Risk & Data Enrichment
A customer isn't just their transaction history. They're also where they live, what kind of neighbourhood, what average income, what mobility. That context improves any risk model.
What data enrichment for territorial scoring entails
Data enrichment for territorial scoring consists of adding geospatial variables — income, type of habitat, accessibility, mobility, housing typology — to credit risk, scoring and automated valuation models. These environmental variables explain behaviours that transactional data doesn't capture and improve the predictive capacity of any model.
unica360 carries out this enrichment with proprietary microterritorial data at postal address and 100m grid level for Europe and LATAM.
Data as a basis
We enrich your risk, scoring and valuation models with microterritorial environmental variables your database doesn't have:
income
type of habitat
probability of having children
housing type
mobility
building construction quality
Variables that explain behaviour and reduce uncertainty.
We do it at postal address or coordinate level, with coverage across the whole national territory and delivery in the format that integrates directly into your stack, via the microtarget enrichment API or batch dataset.
Applications
Credit scoring
We add environmental context to the applicant's profile. The same declared income has a different meaning in a high-centrality urban area than in a peripheral one.
Automated valuation (AVM)
We enrich each property with indicators of its environment: commercial, residential, tourist, green area access, pedestrian traffic.
Default prediction
The territory a customer lives in is a relevant predictive variable. We use it.
Insurance risk segmentation
Accident rates, theft, housing type, urban density. Environmental variables that improve pricing.
The data
The variables come from microtarget's territorial risk indicators
Average area income
Type of habitat
Housing typology and quality
Retail density
Mobility
Floating population
FAQ
What environmental variables improve a credit scoring model?
The most relevant are average area income, type of habitat (urban/peri-urban/rural), retail density, housing typology, owner-to-tenant ratio, and access to financial services. These variables correlate with payment behaviour and reduce model uncertainty.
How is unica360's enrichment integrated into my data stack?
Via API or through delivery of an enriched file.
Does unica360 have coverage across all of Europe and LATAM?
Yes. microtarget's microterritorial geodata covers 100% of Spanish territory at 100m grid level. We also have data for Portugal, Italy, France and Mexico, with LATAM coverage expanding.
Does the enrichment comply with GDPR?
The added variables are aggregated environmental data at 100m grid level, not third-party personal data: they don't incorporate individual or identifiable information into the model. We don't need you to hand over any personal or GDPR-scoped data.
Can I test the enrichment before integrating it?
Yes. It's common to run a pilot on a sample of your portfolio to measure the improvement in predictive capacity before industrialising the integration.
Does your scoring model account for territory?
Ours does. And we integrate it into yours.