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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 = License & Compliance × 40% + Complaints × 35% + Business Profile × 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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MMMB ENTERPRISES INC scores 762 — these providers rank higher on Verdica's composite trust score.
The Verdica score is a composite trust score from 300 to 850, computed from state license records, consumer complaints, and HUD enforcement maintained by state licensing commissions, the CFPB, and HUD. A score of 762 places MMMB ENTERPRISES INC 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 state licensing commissions, the CFPB, and HUD. Each sub-score reflects a different dimension of real estate compliance — license standing, disciplinary history, and complaint outcomes — and is normalized against industry peers before being aggregated to the 300–850 scale.
Verdica pulls public records from state licensing commissions, the CFPB, and HUD: state license records, consumer complaints, and HUD enforcement. 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 license suspensions, unresolved complaints, or HUD enforcement actions. 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.