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Workflow example • Bulk • Institutional

Bulk portfolio screening with geo-risk evidence

When you’re underwriting or servicing thousands of properties, a single AVM isn’t enough — and unstructured “notes” don’t survive handoffs. This workflow shows how teams use AVMLens to generate export-ready valuation signals and risk evidence.

The goal

Produce a consistent CSV output per address: consensus value + confidence, geo adjustments, flood/EPA flags, and selected records & rental fields (where available) — without breaking when a field is missing.

Inputs

CSV file with at least an address column (city/state/zip optional).
Optional identifiers (loan number, property_id, etc.) carried through to the output for joins.

Process

Upload CSV → choose analysis tier (AVMs-only vs Tier 2 geo/risk).
For each property, AVMLens attempts up to 11 AVM sources and computes a consensus with variance/confidence.
Geo layers add evidence and scoring (FEMA NFHL flood zone + risk; EPA layers; distance scoring for highways/rail/transmission/cell towers).
Selected records & rental estimates populate when a match is available.

Outputs

CSV results with stable column order and blank cells when data is absent.
Per-property lookup id that can be used to fetch PDF reports or troubleshoot edge cases.

Why this works

Schema discipline: missing fields become blank — the row still writes and downstream tools don’t break.
Explainability: geo factors provide “why” behind adjustments, not just a number.
Coverage reality: values and records vary by market; the workflow assumes gaps and stays robust.

Next step

If you share a sample CSV (sanitized) and target geographies, we’ll tailor a demo around your schema and show exactly which fields populate reliably for your markets.

Book a demo View sample PDF