Financial Compliance Officers
United States · BLS Employment Projections 2024–34 (figures for SOC 13-1041 occupational group)
AI exposure in published research
Figures below are reproduced from external datasets without modification. Where a dataset does not cover this occupation, the value is shown as — rather than as zero.
Data provider: OpenAI · "GPTs are GPTs"
Time basis: 2023 baselineex-ante estimate
Scored against GPT-4-generation capability.
- Human rater basis
- 48.8%
- GPT-4 rater basis
- 45.1%
β = direct exposure (E1) + 0.5 × exposure when tools are available (E2), per the source repository's definition.
26 rated tasks · 19 tasks with β ≥ 0.5 (73.1%)
- Version:
- gh-main-0471612
- License:
- MIT License · Copyright (c) 2024 OpenAI
Data provider: Anthropic Economic Index
Time basis: Published 2026-03-05composite index
- Observed exposure
- 12.1%
Theoretical exposure index weighted by measured Claude usage, per the original report's definition.
110 tasks · usage observed in 10 · mean 7.6%
Data: Anthropic Economic Index — labor_market_impacts, CC-BY, https://huggingface.co/datasets/Anthropic/EconomicIndex
AI Changing Work uses Anthropic Economic Index data under CC-BY; Anthropic does not endorse or sponsor this site or its analyses.
- Version:
- hf-lmi-2026-03
- License:
- CC BY 4.0
- Observation period:
- — (not applicable to this release)
- Model:
- — (not stated by the source)
- Definition source:
- https://www.anthropic.com/research/labor-market-impacts
2023 prediction vs observation-based index published 2026-03-05
One card (GPTs are GPTs) is a 2023 estimate of what AI could theoretically do; the other (Anthropic Economic Index) is built from observed usage and was published on 2026-03-05 — that is its publication date, not the period it observed. They measure different things, so the two figures cannot be added, averaged, or ranked against each other. The older figure is kept here as a baseline for comparison rather than removed.
Caution: the Anthropic figures — observed exposure and task penetration — take the Eloundou β as one of their inputs. The two sides resembling each other is therefore not evidence that the earlier prediction came true; reading it that way is circular reasoning.
The Anthropic figures are measured on Claude users, who are not the whole economy and not the whole workforce.
The mapping of O*NET tasks and occupation codes was performed by AI Changing Work. The source figures themselves were not modified.
These indices are not forecasts. Which point in time each one belongs to is stated on the badge on its card.
Task Breakdown
- Monitor transactions for suspicious activity and AML violations
- Conduct regulatory compliance audits and risk assessments
- Develop and update compliance policies and procedures
- File regulatory reports and suspicious activity reports
- Train staff on compliance requirements and ethical standards
About This Occupation
If you work as a Financial Compliance Officer, AI is reshaping your profession. With an automation risk of 48/100 and overall exposure at 59%, this role faces high transformation. The highest-impact area is monitor transactions for suspicious activity and AML violations at 78% automation. This is classified as an 'augment' role where AI handles transaction screening and pattern detection while officers focus on policy development, regulatory relationships, and judgment-intensive investigations. BLS projects +6% growth through 2034.
ISCO-08 classification
Government Licensing Officials
Indirect mapping — this occupation is linked to the ISCO unit group by a rule-based fallback.
Definition
ILO original text (English)
Government licensing officials examine applications for licences to export or import goods, set up businesses, build houses or other structures, or to obtain passports, determine eligibility of applications for issuing licences or passports, and identify specific conditions or restrictions to be attached to licences issued, referring exceptional or important cases to senior government officials or managers.
Definition & vocabulary source
Source: International Labour Organization (ILO) — ISCO-08 Structure
License: ILO CC BY 4.0
Official occupational information
- ONET13-1041.00
Compliance Officers
Examine, evaluate, and investigate eligibility for or conformity with laws and regulations governing contract compliance of licenses and permits, and perform other compliance and enforcement inspection and analysis activities not classified elsewhere.
View original - ONET43-4031.00
Court, Municipal, and License Clerks
Perform clerical duties for courts of law, municipalities, or governmental licensing agencies and bureaus. May prepare docket of cases to be called; secure information for judges and court; prepare draft agendas or bylaws for town or city council; answer official correspondence; keep fiscal records and accounts; issue licenses or permits; and record data, administer tests, or collect fees.
View original
Frequently Asked Questions
The Anthropic Economic Index puts observed exposure at 12.1%. The OpenAI "GPTs are GPTs" rubric puts occupation-level β at 48.8% under human raters. Both figures are reproduced from published research without modification.
They come from two published datasets: the Anthropic Economic Index (labor_market_impacts, CC BY 4.0) and the OpenAI "GPTs are GPTs" exposure rubric (MIT License, Copyright (c) 2024 OpenAI). AI Changing Work maps them onto O*NET occupation and task codes and does not calculate exposure scores of its own. AI Changing Work uses Anthropic Economic Index data under CC-BY; Anthropic does not endorse or sponsor this site or its analyses.
No. They are a diagnosis of exposure as measured at the time each source dataset was published. AI Changing Work publishes no prediction of future automation or job displacement for this occupation.