Insurance/Underwriting clerk
AI Exposure Rank
92/100
Range 88–99/100 across source-weight sensitivity checks
Insurance/Underwriting clerk has an AI Exposure Rank of 92/100, meaning its work is more exposed to current AI capabilities than approximately 92% of Singapore occupations. The evidence currently points to hiring or substitution pressure; this is a relative rank, not a probability of job loss.
Clerical Support Workers·SGD 5,045/mo (3,791–7,333)·~2.9K workers in SG·Updated 2026-06-11
Relative AI exposure, not a prediction of job loss. Hiring, wages and role design depend on many forces this rank does not forecast.
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.
The evidence behind this occupation's AI exposure, with human-work and demand context shown separately. 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
Exposure-reducingHigher AI exposure, but comparatively credible exposure-reducing moves exist — the strongest scores 67% match. Escape-route quality and labour demand matter alongside exposure.
Compare within Clerical Support Workers
See how this compares to similar occupations
Compare with... →Classification
More exposed than approximately 91% of occupations · V8 AI Exposure Rank· Polytechnic / ITE Diploma
Raw scores
AIOE 1.296 · θ 0.561 · C-AIOE 1.198
Stability
stable · Optimistic 60% · Pessimistic 72%
Score range (best/worst case)
Exposure sensitivity 79–95% · Rank sensitivity 88–99/100 across source-weight sensitivity checks
Scoring basis
V8 AI Exposure Rank. A relative Singapore occupation index. It ranks AI task exposure; it is not a probability of job loss or a percentage of tasks.
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
medium evidence · 4 exposure sources · direct mapping
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
Career stage can change the task mix and human context. These directional profiles are illustrative, not occupation-level forecasts of hiring or displacement.
Frequently asked questions
Will AI replace Insurance/Underwriting clerk?
Insurance/Underwriting clerk has an AI Exposure Rank of 92/100, meaning its work is more exposed to current AI capabilities than approximately 92% of Singapore occupations. The evidence currently points to hiring or substitution pressure; this is a relative rank, not a probability of job loss. AI Exposure Rank: 92/100 (Very High). Median wage: SGD 5,045/month.
What is the AI exposure rank for Insurance/Underwriting clerk?
Insurance/Underwriting clerk has an AI Exposure Rank of 92/100, rated Very High. It ranks higher than approximately 92% of Singapore occupations for exposure to current AI capabilities; it is not a job-loss probability.
What career transitions are available for Insurance/Underwriting clerk?
Insurance/Underwriting clerk has modeled transition pathways to related occupations. The strongest adjacent pathway is Insurance investigator, 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.