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Excellent · Verdica composite score based on three weighted sub-scores from public regulator data.
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0 sources need reviewHow this is calculated
Composite = Accreditation × 40% + Student Outcomes × 35% + Compliance × 25%, scaled to 300–850.Read full methodology →
Each sub-score starts at a baseline and adjusts based on real regulatory-record signals. Zero-delta rows show what we checked and confirmed clean. “Data quality” indicates how much source data informed the score.
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University of New Haven scores 750 — these providers rank higher on Verdica's composite trust score.
The Verdica score is a composite trust score from 300 to 850, computed from accreditation status, Title IV outcomes, and IPEDS data maintained by accreditors and the Department of Education. A score of 750 places University of New Haven in CT in the strong (740–799) band. The score reflects publicly available regulator data — it is not a rating from Verdica itself and does not incorporate paid reviews or advertising.
Verdica combines three weighted sub-scores drawn from accreditors and the Department of Education. Each sub-score reflects a different dimension of education compliance — accreditation standing, graduation and default rates, and financial responsibility — and is normalized against industry peers before being aggregated to the 300–850 scale.
Verdica pulls public records from accreditors and the Department of Education: accreditation status, Title IV outcomes, and IPEDS data. Data is refreshed on rolling cycles, typically weekly to monthly depending on the source agency's own update schedule. See the "source data current" indicator on the entity page for the last successful refresh.
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Common negative signals include loss of accreditation, high default rates, or heightened cash monitoring. Any of these appear in the underlying regulator records and pull the sub-score down; the composite reflects the weighted impact.
Yes. Entities can file a dispute directly from the score page, and business owners can claim their profile. Verdica reviews disputes against the underlying regulator record; the score is updated when the source data is corrected. Scores are recomputed automatically as new regulator data arrives.