasts say
Forecast change in the number of people doing this work, as published by each named source. Bars share one scale on every role, centred on zero and reaching the end at ±30%. Grey marks a small change, 3% or less either way.
BLS Employment Projections 2025-35
→ 2035
+1.4%
BLS National Employment Matrix, 2025-35 cycle, line for SOC 41-3031 (Securities, commodities, and financial services sales agents): 531.0 thousand jobs in 2025, projected 538.5 thousand in 2035, a change of +7.5 thousand (+1.4%). Matrix employment counts all jobs in the occupation, including self-employed workers (6% of this occupation in 2025). The average for all occupations in this cycle is +3.5%.
Official statisticReport an error
How exposed is this work to AI (research measures)
Scores as published by each study. Each row says what it measures. These measure what AI could technically do, not forecasts of jobs lost.
Eloundou et al. (2023), "GPTs are GPTs"
2023 study · Share of tasks exposed to LLMs (β, human-rated)
51.9%
of tasks
What this measures

Published occupation-level exposure from the paper's occ_level.csv for O*NET-SOC 41-3031.00 Securities, Commodities, and Financial Services Sales Agents. Shown: human-rated β = 0.519, the share of the occupation's tasks an LLM could do in at least half the time at equal quality, counting tasks that need LLM-powered software at half weight (β = E1 + 0.5 × E2). Other published measures for this occupation: human-rated α (LLM alone) 0.269 and γ (all LLM-assisted) 0.769; GPT-4-rated β 0.606. This measures how much of the work an LLM could touch, not how many jobs disappear.

Official statisticReport an error
Frey & Osborne (2013), "The Future of Employment"
2013 study · Probability of computerisation (2013 model)
1.6%
probability
What this measures

Published appendix value for SOC 2010 41-3031 Securities, Commodities, and Financial Services Sales Agents: probability of computerisation 0.016, rank 74 of 702 (rank 1 is least computerisable). Frey and Osborne estimated in 2013, with a Gaussian-process classifier on O*NET variables, how likely the whole occupation is to be technically automatable over "some unspecified number of years, perhaps a decade or two". It is a probability for the occupation, not a share of tasks and not a forecast of jobs lost.

Official statisticReport an error
Today, in this role

What's changing day to day for financial services sales agents

Three parts of your work where AI is already doing real lifting, and what stays yours.

AI is taking this onExecute and confirm client trades, process transaction documentation, and maintain accurate records of client portfolios: rely on straight-through processing and AI-assisted trade-confirmation workflows that verify trade details, flag reconciliation exceptions, and auto-generate trade confirmations and contract notes with minimal manual intervention, tasks that once occupied a substantial share of a registered representative's day.

Execute and confirm client trades, process transaction documentation, and maintain accurate records of client portfolios: rely on straight-through processing and AI-assisted trade-confirmation workflows that verify trade details, flag reconciliation exceptions, and auto-generate trade confirmations and contract notes with minimal manual intervention, tasks that once occupied a substantial share of a registered representative's day.[2],[7]

Where your edge is

Trade execution, confirmation, and reconciliation are being absorbed into straight-through processing systems at virtually all major broker-dealers. The manual touchpoints shrink to exception-handling: trade breaks, client dispute resolution, complex multi-leg execution in illiquid instruments. Redirect the time freed by automation to client-facing activities: proactive outreach, investment reviews, and relationship deepening that generate new business rather than administrative maintenance.

AI is sitting alongside you hereProspect and qualify new institutional or retail clients using AI-enriched prospecting platforms: use Salesforce Financial Services Cloud Einstein or Outreach signal-based sequencing to prioritize outreach based on life-event triggers (inheritance, liquidity events, executive stock-vesting dates, business sale), engagement signals, and portfolio-fit scoring, replacing the static call-list dialing that characterized pre-AI prospecting.

Prospect and qualify new institutional or retail clients using AI-enriched prospecting platforms: use Salesforce Financial Services Cloud Einstein or Outreach signal-based sequencing to prioritize outreach based on life-event triggers (inheritance, liquidity events, executive stock-vesting dates, business sale), engagement signals, and portfolio-fit scoring, replacing the static call-list dialing that characterized pre-AI prospecting.[10],[11]

Where your edge is

AI surfaces the right prospect at the right moment; the human still has to convert that signal into a relationship. Develop a disciplined outreach process that personalizes beyond what the AI inserts automatically (reference a specific public event in the prospect's professional life, a shared connection, or a relevant market development) to move from acknowledged to trusted advisor. Conversion from AI-identified lead to first meeting still requires a human who can credibly represent the firm's capabilities.

