From origination to portfolio management, banks and mortgage lenders need accurate, consistent location data to value properties, score risk, and meet green product disclosure requirements. Neighbourly provides a structured API layer that integrates directly into lending platforms and AVM pipelines.
Neighbourly · Banking & LendingLending decisions need a defensible view of the property and its market. Assembling collateral, demographic and market context per address slows origination and adds risk.
Clean location data is load-bearing infrastructure for a lending platform. At origination, an address that doesn't resolve cleanly to a canonical form creates downstream data quality problems that compound through the life of the loan. In AVM workflows, neighbourhood context and permit history are signal inputs that most providers aren't yet using. For green mortgage products, energy efficiency data at the address level is becoming a regulatory expectation, not just a product differentiator.
Neighbourly addresses all three stages. Address standardization and geocoding at origination ensure every loan record is anchored to a clean, validated civic address with a consistent identifier. Neighbourhood boundaries, demographics, and permit data enrich AVM models with the contextual signals that pure transaction-based models miss. And energy efficiency scores — derived from building characteristics and EnerGuide data where available — support green mortgage qualification and mandatory disclosure requirements.
The API offers REST and GraphQL, returns clean JSON, and is designed to drop into existing origination and portfolio management workflows with minimal integration work.
The specific, production-grade capabilities behind banking on Neighbourly — not features on a slide, but data and tooling you can ship on.
Resolve a subject address into standardized components, boundary hierarchy, property characteristics and neighbourhood context in a single call, giving a loan file a complete collateral picture. The result is structured JSON ready to attach to a decision record.
Layer Forward Sortation Area demographics, Building Permits activity and Real Estate market context onto a property to inform valuation and credit models. Permit activity in particular acts as a forward-looking signal of neighbourhood investment.
Run an existing book of collateral addresses through the same enrichment pipeline on a schedule to detect shifts in market and neighbourhood conditions. Every re-run uses the identical schema, so period-over-period comparison is clean.
Attributes are returned as consistent JSON keyed to the standardized address, so they feed straight into automated decisioning without manual reconciliation. This keeps origination workflows fast and auditable.
Because every address is stitched to the same Country to Neighbourhood hierarchy, collateral in different cities can be compared on a consistent geographic basis. This underpins concentration and exposure analysis across the book.
Validate and normalize borrower and property addresses at application time to reduce downstream errors and duplicate collateral records. Clean intake data improves every model that consumes it later.
Property characteristics, boundaries and neighbourhood data for every address you underwrite.
Demographics, permit activity and neighbourhood trends for lending models.
Batch-enrich and re-check portfolios against current location data.
Feed clean, structured location attributes straight into credit workflows.
A consistent, standardized set of location attributes gives credit and audit teams a view of collateral they can stand behind.
Property and market context resolves automatically per address, removing manual research from the origination path.
Scheduled re-enrichment surfaces changing market conditions across the book without manual data pulls.
Canadian hosting and PIPEDA compliance align with the data-governance expectations of federally and provincially regulated lenders.
Use the data yourself, have us build the whole thing, or bring in our team for strategy and analysis — whatever fits how you work.
Wire standardized banking data straight into your product or workflow — REST and GraphQL, one key, Canada-wide.
Explore the API →No engineering team? We design and build the banking tool, dashboard or platform on our data — you bring the idea, we ship it.
Start a build →Strategy, enrichment, analytics and measurement from our team, so your banking data turns into decisions and results.
See our services →Hosted in Canadian data centres, end to end.
Privacy-first by default, with provincial compliance built in.
Every layer shares a spine, so data joins cleanly.
Live, maintained data — never stale snapshots.
Common questions about this data and how to use it.
To enrich origination workflows, AVM pipelines, and green-mortgage products with Canadian address-level neighbourhood and demographic data, plus energy data in Ontario.
Yes. Structured, address-resolvable data feeds directly into valuation and risk models.
Electricity, gas, and water consumption keyed to Ontario addresses, with more regions rolling out.
Through a single API with consistent, RESO-aligned fields — no GIS infrastructure required. Attributes come back as consistent JSON, ready to feed directly into automated decisioning and origination systems.
Standardized address and boundary data, property characteristics, neighbourhood demographics and permit activity together give lenders a defensible, consistent view of collateral and its market.
Yes — addresses can be enriched in batch with consistent location attributes for origination and ongoing portfolio monitoring.
Neighbourhood demographics, building-permit activity and market trends provide forward-looking signals to feed valuation and credit models.
Yes — portfolios can be re-enriched against current data to monitor changes in market and neighbourhood conditions.
Address & Geocoding, Demographics, Building Permits, Location Boundaries and Real Estate are the core layers for collateral and market context.
Yes. The same address-based enrichment runs at origination for a real-time collateral view and on a batch schedule during servicing, using an identical schema so results are directly comparable over time.
Neighbourly supplies the standardized location and market context around collateral rather than a formal valuation, so it complements appraisal by giving models consistent neighbourhood, demographic and permit inputs.
You call REST or GraphQL with one API key and receive consistent JSON, so most teams add a single enrichment step ahead of their credit decision without changing their core workflow.
Yes. If you prefer not to call the API in-line, our data services can enrich a portfolio file and return it in your schema, or a custom build can wrap the logic your credit team needs.
Yes, supporting data-residency and compliance requirements.
Tell us about your origination workflows, your AVM pipeline, and your green product roadmap. We'll show you what fits.