Insurance/Underwriting clerk
AI displacement risk
63%
Range 55.39–69.86%
Insurance/Underwriting clerk has 88% AI task overlap with only 3% human bottleneck protection — higher risk than 98% of occupations in the live market. Structural displacement pressure is significant.
Clerical Support Workers·SGD 5,045/mo (3,791–7,333)·~2.9K workers in SG·Updated 2026-06-11
Structural pressure, not a prediction of job loss. Displacement tends to arrive through slower hiring, wage compression and role redesign before layoffs.
Why This Score
88% of tasks overlap with current AI
3% human advantage from judgment & presence
48% demand buffer from the local labour market
AI usage 20pp below theoretical exposure
These factors interact with each other — the final score is not a simple sum of these bars.
How much AI overlaps with this job's tasks, offset by human advantages and local demand. How this works
Tasks AI can handle
With 88% AI task overlap (based on Felten AIOE, Anthropic Economic Index, Eloundou GPT exposure, and ILO occupational exposure), the Insurance/Underwriting clerk tasks most exposed include: financial modeling, data extraction from filings, ratio analysis, report generation, transaction categorization, and regulatory document summarization.
- • Examine letters from policyholders or agents, original insurance applications, and other company documents to determine if changes are needed and effects of changes.
- • Process and record new insurance policies and claims.
- • Process, prepare, and submit business or government forms, such as submitting applications for coverage to insurance carriers.
O*NET tasks for this occupation with the most observed AI usage (Anthropic task data).
What AI can't do here
At 3% human bottleneck protection, the tasks that remain hardest to automate for Insurance/Underwriting clerk include: judgment on risk vs. return, client advisory relationships, regulatory interpretation in edge cases, fraud detection in novel scenarios, and strategic capital allocation.
Main insulation channels: Non-routine work + High-stakes decisions — the work-context dimensions behind this occupation's human bottleneck.
Skills to focus on
Sources: Felten AIOE (2021), Anthropic Economic Index (2026), Eloundou GPT Exposure (Science, 2024), ILO GenAI (2025), Pizzinelli et al. bottleneck model. Full methodology.
Singapore Now
Current labour market conditions and how they affect this role.
Cooling, but not collapsing. Vacancies are softer, yet retrenchment remains low and hiring still exceeds resignations.
Vacancy
3.1%
↓ 11.4% YoY
Hiring
2.6%
vs 1.6% resign
Retrenchment
1.5
per 1,000 · low
Re-entry
78.5%
find work in 12mo· -1.6pp
Clerical, Sales & Service Workers · 2025 Q4
Top Industries
Industry vacancy overlays use the latest published detailed cross-tab, which can lag the main labour monitor.
What You Can Do
Insurance/Underwriting clerk has some offset potential, but it depends on transition pathways holding up in practice and on workers clearing the main switching frictions.
Published transition support
Related roles you could transition to
Risk-reducingHigh displacement pressure, but comparatively credible risk-reducing moves exist — the strongest scores 68% match. Escape-route quality, not pressure alone, shapes how risk resolves.
Compare within Clerical Support Workers
See how this compares to similar occupations
Compare with... →Classification
Higher risk than 98% of occupations · V7 structural score
Raw scores
AIOE 1.296 · θ 0.561 · C-AIOE 1.198
Stability
stable · Optimistic 60% · Pessimistic 72%
Score range (best/worst case)
Exposure 79–95% · Net risk 55.39–69.86%
Scoring basis
V7 structural score. Uses task-concentration-weighted exposure, human bottleneck, and demand resilience. V6 baseline fields are retained for release-to-release comparison.-3.2pp versus retained V6 baseline.
Wage range (SGD/mo)
25th 3,791 · Median 5,045 · 75th 7,333
Evidence & sources
Data matching
direct · SSOC 43122
Real-world AI usage: -20% vs estimated
Data quality
77% · Matching 0.92 · Market data 0.70 · Freshness 0.84
Capped at high · Final rating: medium · capped for conflicting signals
100% weighted task match · 16% effective coverage
AI overlap by data source
Weights: aioe 24% · anthropic 26% · eloundou 25% · ilo 26%
Conflicting data signals
Tools & offset factors
What helps
- Nearby moves and published transition support look reasonably strong.
What could slow it down
- Current demand support is thin, so offsets may take longer to show up.
Worker profile & local context
- Vacancy rate is 3.1% and fell by 0.2 points from last quarter.
- Hiring read: recruitment is running above resignation (2.6% vs 1.6%).
- Retrenchment was low at 1.5 per 1,000 employees.
- 78.5% of retrenched workers re-entered employment within 12 months.
- Employer pressure is low, based on 2 recent Singapore-relevant company signals.
Worker profile
Gender mix
37% male / 63% femalePublished Singapore worker composition for the detailed occupation family 43 Numerical & Material-Recording Clerks.
Employment structure
Employee-heavy99% employees, 1% employers or self-employed workers.
Work arrangement
Mostly full-time13% part-time and 87% full-time in 2025.
Age profile
Older-skewing16% aged 15 to 29, 35% aged 30 to 49, and 49% aged 50 or older.
Qualification mix
Mixed qualificationsSecondary 29%; Diploma / professional qualification 28%.
Gross wage by sex
Female median 23% lowerPublished June 2024 gross wage medians: male $6,271, female $4,800.
Where this work is concentrated
Top planning areas
Jurong West, Tampines, Woodlands22% of workers in this occupation group live in these three planning areas.
Residential concentration
Moderately clustered35% live across the top five planning areas in the 2020 Census.
Commute pattern
Longer commutesEstimated average commute 39.7 minutes. 38% take 46 minutes or more.
Role profile
How this role's work breaks down across key dimensions. This is a general profile, not an individual measurement.
Workflow dimensions (0 = low, 1 = high)
How this changes by career stage
Senior workers benefit from institutional knowledge and judgment that AI cannot replicate. Entry-level roles have higher task overlap with AI.
Frequently asked questions
Will AI replace Insurance/Underwriting clerk?
Insurance/Underwriting clerk has 88% AI task overlap with only 3% human bottleneck protection — higher risk than 98% of occupations in the live market. Structural displacement pressure is significant. Net displacement risk: 63% (Very High). Median wage: SGD 5,045/month.
What is the AI risk score for Insurance/Underwriting clerk?
Insurance/Underwriting clerk has an AI displacement risk of 63%, rated Very High. AI task overlap: 88%. Human advantage: 3%. Local demand buffer: 48%.
What career transitions are available for Insurance/Underwriting clerk?
Insurance/Underwriting clerk has modeled transition pathways to related occupations. The strongest adjacent pathway is Quality control/assurance manager, based on skill and wage similarity (model-estimated). Transition scoring accounts for wage preservation, training ease, and destination quality.
How does Insurance/Underwriting clerk salary compare in the live market?
Insurance/Underwriting clerk earns a median gross wage of SGD 5,045/month in the live market (25th-75th percentile: SGD 3,791-7,333). This is 12% above median across all 562 scored occupations, and 58% above group median within Clerical Support Workers occupations.