AI is sitting alongside you hereMonitor client portfolios and market conditions on a continuous basis using AI-driven portfolio surveillance and alerting: use S&P Capital IQ Pro or FactSet Mercury to generate automated alerts on credit rating changes, earnings estimate revisions, position limit breaches, or market-moving events affecting client holdings, then prioritize which AI-generated alerts warrant proactive client outreach vs

Monitor client portfolios and market conditions on a continuous basis using AI-driven portfolio surveillance and alerting: use S&P Capital IQ Pro or FactSet Mercury to generate automated alerts on credit rating changes, earnings estimate revisions, position limit breaches, or market-moving events affecting client holdings, then prioritize which AI-generated alerts warrant proactive client outreach vs. which require no action.[12],[13]

Where your edge is

AI has essentially eliminated the possibility of missing a significant event affecting a client's holdings: the alerting layer is commoditized. The residual human value is in alert triage (which client genuinely needs a call about this news vs. which already knows and has acted) and in the advisory conversation that follows: positioning the event in the client's overall portfolio context and recommending a response that is appropriate to their specific situation and risk profile.

Where financial services sales agents go next

Natural next steps for someone with your foundation: not exits, evolutions.

What each move takes

A direction you could grow

Sales Managers

High-performing securities sales agents with track records of quota attainment and client relationship development are the natural pipeline for sales management roles, overseeing a coverage team, managing pipeline health, and coaching junior reps on client development strategy. AI is changing the Sales Manager role (Salesforce Agentforce and Gong generate forecasts and call analytics automatically), but quota accountability, talent development, and strategic account oversight remain irreducibly human. The transition is well-understood in broker-dealer and investment banking contexts: top producers promoted to regional or coverage team management. Slightly lower CRI reflects that sales management layers face their own automation pressure on administrative and reporting functions.

What you'd add
  • · Sales pipeline management: Salesforce or HubSpot pipeline analytics, forecast accuracy, rep productivity dashboards
  • · Coaching methodology using Gong call reviews: structured feedback frameworks and performance improvement plans
  • · Hiring and onboarding: building a broker-dealer or institutional-sales hiring scorecard and licensing onboarding process
  • · Incentive compensation design: commission structures, grid-based production credits, retention arrangements
  • · Regulatory supervisory procedures: FINRA Rule 3110 principal-review obligations for a team
What it takesSome new skills to pick up
Tools of the era

How has the work of financial services sales agents changed since 1792?

The tools that defined the work, one line per era. Select an era to see how it reshaped the work.

  • Quill, ledger book, and word of mouth

    Before the telegraph, every securities trade depended on physical presence or letter. Brokers in New York could not know the price of a stock in Boston or Philadelphia without waiting for a rider or a ship. Prices diverged between cities by amounts that patient arbitrageurs could exploit with days-long round trips. The New York market's authority derived partly from the Buttonwood Agreement's discipline (fixed commissions, counterparty accountability among members) but its informational reach stopped at the Hudson.

  • Stock ticker tape (Calahan 1867, Edison 1871)

    On November 15, 1867, Edward A. Calahan unveiled the first stock ticker at the Gold and Stock Telegraph Company in New York: a machine that printed stock symbols and prices onto a moving strip of paper via telegraph cable, propagating real-time quotes across the city for the first time. Thomas Edison improved Calahan's design in 1871 with his Universal Stock Printer, which synchronized all machines on a telegraph line. For the first time, a broker's customer in a downtown office could see prices update in real time without standing on the floor of the exchange. The ticker democratized market information within a city and opened the era of the retail brokerage office: a storefront with a ticker machine, a chalkboard, and a broker ready to take orders.

    Effect on the work

    The ticker created the category of off-floor retail broker. Before the ticker, only floor members could trade in real time. After, any storefront with a telegraph connection could offer real-time quotes and order execution, expanding the broker labor market from a few hundred floor members to tens of thousands of customer-facing registered brokers over the next generation.

