AI Income Risk · Real Estate
Päijät-Häme
ProofIndex score 61/100 (High Risk) · medium confidence
ProofIndex score: 61/100 — High Risk risk.
Scoring period 2026-Q2 · medium confidence in the underlying data
Päijät-Häme (Finland) ranks among the higher-risk markets ProofIndex tracks, with a ProofIndex score of 61/100 (High Risk). The biggest contributor is housing leverage — how leveraged local mortgage borrowers are — loan-to-value, debt-to-income, and price-to-income.
Key risk drivers
- Housing Leverage — 80/100
- How leveraged local mortgage borrowers are — loan-to-value, debt-to-income, and price-to-income.
- Employment Vulnerability — 63/100
- How exposed local jobs are to AI automation, based on the area’s occupation mix.
- Income Concentration — 29/100
- How concentrated local income is in higher-paid, AI-exposed work.
- Resilience Factors — 21/100
- Local economic cushioning — savings, benefits, and job diversity that absorb an income shock.
Where this score comes from
Every ProofIndex pillar is computed from published statistics. These are the sources behind this area's score, with the vintage of each and the limitation we know about it.
- Employment Vulnerability — Statistics Finland — StatFin
- Finnish occupation register · Official statistics · Maakunta · vintage 2023. Direct occupation structure at maakunta level; seutukunta reports may inherit adjusted parent-region mix.
- Income Concentration — Statistics Finland — StatFin
- Finnish income statistics · Official statistics · Seutukunta · vintage 2024. Direct income series at seutukunta level.
- Housing Leverage — Statistics Finland — StatFin
- Finnish property prices · Official statistics · Municipality / seutukunta · vintage 2025. Municipality prices are aggregated to seutukunta where population-weighted coverage is sufficient; remaining areas use derived regional housing estimates.
- Rental Market Exposure — Statistics Finland — StatFin
- Finnish property prices · Official statistics · Municipality / seutukunta · vintage 2025. Municipality prices are aggregated to seutukunta where population-weighted coverage is sufficient; remaining areas use derived regional housing estimates.
- Resilience Factors — Statistics Finland
- Finnish official regional indicators · Official statistics · Maakunta / seutukunta · vintage 2024-2025. Official StatFin series; some seutukunta values use derived transformations where direct series are unavailable.
Frequently asked questions
Is Päijät-Häme at risk from AI job losses?
Relative to other Finland markets, yes — Päijät-Häme ranks among the higher-risk markets ProofIndex tracks. It scores 61/100 (High Risk) overall, and 63/100 on employment vulnerability — how much of the local occupation mix overlaps with work today’s AI can already do. ProofIndex measures how exposed local incomes are, not how many jobs will go: a higher score means more of the local wage base sits in work that AI is changing.
How exposed is the Päijät-Häme housing market to AI automation?
Päijät-Häme scores 61/100 (High Risk) on ProofIndex, which blends how exposed local incomes are to AI with how leveraged the local housing market is. The largest single contributor is housing leverage at 80/100 — how leveraged local mortgage borrowers are — loan-to-value, debt-to-income, and price-to-income. Housing leverage — loan-to-value, debt-to-income, and price-to-income among local borrowers — scores 80/100. Local resilience — savings, benefits, and job diversity that absorb an income shock — scores 21/100 and pulls the composite down. Scores are normalized 0–100 within Finland, so this ranks Päijät-Häme against other Finland markets rather than against markets abroad.
Why is Päijät-Häme rated High Risk?
High Risk is the risk tier ProofIndex assigns to a composite score of 61/100. The composite weights employment vulnerability at 35%, income concentration at 25%, housing leverage at 25%, and subtracts local resilience at 15%. For Päijät-Häme the risk pillars rank housing leverage 80/100, employment vulnerability 63/100, income concentration 29/100. Confidence in the underlying data for this area is medium.
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