Methodology
How Financial Risk Score v1 is built
FinancialRiskIQ measures location-level financial pressure using public, defensible data. The methodology is built for clarity: explainable drivers, consistent scoring, and transparent updates.
Version
Financial Risk Score v1
A five-risk composite designed to compare locations, not people.
Core promise
Scores stay relative, explainable, and comparable across geographies. We avoid advice, personal recommendations, and promised outcomes.
Score construction
From public data to a composite score
This methodology emphasizes transparency over complexity. Each step is documented and aligned to location-level comparisons.
Collect public, aggregated data
Use location-level datasets that describe income stability, cost pressure, debt exposure, and legal context.
Normalize for fair comparison
Convert raw measures into comparable indices or percentiles across geographies.
Score each risk area
Compute risk scores to reflect the local intensity of each driver.
Blend into a composite score
Combine risks into Financial Risk Score v1 and publish the drivers alongside it.
Scoring mechanics
The exact scoring logic used in v1
Peer scope
Each metric is ranked against the same geography scope: city, county, metro, or state.
Directional normalization
Metrics where higher is better (income, earnings, participation) are inverted so higher always means more risk pressure.
Risk score rule
Each risk score is the average of metric risk percentiles for available core metrics (minimum 2 metrics required).
Composite rule
Financial Risk Score v1 is the average of available risk scores for that location.
Formula reference
metric_percentile = percentile_rank(metric_value, peer_scope_distribution) metric_risk = higher_is_better ? (100 - metric_percentile) : metric_percentile risk_score = mean(metric_risk for available core metrics), min 2 metrics overall_score = mean(available risk_scores)
Risk framework
Five risks, each explainable
Household financial stress
Baseline fragility signals tied to income, savings resilience, and cost burden.
Debt and credit pressure
Leverage, utilization, and credit vulnerability signals that elevate risk.
Cost of living exposure
Housing costs and rent growth that erode purchasing power.
Legal and collection risk
Civil court activity and enforcement intensity that signal collection pressure.
Employment and income stability
Exposure to job volatility, earnings softness, and income shocks.
Metric reference
Risk-by-risk metric table
| Risk | Core metrics in v1 |
|---|---|
| Household financial stress | Median household income | Households under 200% poverty | Rent-burdened households (30%+) | Mortgage-burdened households (30%+) | Households receiving SNAP | Income trend (YoY) |
| Debt and credit pressure | Subprime share (score < 620) | 90+ day delinquency rate | Revolving utilization (75%+) | Total debt per borrower |
| Cost of living exposure | Median gross rent | Median home value | Median monthly housing costs | Rent as % of household income | Rent growth (YoY) |
| Employment and income stability | Unemployment rate | Unemployment volatility (12-mo) | Labor force participation | Employment rate (16+) | Median earnings (full-time, year-round) | Earnings trend (YoY) | Industry concentration (HHI) |
| Legal and collection risk | Civil filings per 100k residents | Civil filings trend (YoY) |
Scoring rules
Guardrails that keep the score trustworthy
Relative, not absolute
Scores represent indexed or percentile-based comparisons, not absolute predictions.
Explainable by design
Every score includes a clear why and the underlying drivers.
Comparable across locations
Methodology is consistent so geographies can be compared fairly.
Versioned and documented
Each release is labeled (Financial Risk Score v1) to preserve transparency.
Presentation rules
- Scores are tied to geography, not individuals.
- Neutral, diagnostic language only.
- No guarantees, promises, or outcome predictions.
- Sources and data years are disclosed on each page.
Data transparency
Data sources, data years, and the specific drivers behind each score are disclosed on every location page. If a dataset is missing for a location, we label it clearly.
FinancialRiskIQ does not provide financial advice, lending offers, or debt relief services.