  • Telephone + private wire service

    The telephone, reaching brokerage offices by the early 1900s, transformed the customer's man from a figure who had to physically visit clients to one who could serve them remotely. Large brokers ran private wire services, leased telegraph and telephone circuits, connecting branch offices across cities, allowing a single firm to have a national reach. The "wire house" model (Merrill Lynch, Kidder Peabody, E.F. Hutton) was built on this infrastructure: a retail client in Des Moines could call a local branch and have their order executed on the NYSE floor within minutes. This model defined the occupation for the first half of the 20th century.

  • Negotiated commissions + early quote machines (Quotron)

    May 1, 1975, "May Day", ended more than a century of fixed-commission rates on NYSE trades. Before May Day, every broker charged the same mandatory minimum fee; after, commissions were negotiable and immediately began collapsing. Charles Schwab & Co., incorporated in 1971, opened its first branch in Sacramento in September 1975 and cut commissions in half, creating the discount brokerage category. Quotron Systems, which began replacing handwritten order tickets with terminal-based quote retrieval in the late 1960s and early 1970s, accelerated the back-office efficiency that made discount commissions viable.

    Effect on the work

    May Day bifurcated the occupation permanently: full-service wirehouses (Merrill Lynch, Smith Barney, Dean Witter) retained brokers on high-commission-plus-advisory models; discount brokers (Schwab, Fidelity Brokerage) operated on low-commission, high-volume, execution-only models with far fewer people per trade. Commission compression did not immediately reduce headcount, it expanded access to stock trading for middle-class investors, but it began the structural trend of extracting value from the execution layer of the job.

  • Bloomberg Terminal (1982)

    In December 1982, Michael Bloomberg delivered the first Bloomberg Terminal units to Merrill Lynch: the company had purchased a stake in Bloomberg's firm, Innovative Market Systems, in exchange for a five-year non-compete restriction. The Terminal provided real-time bond pricing, yield analytics, and financial data in a single workstation at a high annual cost. For securities sales agents at institutional desks, the Bloomberg Terminal became the primary lens through which markets were seen and analyzed: from the mid-1980s onward, to not have a Bloomberg on your desk was to not be in the institutional securities business.

    Effect on the work

    Bloomberg reached thousands of terminal subscribers by 1991. The Terminal raised the analytical floor for institutional brokers: a salesperson now had to be able to interpret Bloomberg data and build basic fixed-income analytics in addition to managing client relationships. Over time the Terminal's standardization of market information raised the skill threshold while commoditizing the informational edge that had previously justified high commissions on institutional trades.

  • Online brokerage (E*Trade 1992, Schwab.com 1996)

    William Porter's TradePlus executed the first online trade over CompuServe in July 1983; by 1992 it had rebranded as E*TRADE Securities. By 1996, Schwab had launched Schwab.com with online trade execution; E*TRADE went public in 1996 as well. The "order taker" function that had sustained a large portion of full-service broker employment was technologically redundant for any client who knew what they wanted to buy. The retail stockbroker's role was forced up the value chain: execution was no longer a service worth paying for; advice, selection, and financial planning were.

    Effect on the work

    Full-service brokerage employment did not immediately collapse because the late-1990s bull market expanded the total pool of investors; but the long-run structural pressure on transaction-focused retail brokers was established. The dot-com crash in 2000-2002 collapsed retail trading volumes and eliminated many commission-dependent brokers who had not transitioned to fee-based advisory models.

  • Zero-commission trading (Robinhood 2013 → industry-wide 2019)

    Vladimir Tenev and Baiju Bhatt founded Robinhood in April 2013 on a single premise: every trade should cost nothing. Schwab, TD Ameritrade, and E*TRADE all eliminated commissions within days of each other in October 2019, following competitive pressure from Robinhood's rise. The price of executing a trade had reached zero. For a broker whose job was to accept orders and execute them, the "customer's man" model that had been the dominant form of the occupation since 1900, there was no longer a business model. The final structural displacement of the pure transaction broker was complete.

    Effect on the work

    The zero-commission wave eliminated the last economic rationale for paying a broker to execute a simple trade. BLS OEWS establishment-survey employment actually rose during this period (from 437,880 in 2019 to 472,300 in 2024) because the occupation's survivor population shifted heavily toward wealth management, institutional sales, and financial services sales: work where the broker adds value through relationship, advice, and product complexity rather than execution alone.

