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Time Machine

Brokerage Clerks

Scrub through 244years of this role's history, from when it first emerged, through every wave of technology that reshaped it, to the cited projections for where it's heading next.

2026drag to travel through time
180018251850187519001925195019752000now
2026
Known today as Brokerage Clerks (BLS SOC 43-4011)
Latest actual · 2024
40K
OEWS is a point-in-time survey snapshot, not a continuous time series; BLS advises against using it for year-over-year trend comparison.
Latest actual · 2024
$62,940
Source: BLS-OEWS
Each dot is a cited figure over time; the dotted line only links them (values between aren't measured). Hollow dots are estimates.
Tools of the era

The tools that defined the work

Select an era to see how it reshaped the work.

  • Ledger book, quill pen, and stock runner (manual era)

    The founding era of organized securities trading ran entirely on handwritten ledgers, quill pens, and a class of workers called runners or "paper boys" who physically carried stock certificates, order slips, and cash between brokerage houses, banks, and the NYSE floor. Every trade required a paper certificate to move from seller to buyer by hand. The counting-house clerk recorded each transaction in a bound ledger, computed commissions and taxes by hand, and maintained the firm's stock position manually. Speed depended entirely on how fast a messenger could run.

    Effect on the work

    Each additional percentage point of trading volume growth required a proportional increase in clerks and runners. Labor was the only scalable resource; the occupation grew in direct proportion to market volume.

    Ledger workPaper recordkeeping
  • Stock ticker, telephone, and paper certificate system (volume-scaled manual era)

    The Edison stock ticker (1867, refined through the 1870s) allowed market prices to be transmitted electrically across the country, driving order volumes far beyond what prior messenger systems could handle. The telephone arrived on the NYSE floor in the 1870s, further accelerating order flow. The back office response was to scale up the clerk workforce: large firms employed dozens of specialized clerks (transfer, margin, dividend, purchase-and-sale, receive-and-deliver) each handling a distinct workflow node. Physical stock certificates, engraved on heavy paper, still had to travel between firms by messenger for each settlement. By the 1920s, the streets around Wall Street were clogged with messenger boys carrying certificates up and down the financial district.

    Effect on the work

    Stock market volumes roughly tripled between 1929 and 1968 (from about 1 billion shares per year in 1929-1950 to 3 billion by 1968). Back office staffing scaled with volume. By 1968, the paperwork load had outrun even a massively expanded clerk workforce.

    Work toolChanging equipment
  • DTC book-entry system and mainframe settlement (first automation era)

    The 1968 paperwork crisis forced the industry to abandon the physical certificate delivery model. The NYSE established the Central Certificate Service (CCS) in 1968 as a stopgap, then the Depository Trust Company (DTC) was founded in 1973 to implement a comprehensive book-entry system: certificates would be immobilized in a central depository and ownership transfers made as electronic ledger entries rather than physical deliveries. Mainframe computers were introduced in large firms during the late 1960s and 1970s, though they were expensive and required specialist management few smaller firms could provide. The standard settlement cycle during this period was T+5 (five business days after trade date), reflecting the manual processing time still required even with early automation. The brokerage clerk role narrowed from general settlement worker to specialized positions in exception handling, customer account management, and regulatory record-keeping.

    Effect on the work

    The DTC and mainframe era reduced the peak crisis-level clerk headcount substantially. Firms that had hired emergency third shifts in 1967-1968 did not need to replace those workers as volume returned to normal post-1970. Industry employment in the securities sector (New York alone) was approximately 74,500 in 1973 and grew to 130,000 by 1985 as markets recovered, but the growth was in sales, analytical, and technology roles rather than in the back office clerk category.

    Mainframe processingComputerized records
  • T+3 settlement, electronic order entry, and STP (straight-through processing)

    On October 6, 1993, the SEC adopted Rule 15c6-1 shortening the standard US securities settlement cycle from T+5 to T+3, effective June 7, 1995. The rule was made possible by widespread adoption of facsimile machines, electronic order routing, and centralized clearing through the NSCC (National Securities Clearing Corporation, founded 1976). Simultaneously, electronic order entry systems replaced the telephone-and-paper slip workflow on the sales side, feeding directly into automated clearing pipelines. The National Securities Clearing Corporation and Depository Trust Company merged under the DTCC holding company in 1999, creating a single clearing-and-settlement entity. Straight-through processing (STP) began automating the entire trade lifecycle from execution through settlement without manual intervention for standard transactions. Brokerage clerks became concentrated in the exceptions: failed trades, corporate actions, option exercises, and customer account disputes that STP could not handle.

    Effect on the work

    From approximately 97,894 clerical workers in the securities brokerage industry in 2000 (EEOC EEO-1) to an estimated 75,000 BLS SOC 43-4011-specific brokerage clerks in the mid-2000s, a contraction of roughly a quarter. The post-dot-com bust (2001-2003) accelerated layoffs as brokerage volumes fell and firms cut back office costs aggressively. By 2024 the BLS counted 40,800 in the role, a further halving from the mid-2000s level.

    Work toolChanging equipment
  • T+2 settlement, cloud-based portfolio systems, and algorithmic reconciliation

    The SEC moved the standard settlement cycle from T+3 to T+2 in 2017, effective September 5. The change was enabled by continuous improvements in real-time trade matching, automated reconciliation, and industry-wide straight-through processing. Cloud-based portfolio accounting systems (BlackRock Aladdin, SimCorp, Broadridge) further automated the record-keeping, pricing, and corporate-action workflows that had been manual brokerage clerk tasks. Machine learning models began flagging reconciliation breaks and failed-trade exceptions automatically, replacing much of the pattern-recognition work that experienced back office clerks had previously done. The brokerage clerk role by the early 2020s was predominantly exception management, regulatory reporting, and client-facing account inquiries for complex situations.

