Finance Manager
Estimated AI exposure rank
27/100
Estimated range 15–39/100
Oversees financial operations, reporting, and strategic financial planning
Finance Manager has an estimated AI Exposure Rank of 27/100, near the 28th percentile. It is a synthetic blend of 3 occupations, not a job-loss probability.
Relative AI exposure, not a prediction of job loss. Hiring, wages and role design depend on many forces that this estimate does not forecast.
Limited current buffers in the supporting context.
Why This Score
85% of tasks overlap with current AI
49% human advantage from judgment & presence
51% demand buffer from the local labour market
AI usage 3pp below theoretical exposure
On the Shortage Occupation List & Jobs in Demand list — government recognises hiring need
These factors interact with each other — the final score is not a simple sum of these bars.
Blended across 3 occupations using the same score logic as an occupation page. How this works
Tasks AI can handle
Financial modeling, data extraction from filings, ratio analysis, report generation, transaction categorization, and regulatory document summarization.
Where humans stay essential
Judgment on risk vs. return, client advisory relationships, regulatory interpretation in edge cases, fraud detection in novel scenarios, and strategic capital allocation.
Skills to focus on
Role profile
Heuristic workflow context blended from related occupations. This profile helps interpret the score; it is not a direct role-level measurement and is not part of the core net-risk formula.
Workflow dimensions (0 = low, 1 = high)
Singapore Now
Use these signals as directional context from closely related occupations and recent postings.
Observed hiring
0
30-day postings · no_signal
Employer signals
low
6 recent signals
Local support
1
blended context anchors
Top Industries
How this changes by career stage
What You Can Do
This estimated role shows some offset potential, but it depends on demand and transition pathways holding up across the blended occupation set.
Published transition support
Component occupation pathways
Explore each occupation for seniority and labour-market detailCompare with similar roles or occupations
Compare with... →Built From
Augmentation
Low (21%)
Dispersion
6.8pp spread · 15/100–39/100 range
Raw Scores
Exp 0.851 · Bot 0.494 · Mkt 0.514
Percentile Rank
More exposed than approximately 28% of occupations
Common tools in similar work
Blended from O*NET matches across 1 component occupations.
What helps
- A meaningful share of the work can likely be reorganized around AI rather than removed outright.
What could slow it down
- Current demand support is thin, so offsets may take longer to show up.
Worker profile
Gender mix
45% male / 55% femalePublished Singapore worker composition for blended detailed occupation-family anchors.
Employment structure
Employee-heavy89% employees, 11% employers or self-employed workers.
Work arrangement
Mostly full-time3% part-time and 97% full-time in 2025.
Age profile
Mid-career heavy9% aged 15 to 29, 60% aged 30 to 49, and 30% aged 50 or older.
Qualification mix
Degree-heavyDegree 78%; Diploma / professional qualification 15%.
Where this work is concentrated
Top planning areas
Bedok, Sengkang, Tampines20% of the blended underlying occupation families live across these three planning areas.
Residential concentration
Broadly distributed30% live across the top five planning areas in the weighted occupation blend.
Commute pattern
Mid-range commutesWeighted average commute 35.3 minutes. 28% take 46 minutes or more.
Local context & support
Market detail
Industry vacancy overlays use the latest published detailed cross-tab, which can lag the main labour monitor.
- Vacancy rate is 3.1% and was essentially flat versus last quarter.
- Hiring read: recruitment is running above resignation (1.5% vs 0.9%).
- Retrenchment was low at 1.5 per 1,000 employees.
- 67.7% of retrenched workers re-entered employment within 12 months.
- Employer pressure is low, based on 6 recent Singapore-relevant company signals.
Frequently asked questions
Will AI replace Finance Manager?
Finance Manager has an estimated AI Exposure Rank of 27/100, near the 28th percentile. It is a synthetic blend of 3 occupations, not a job-loss probability. Estimated AI exposure rank: 27/100 (Moderate).
What is the AI exposure rank for Finance Manager?
Finance Manager has an estimated relative AI Exposure Rank of 27/100, rated Moderate. This is a synthetic relative estimate blending 3 official occupations in Singapore, not a job-loss probability.
What occupations make up the Finance Manager estimate?
Finance Manager is estimated from 3 official occupations in Singapore: Budgeting and financial accounting manager (including financial controller) (40%), Accountant (excluding tax accountant) (30%), Financial analyst (e.g. equities analyst, credit analyst, investment research analyst) (30%).