  • AI research and sales intelligence: Morgan Stanley AI Assistant, FactSet Mercury, Bloomberg AI Assist

    September 2023: Morgan Stanley fully rolled out AI @ Morgan Stanley Assistant, a GPT-4-powered internal chatbot giving thousands of financial advisors and sales professionals instant search across about a hundred thousand research documents. Adoption reached 98% of Morgan Stanley advisor teams. In December 2023 FactSet released FactSet Mercury in beta, an LLM-based chatbot that answers company-research questions from FactSet data, aimed first at junior bankers (FactSet then reported more than a hundred thousand individual users). Bloomberg AI Assist (2025) added natural-language query capabilities to the Terminal. For securities sales agents, these tools automate the research-retrieval and document-synthesis layer of the job: the cognitive work that previously justified the premium a client paid for expert access to market intelligence.

    Effect on the work

    Morgan Stanley AI @ Debrief saves advisors many minutes of post-meeting administrative work per client interaction. The pattern is consistent across tools: AI handles research production and documentation; the human holds the relationship, exercises judgment on product suitability, and executes the client conversation that converts intelligence into action.

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Securities, Commodities, and Financial Services Sales Agents employment and pay by year

On record since1792
Latest US employment489,570 (May 2025)Source: BLS OEWS May 2025Official statisticReport an error
Latest US median pay$78,660 (May 2025)Source: BLS OEWS May 2025Official statisticReport an error
Outlook+1.4% by 2035Source: BLS Employment Projections 2025-35Official statisticReport an error

In other countries

The latest figure each country's statistics agency publishes for this job. Each uses its own occupation definition, survey basis and currency, so the numbers are not directly comparable with each other or with the US figures.

  • Australia (ANZSCO 2222)

    Employment, 2025
    19,500, ABS Labour Force Survey Official statistic Report an errorABS Labour Force Survey (Detailed), table EQ08: employed persons in ANZSCO 2222 Financial Dealers, national (summed across sex and state/territory), annual average of 4 quarterly estimates.
    Median pay, 2025
    A$137,852, ABS Employee Earnings May 2025 Official statistic Report an errorAnnualised (x52) from A$2,651 median weekly earnings. ABS Survey of Employee Earnings and Hours, May 2025: median pay for full-time non-managerial employees paid at the adult rate, before tax. Surfaced via the Jobs and Skills Australia occupation profile.
View all 28 years of cited US data, each linked to its source
YearUS employmentAnnual pay (median unless marked)SourceReport
19005,000n/aEst., NYSE Researched contextReport
192970,000n/aEst., Wikipedia Researched contextReport
194030,000n/aEst., Library of Congress Researched contextReport
1975130,000n/aEst., Wikipedia Researched contextReport
2002254,600$60,990BLS OEWS 2002 Official statisticReport
2003245,280$60,530BLS OEWS May 2003 Official statisticReport
2004240,500$69,200BLS OEWS May 2004 Official statisticReport
2005251,710$67,130BLS OEWS May 2005 Official statisticReport
2006260,360$68,500BLS OEWS May 2006 Official statisticReport
2007268,480$68,430BLS OEWS May 2007 Official statisticReport
2008271,900$68,680BLS OEWS May 2008 Official statisticReport
2009271,670$66,930BLS OEWS May 2009 Official statisticReport
2010276,290$70,190BLS OEWS May 2010 Official statisticReport
2011307,020$72,060BLS OEWS May 2011 Official statisticReport
2012330,470$71,720BLS OEWS May 2012 Official statisticReport
2013325,140$72,640BLS OEWS May 2013 Official statisticReport
2014316,340$72,070BLS OEWS May 2014 Official statisticReport
2015319,280$71,550BLS OEWS May 2015 Official statisticReport
2016353,780$67,310BLS OEWS May 2016 Official statisticReport
2017389,610$63,780BLS OEWS May 2017 Official statisticReport
2018415,890$64,120BLS OEWS May 2018 Official statisticReport
2019437,880$62,270BLS OEWS May 2019 (employment) Official statisticBLS OEWS May 2019 (pay) Official statisticReport
2020440,300$64,770BLS OEWS May 2020 Official statisticReport
2021426,870$62,910BLS OEWS May 2021 Official statisticReport
2022443,220$67,480BLS OEWS May 2022 Official statisticReport
2023479,630$76,900BLS OEWS May 2023 (employment) Official statisticBLS OEWS May 2023 (pay) Official statisticReport
2024472,300$78,140BLS OEWS May 2024 Official statisticReport
2025489,570$78,660BLS OEWS May 2025 Official statisticReport
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