Financial markets back office administrator
AI Exposure Rank
99/100
Range 92–99/100 across source-weight sensitivity checks
Financial markets back office administrator has an AI Exposure Rank of 99/100, meaning its work is more exposed to current AI capabilities than approximately 99% of Singapore occupations. The evidence currently points to hiring or substitution pressure; this is a relative rank, not a probability of job loss.
Associate Professionals & Technicians·SGD 5,366/mo (4,000–6,700)·~9.8K workers in SG·Updated 2026-07-17
Relative AI exposure, not a prediction of job loss. Hiring, wages and role design depend on many forces this rank does not forecast.
How This Rank Is Built
The source percentiles are combined using the displayed reliability weights, then ranked against all 562 Singapore occupations. This is not a percentage of tasks and not a job-loss probability.
Likely job pathway
Hiring or substitution pressure
Current demand context
Mixed current demand
Pathway and demand are reported beside the exposure rank. Current demand does not change the rank.
The evidence behind this occupation's AI exposure, with human-work and demand context shown separately. Score stability: watch. How this works
Tasks AI can handle
With 91% AI task overlap (based on Felten AIOE, Anthropic Economic Index, Eloundou GPT exposure, and ILO occupational exposure), the Financial markets back office administrator tasks most exposed include: financial modeling, data extraction from filings, ratio analysis, report generation, transaction categorization, and regulatory document summarization.
- • Analyze operations to evaluate performance of a company or its staff in meeting objectives or to determine areas of potential cost reduction, program improvement, or policy change.
- • Interpret and explain policies, rules, regulations, or laws to organizations, government or corporate officials, or individuals.
- • Direct or coordinate an organization's financial or budget activities to fund operations, maximize investments, or increase efficiency.
O*NET tasks for this occupation with the most observed Claude usage (Anthropic task data).
What AI can't do here
At 29% human bottleneck protection, the tasks that remain hardest to automate for Financial markets back office administrator 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: Deep preparation + 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.
From exposure to employment
What could change the employment outcome?
AI capability is only the starting point. Adoption, task design, human oversight, demand, mobility and evidence quality determine how exposure may resolve in practice.
Workplace adoption
Leading sectors represented
All listed industries have MOM sector adoption evidence; observed-sector average 56.4%.
Task structure
Task evidence available
100% weighted task match · 5% effective coverage
Human advantage
Coordination and judgment still matter
At 29% human bottleneck protection, the tasks that remain hardest to automate for Financial markets back office administrator include: judgment on risk vs. return, client advisory relationships, regulatory interpretation in edge cases, fraud detection in novel scenarios, and strategic capital allocation.
Hiring and demand
3.4% vacancy rate · 2026 Q1
PMET vacancies increased from Q4 and remained below their year-ago level. Hiring stayed net positive but slowed, while retrenchment incidence remained the highest of the three broad occupation groups. In 2025, this broad occupation group had 2.3% time-related underemployment and 8.7% non-permanent employment. Across the published male and female series, CPI-adjusted median income changed -7.7% to -2.1% from 2018 to 2023.
Career transitions
Quality control/assurance manager
moderate modeled transition; outcomes still depend on skills, wages and openings.
Evidence strength
medium confidence
4 exposure sources · sensitivity 92–99/100 across source-weight sensitivity checks.
These lenses are reported separately and do not alter AI Exposure Rank. Labour-market figures describe a broad official occupation cluster, not this SSOC occupation alone.
Singapore Now
Current labour market conditions and how they affect this role.
Local conditions are under more strain. Vacancies have softened and displacement signals are less forgiving.
Vacancy
3.4%
↓ 2.9% YoY
Hiring
1.2%
vs 0.7% resign
Retrenchment
2.6
per 1,000 · moderate
Re-entry
69.1%
find work in 12mo· +1.4pp
Professionals, Managers, Executives & Technicians · 2026 Q1
Top Industries
Industry vacancy overlays use the latest published detailed cross-tab, which can lag the main labour monitor.
What You Can Do
Financial markets back office administrator 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 69% match. Escape-route quality and labour demand matter alongside exposure.
Compare within Associate Professionals & Technicians
See how this compares to similar occupations
Compare with... →Classification
More exposed than approximately 99% of occupations · V8 AI Exposure Rank· University Degree
Raw scores
AIOE 1.386 · θ 0.651 · C-AIOE 1.156
Stability
watch · Optimistic 45% · Pessimistic 58%
Score range (best/worst case)
Exposure sensitivity 86–95% · Rank sensitivity 92–99/100 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 4,000 · Median 5,366 · 75th 6,700
Evidence & sources
Data matching
direct · SSOC 33121
Real-world AI usage: -18% vs estimated
Data quality
medium evidence · 4 exposure sources · direct mapping
100% weighted task match · 5% effective coverage
AI overlap by data source
Weights: aioe 24% · anthropic 26% · eloundou 25% · ilo 26%
Conflicting data signals
Tools & offset factors
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 3.4% and rose by 0.3 points from last quarter.
- Hiring read: recruitment is running above resignation (1.2% vs 0.7%).
- Retrenchment was moderate at 2.6 per 1,000 employees.
- 69.1% of retrenched workers re-entered employment within 12 months.
- The postings snapshot is stale; its latest captured ad is dated 2026-03-19.
- Employer pressure is low, based on 2 captured Singapore-relevant company signals through 2025-06-18.
Worker profile
Gender mix
39% male / 61% femalePublished Singapore worker composition for the detailed occupation family 33 Business & Administration Associate Professionals.
Employment structure
Employee-heavy87% employees, 13% employers or self-employed workers.
Work arrangement
Mostly full-time9% part-time and 91% full-time in 2025.
Age profile
Mid-career heavy17% aged 15 to 29, 52% aged 30 to 49, and 31% aged 50 or older.
Qualification mix
Diploma-heavyDegree 37%; Diploma / professional qualification 35%.
Gross wage by sex
Near parityPublished June 2024 gross wage medians: male $5,500, female $5,330.
Where this work is concentrated
Top planning areas
Jurong West, Woodlands, Tampines22% 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 38.7 minutes. 36% 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.
General role profile on a 0–100 scale. These are modelling inputs, not measurements of an individual job or worker.
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 Financial markets back office administrator?
Financial markets back office administrator has an AI Exposure Rank of 99/100, meaning its work is more exposed to current AI capabilities than approximately 99% 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: 99/100 (Very High). Median wage: SGD 5,366/month.
What is the AI exposure rank for Financial markets back office administrator?
Financial markets back office administrator has an AI Exposure Rank of 99/100, rated Very High. It ranks higher than approximately 99% of Singapore occupations for exposure to current AI capabilities; it is not a job-loss probability.
What career transitions are available for Financial markets back office administrator?
Financial markets back office administrator 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 Financial markets back office administrator salary compare in the live market?
Financial markets back office administrator earns a median gross wage of SGD 5,366/month in the live market (25th-75th percentile: SGD 4,000-6,700). This is 19% above median across all 562 scored occupations, and 30% above group median within Associate Professionals & Technicians occupations.