Data & Information Sources

~9 min read · Vet MLS, public records and third-party data before they enter the workfile.

Modern appraisal runs on data pipelines — MLS, public records, listing portals, cost services, market surveys — and the appraiser's professional duty is source vetting: know each source's biases, verify what matters, and never let convenient data replace confirmed data.

The source inventory

MLS: richest transaction detail (concessions, DOM, remarks) but agent-entered — square footage and features need verification. Public records: authoritative for legal description, transfers, taxes; often stale or wrong on physical characteristics. Listing portals and AVming sites: broad coverage, consumer-grade accuracy — their 'estimates' are not comps. Cost services (published manuals): benchmarked construction costs, localized by multipliers. Surveys and market reports: cap rates, vacancy, absorption. Interviews — agents, parties, managers — remain the verification backbone.

  • MLS: detailed, agent-entered — verify the load-bearing facts
  • Public records: legal-authoritative, physically unreliable
  • Portal estimates are marketing, not evidence
  • Interviews convert data into verified data

Vetting discipline

For each source ask: who entered it, with what incentive, when, and how is it audited? Cross-check load-bearing facts across two independent sources (MLS GLA vs assessor sketch vs your measurement); prefer primary over derivative (the deed over the portal's transfer line); date-stamp everything (cap-rate surveys age fast). USPAP hooks: data quality is part of scope of work, and relying on unverified data where verification was warranted is a credibility failure.

  • Source, incentive, vintage, audit trail
  • Two independent checks on decisive facts
  • Primary sources outrank derivatives

New pipelines

Aerial and street-level imagery, GIS layers (flood, zoning, parcels), permit databases, and property-data APIs extend reach — excellent for screening and condition clues, with known limits: imagery vintage, GIS layer errors, permit lag. The appropriate-use rule: new sources ADD coverage; they inherit the same vetting duty, and their limitations are disclosed when they matter.

Worked example

A comp's MLS entry claims 2,400 sq ft and 'full renovation 2024'; the assessor shows 2,080 sq ft; street imagery from 2023 shows a pre-renovation facade. The sale price supports the appraiser's value nicely at the MLS square footage. How does a disciplined appraiser proceed?

The 320 sq ft discrepancy is load-bearing — at ~$150/sq ft it moves the comp analysis ±$48,000. Vetting: MLS is agent-entered (incentive: bigger sounds better; possibly includes a non-permitted addition or below-grade space); the assessor sketch is often stale but measurement-based; 2023 imagery predates the claimed renovation, proving nothing either way. The move: verify — pull the permit record for the addition/renovation, call the listing agent to ask how GLA was measured, check the appraisal-era sketch if available. If the addition is permitted and above-grade, the MLS figure stands (and the assessor is stale); if it is a converted garage or basement, the comp's effective GLA changes and so does its adjusted price. What is NOT permitted: keeping the convenient number because it flatters the value.

Common exam pitfalls

Treating MLS fields as verified facts.

Agent-entered data needs confirmation whenever it is load-bearing — GLA, concessions, condition claims.

Citing portal estimates as market evidence.

Algorithmic consumer estimates are neither comps nor support — use the underlying verified transactions.

Ignoring data vintage.

Imagery, surveys, and records carry dates — stale data describes a market that no longer exists.

Who typed it, why, and when — check twice where the dollars ride, and let the primary source win.

Recap

  • Know each source's entry path, incentive, and vintage
  • MLS detailed but agent-entered; records legal-authoritative but stale
  • Cross-check decisive facts across independent sources
  • Interviews remain the verification backbone
  • New pipelines (imagery, GIS, permits) extend reach, inherit vetting
  • Data quality is a scope-of-work and credibility issue

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