How RetirementRiskIQ builds a location-aware retirement risk score
What goes into the score, how we normalize across states and cities, and why we avoid false precision.
Key takeaways
- • We blend SSA life tables, BLS, BEA RPP, BLS LAUS, tax data, and county-level inputs where available.
- • Scores are relative by location, not predictions; they surface pressure points for planning.
- • We never sell advice; data is public, defensible, and normalized for fair comparisons.
Deep dive
RetirementRiskIQ is a location-aware diagnostic, not a generic calculator. We normalize public, defensible data (SSA life tables, BEA RPP, BLS LAUS, state tax rules) into relative scores so you can compare locations without false precision.
Scores are directional and update as new data ingests publish. We prioritize transparency: which signals we use, how we normalize them, and how they flow into composite risk and pillar scores.
Signals we consider
- • Signals are relative by state/city, not predictions of your outcome.
- • Public sources only; no black-box vendor data or scraped leads.
- • Normalization favors fairness and readability over opaque modeling.
How this affects you
These signals feed directly into the RetirementRiskIQ score. They are relative to other states and cities, using public, defensible data. No advice or sales—just context so you can make informed decisions and test scenarios in the assessment.
FAQs
- Do scores change over time? — Yes. When SSA, BEA, BLS, or tax datasets refresh, location adjustments and pillar scores update automatically.
- Is this investment or tax advice? — No. It is educational context using public data. You decide what to do next.
- Why location-first? — Most retirement risks are amplified or dampened by where you live—cost pressure, tax drag, healthcare/LTC costs, housing/insurance, and longevity deltas.