    Effect on the work

    Brokerage clerk employment fell from approximately 75,000 in 2004 to approximately 40,800 in 2024, a decline of roughly 46% over twenty years. The remaining workforce is concentrated in large custodians, prime brokers, and full-service broker-dealers where the complexity of institutional client accounts and regulatory reporting still requires human expertise.

    Work toolChanging equipment
  • T+1 settlement, AI-assisted reconciliation, and real-time processing

    Effective May 28, 2024, the SEC moved US securities settlement to T+1, compressing the window for post-trade processing to a single business day. T+1 eliminates most of the overnight manual verification workflows that brokerage clerks had retained even as earlier automation waves compressed their numbers. AI-assisted reconciliation tools can now flag, categorize, and often auto-resolve the breaks and exceptions that previously required a clerk's judgment. The remaining brokerage clerk tasks are primarily complex exception handling (cross-border trades, corporate actions on illiquid securities, estate account transfers) and regulatory reporting that requires a licensed, accountable human in the workflow.

    Effect on the work

    BLS projects a further 9.5% employment decline for SOC 43-4011 from 2024 to 2034 (40,800 to 36,900 positions), representing the acceleration of a multi-decade contraction. The pace of AI adoption in reconciliation and exception-management platforms could steepen this decline beyond the BLS central estimate.

    Work toolChanging equipment
Projection cone · present → 2034

What credible sources project

Scrub the slider past now to anchor each scenario on the scrubber. The spread is the range of futures credible sources project for this role.

Employment outlook
Projected change in the number of people doing this work.
BLS Employment Projections 2024-34 -- Securities, commodity contracts, and financial investments sector
2034
-5%
BLS projects overall employment in the securities, commodity contracts, and financial investments sector (NAICS 523) to decline modestly over 2024-34, driven by continued automation of back office and administrative functions. The sector-level projection is less steep than the occupation-specific 43-4011 projection because it includes growth in compliance, risk management, and quantitative roles that offset back office contraction. Reported here as a cross-check against the occupation-level projection; they move in the same direction as expected.
BLS National Employment Matrix 2024-34
2034
-9.5%
BLS Employment Projections industry-occupation matrix. The 2024-34 cycle projects -9.5% employment change for SOC 43-4011, from 40,800 to approximately 36,900 positions. The BLS methodology cites continued automation of back office processing, the shift to T+1 settlement compressing manual verification windows, and declining demand from industry consolidation as the primary drivers. Approximately 4,100 openings per year are still projected from retirements and career transitions out of the role.
AI task exposure
Share of the role’s tasks that researchers estimate AI can do. This is a measure of task exposure, not a forecast of jobs lost.
Eloundou et al. -- "GPTs are GPTs" (2023)
2028
20%
of tasks
GPT-4 task-by-task LLM exposure labeling on O*NET tasks for financial clerks. Brokerage clerks score in the high range for LLM exposure because their primary tasks (document verification, transaction computation, correspondence with customers, regulatory record-keeping) are highly text-based, rules-driven, and structured, exactly the task profile where large language models perform well. The -20% estimate reflects this indirect channel: AI reconciliation and exception-flagging tools reduce the need for human clerks to handle routine processing, while more complex tasks (corporate action disputes, cross-border settlement fails, estate account management) remain human-in-the-loop.
Today, in this role

What's shifting in the work right now

The historical view above shows how this role has moved. This is the present-day detail: which AI tools are picking up which tasks, where the edge still is, and the natural directions this work can grow.

What's changing in your day

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

AI is sitting alongside you hereDocument security transactions, such as purchases, sales, conversions, redemptions, or payments, using computers, accounting ledgers, or certificate records.

Document security transactions, such as purchases, sales, conversions, redemptions, or payments, using computers, accounting ledgers, or certificate records.[2]

Where your edge is

AI is sitting alongside you hereFile, type, or operate standard office machines.

File, type, or operate standard office machines.[2]

Where your edge is

AI is sitting alongside you herePerform clerical tasks, such as answering phones or distributing mail.

Perform clerical tasks, such as answering phones or distributing mail.[2]

Where your edge is

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The data behind this timeline

On record since1792
Latest tracked employment40,090 (US, 2024)
Latest median pay$62,940 (2024)
Outlook-9.5% by 2034 (BLS National Employment Matrix 2024-34)
View all 24 cited data points
YearUS employmentMedian annual paySource
1968150,000n/aESTIMATE
200097,894n/aESTIMATE
200375,380$34,090BLS-OEWS
200473,910$35,240BLS-OEWS
200570,110$35,450BLS-OEWS
200672,400$36,390BLS-OEWS
200771,170$37,360BLS-OEWS
200868,430$38,710BLS-OEWS
200962,470$40,180BLS-OEWS
201057,600$40,160BLS-OEWS
201160,720$41,760BLS-OEWS
201261,870$42,440BLS-OEWS
201360,300$45,450BLS-OEWS
201457,240$47,520BLS-OEWS
201557,490$48,180BLS-OEWS
201659,820$49,200BLS-OEWS
201758,930$49,800BLS-OEWS
201855,100$51,400BLS-OEWS
201947,990$52,750BLS-OEWS
202044,720$55,270BLS-OEWS
202139,980$54,000BLS-OEWS
202242,700$54,680BLS-OEWS
202348,060$60,150BLS-OEWS
202440,090$62,940BLS-OEWS
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