High AI Risk Average

Financial risk specialists

SOC Code: 13-2054

Financial risk specialists carries a 53% AI exposure score (High automation risk), with a median annual wage of $106,000 and +6.5% projected employment growth from 2024 to 2034 (BLS), affecting approximately 60,500 workers. Full task breakdown, skills, and employer data are below.

AI Exposure Score
53% High

Proportion of tasks susceptible to AI automation (O*NET analysis)

Projected Growth
+6.5%
2024–2034 (BLS)
+3,900 jobs
Median Annual Wage
$106,000
BLS May 2024
How wage figures are sourced →

AI Exposure vs Industry Growth

Workforce demand by occupation Sanctioned bespoke signature viz (@signature-viz, KIZ-799) showing occupation-level workforce demand from BLS OEWS data. Pure SVG, no external dependencies.Projected Growth 2024-2034 (BLS)Technology+12.8%Healthcare+10.2%Professional+7.8%Education+5.8%Construction+4.5%Finance+4.6%Logistics+3.2%Government+1.2%Manufacturing-2.1%Retail-3.4%
National AI Exposure
40%
Average across all occupations
Avg Wage Growth
+3.2%
Median annual wage change
High-Risk Roles
127
Occupations with >70% AI exposure

Total occupations tracked

832

Covering all SOC major groups

Data currency

2024

BLS Employment Projections

AI exposure avg

40%

Fleet-wide median across all roles

Methodology confidence 92.0%
Industry standard

Composite score weighing O*NET task data completeness, BLS projection methodology, and cross-validation with employer risk grades.

Employment Projections

60,500
Employment 2024
64,400
Projected 2034
+6.5%
Change (%)
+3,900
Change (jobs)

Occupation Insight

Financial risk specialists (SOC 13-2054) carries an AI exposure score of 53%, placing it in the High automation-risk tier. This score is computed from O*NET Database 30.0 task-level analysis, where each task an occupation performs is evaluated against current generative AI, robotic process automation, and machine-learning capabilities. A score in the 40–70% range indicates meaningful automation pressure on specific task categories, but the role as a whole still requires human judgment for coordination, exception handling, or client interaction.

The economic context matters alongside the risk score. BLS counted approximately 60,500 workers in this occupation in 2024, and projects a +6.5% change through 2034 — modest growth that keeps the occupation viable even as tasks evolve. Median annual compensation stands at $106,000, reflecting both skill scarcity and the value employers place on the tasks that remain difficult to automate. Entry typically requires Bachelor's degree, plus None of related experience.

For career planners, this profile should be read alongside the task, skill, and knowledge breakdowns below and the list of employers whose workforce composition includes Financial risk specialists. Adjacent occupations shown further down offer lateral moves that preserve industry knowledge while potentially reducing exposure. Pair the AI exposure score with the BLS employment projection and wage percentiles above for a complete career assessment.

Education & Entry Requirements

Typical Education
Bachelor's degree
Work Experience
None
On-the-Job Training
None

Top Tasks (O*NET)

  1. 1. Analyze areas of potential risk to the assets, earning capacity, or success of organizations.
  2. 2. Analyze new legislation to determine impact on risk exposure.
  3. 3. Conduct statistical analyses to quantify risk, using statistical analysis software or econometric models.
  4. 4. Confer with traders to identify and communicate risks associated with specific trading strategies or positions.
  5. 5. Consult financial literature to ensure use of the latest models or statistical techniques.
  6. 6. Contribute to development of risk management systems.
  7. 7. Determine potential environmental impacts of new products or processes on long-term growth and profitability.
  8. 8. Develop contingency plans to deal with emergencies.
  9. 9. Develop or implement risk-assessment models or methodologies.
  10. 10. Devise scenario analyses reflecting possible severe market events.

Frequently Asked Questions

Will AI replace Financial risk specialists?

Financial risk specialists has an AI exposure score of 53%, indicating a high level of automation risk. Some tasks in this role can be augmented or partially automated by AI, but core responsibilities require human judgment.

What is the job outlook for Financial risk specialists?

According to BLS Employment Projections 2024-2034, Financial risk specialists is projected to grow by 6.5% over the decade. Current employment stands at approximately 60,500 workers.

What skills are needed for Financial risk specialists?

Financial risk specialists requires a combination of technical knowledge and interpersonal skills. Typical education requirement: Bachelor's degree.

How much do Financial risk specialists earn?

The median annual wage for Financial risk specialists is $106,000, according to BLS Occupational Employment and Wage Statistics (May 2024). Actual earnings vary by location, experience, industry, and employer. The BLS publishes detailed wage percentiles by region in its Occupational Employment and Wage Statistics program.

What education is required for Financial risk specialists?

The typical entry-level education for Financial risk specialists is Bachelor's degree. Employers generally expect None of related work experience. On-the-job training typically involves None. Requirements can vary by employer and specialization.

Which companies employ Financial risk specialists?

Financial risk specialists roles exist across many industries and employers. Workforce composition is estimated from BLS industry-occupation employment distributions matched to SEC-registered public companies.

AI Exposure Rating

2.6
out of 5.0

High automation risk based on 10 analyzed tasks. A moderate share of tasks may be augmented by AI tools.

Data sources: Bureau of Labor Statistics Employment Projections 2024–2034 and O*NET Database 30.0. Employment figures are rounded. Wage data from BLS Occupational Employment Statistics (OES).

Related

Data sourced from official public datasets. See our methodology for details. Retrieved and formatted by PlainWorkforce Editorial