Top 10% wealth share
59.48%of household net wealth.
Germany · wealth → flow → outcome
Follow the money.
Who owns it? Where does public money go? Who still gets missed?
Show me →Bottom 50% wealth share
≈2.17%combined.
At risk of poverty · 2025
13.3mpeople · 16.1% of the population.
“Live” means latest public official data. No private bank accounts or real-time personal transactions.
01 · Wealth
10% own most of it. The bottom half owns very little.
100 household-percentile dots
Top 10%59.48%
Middle 40%≈38.35%
Bottom 50%≈2.17%
Derived insight
≈137×Average net wealth per household in the top decile versus the bottom half, derived from the ECB group shares.
·Total wealth · Q4 2025
≈€19.9tnThe issue is not that Germany has no wealth. It is how ownership and access are distributed.
02 · Compounding
The starting gap can reproduce itself.
Two different starting positions create two different return engines.
More assets
59.48%wealth share
→
Market assetsmore exposure
→
Positive real returntop 10% in Q1 2026
Bundesbank: average real financial-asset returns remained positive only for the wealthiest tenth in Q1 2026.
Fewer assets
≈2.17%wealth share
→
Deposits + insurancelarger role
→
Less exposureto market compounding
This describes group-level portfolio structure — not every individual household.
03 · Public money
Germany redistributes a lot. But “social budget” is not the same as “money to the poorest”.
37.62%BMAS share
of federal budget
of federal budget
Federal budget · 2026
€524.5bnTotal federal expenditure.
BMAS · 2026
€197.3bnIncludes pensions, social insurance and labour/social policy — not only poverty-targeted transfers.
04 · The leak
Sometimes the money exists. The intended person still does not receive it.
Participation benefit · analysed 6–14 group
≈82 / 100were not reached in the cited 2026 analysis, because take-up was only around 18% among eligible children in that group.
■ 18 reached■ ≈82 not reachedRouting failure, not proof of funding shortage
05 · What changes first?
Make every euro traceable to an outcome.
Priority 1
Route existing benefits automatically.
Where verified government data is already sufficient, identify likely eligibility, pre-fill the claim and ask only for what is missing.
Eligible→Detected→Pre-filled→Reached
Priority 2
Give every public euro a Distribution Score.
Do not stop at “€1bn spent”. Show who receives it, which income/wealth groups benefit, what outcome changes and what remains unknown.
€1→Recipient→Distribution→Outcome
Coverageeligible people actually reached
Bottom sharebenefit reaching lowest-income groups
Poverty effectmeasured gap reduction
Evidencesource + uncertainty behind every claim
Explore scale scenarios
10% of reported subsidy envelope
Arithmetic scale only — not a recommendation.
€7.78bn/year≈ €48.75/month per person currently at risk of poverty
Illustrative share of top-decile wealth
This is not a tax proposal or revenue forecast.
≈ €11.84bn/year≈ €74.18/month per person currently at risk of poverty
Scale ≠ outcome. Real reform modelling must include thresholds, behaviour, avoidance, household composition, work incentives, legal constraints and programme interactions.
Next experiment
Pick one benefit. Map every eligible person to the money they actually receive.
Eligible → reached → missed → euro gap → reason → smallest fix. That turns the Atlas from an inequality dashboard into a distribution-improvement system.