Fast company
world changing ideas
Upward Labs
Proptech
SBC
Fintech Australia
Rebny
Proptech challenge

for lenders, risk managers and property owners

Enhance credit quality
with location data

for lenders, risk managers and property owners

Enhance credit quality
with location data

Improve predictability of insurance risk models with location data

Hyperlocal data for real estate wordwide

Accurately determine value and risk of property locations. Access to actionable metrics tailored from hundreds of data sources.

Success stories

Using Habidatum automated solution, the bank dramatically increased the size of property selection funnel, approved multiple new properties and managed to reduce time for underwriting.
There's an ongoing collaboration to test Habidatum data in risk management and mitigation models, from underwriting to IoT, across 100s of thousands of properties.
We joined a task force focusing on the 'S' of ESG and impact investments into arts & culture, an initiative by Investitionsbank Berlin, Berlin Partner, visitBerlin and Leading Culture Destinations.

LENDING

INSURANCE

ESG

Regional Bank with Assets of $65 Billion
Hartford Steam Boiler
ESG Innovation Collective

Press coverage

Scoring billions of locations by mobility, spend and business diversity

Building
Neighbourhood
Trade area
City
Location data to
Banks
enhance underwriting quality
Asset managers
reduce asset portfolio risk of losing value
Insurance
improve loss prediction quality
Retailers
convert mobility into revenue
Transportation & Planning
support to masterplanning
Location data to
Banks
enhance underwriting quality
Asset managers
reduce asset portfolio risk of losing value
Insurance
improve predictability of insurance risk
Retailers
convert mobility into revenue
Transportation & Planning
support to masterplanning
Banks
Neighbourhood
Trade area
City

Why choose us?

Cleansed & normalized, checked for comparability and equalization

Data integrity

Scoring & Analytics

Out-of-the-box risk metrics and scores adaptible to your financial models
Engaging with clients to design solutions that best meet their needs

Collaboration, thought leadership

Easy to use automated reports, API, interactive dashboard, csv

Flexible delivery

Privacy-by-design database built in-house for secure highly granular data aggregation

GDPR compliant

Large inventory of vetted global data partners in GPS, mapping and telecom

Global coverage

FAQ

Our top references, materials and tips for you
What are the metrics?
Metrics underlying our industry-specific products include:
  • Statistically normalized foot traffic by 50m grid cells (with dwell time, amount of time people spend in a location: transit stops for 2 min and more, work and leisure activities for 3 h and more, as well as total activity - median crossers per day), updated monthly
  • Statistically normalized occupancy by building polygons, updated monthly
  • Location Risk Score (LRS) = [ Foot traffic * Density of Points of Interest (POI) ] within customizable accessible area, updated quarterly
  • You can see the full list of metrics and details on the core package in our Data Dictionary
  • USA and other countries are covered: contact us to find out more about a set of metrics for your country.

What are our data sources?
  • We collaborate with GPS data aggregators and telecoms to get mobility data and process it into statistically normalized metrics of footfall, occupancy and location risk.
  • We also source information on points of interest from online maps.
  • For statistical normalisation, filtering and validation we may apply Census data, satellite imagery and building footprint information.
  • We use travel time data (auto, transit, pedestrian) to define a relevant catchment area around each and every property, measure commercial potential of those areas, and then compare all areas employing a scoring mechanism.
  • Please contact us if you want to learn more about preferred data partnerships used to calculate your metrics.

What are the spatial units?
  • Foot traffic data is offered in a regular grid covering whole globe with a minimal cell side of 50 meters that can be aggregated to larger areas in real time.
  • There is also a metric showing foot traffic by building footprint boundaries helping differentiate between street traffic and building occupancy.
  • Location risk and local commercial potential metrics are calculated for neighborhood clusters defined by travel time data (accessible area isochrones).
All spatial units are comparable by their commercial risk metrics both on a national and global scale.
Is historical and current data available?
  • Foot traffic, property occupancy and dwell time data is updated on a monthly basis. Location Risk Score, travel time and POI metrics are updated quarterly.
  • History: we offer historical metrics for Pre-COVID (2019), Lockdown (2020) and End-to-Post-Lockdown periods (2020-2021).
  • Longer history of observations and higher-frequency updates are available on your request.

How is source data cleaned and normalized?
Before data is transformed into metrics, a set of data cleansing, validation, normalization and approximation processes is performed:
  • There are basic machine-readable format checks and anomaly detections performed by our automatic data pipelines.
  • The data is filtered using satellite and building/road/water footprint data to match with actual territory of interest.
  • Data validation checks are run with internal quality reports production.
  • Then, data normalization is carried out for making data comparable over time and geography.
For approximation, we apply wide historical samples as well as official Census data.
We guarantee quality of our metrics, and will be glad to share our validation results with you if required.
What is different in our approach?
  • Adaptability. Real estate properties do not move while everything around does → Scoring shows the most up-to-date situation, and allows seeing time delta
  • Relativity. You need to know not just where property is, but also where it is not → Scoring is relative to millions of comparable and target locations
  • Operability. Location data is rich; encyclopedic view on it, however, complicates decision making → We translate location data into financial benchmarks, proof points and signals of value and cap rate change
What are delivery formats?
  • Per location web reports to support underwriting quality. Web report with metrics tailor-made for specific applying and industries.
  • Per location data package via API. HTTP request to get a spreadsheet with metrics for your location. Read documentation
  • Full region data package via web dashboard. Access web dashboard with monthly updated data visualized on a map. About dashboard
  • Bulk CSV/Excel download can be provided on request and enterprise integrations.
Who are our customers?
  • We work with financial risk underwriters: appraisers, lenders, property owners, investors, insurers, reinsurers, and various types of asset networks both in the USA and internationally. Our current client base includes several Fortune 500 financial institutions. Habidatum powers Mastercard's global database and its visualization tool for real estate investors into opportunity zones: Inclusive Growth Score.
Our work has been recognised by the Real Estate Board of New York (REBNY), International Real Estate Federation, the World Bank Group, Intel, Fast Company's World Changing Ideas Awards.
What metrics also help to find out?
  • How your location compares with each and every location in your neighbourhood, city, region and nation
  • The amount of people who move and stop in and around your property
  • Pre and post COVID location mobility values with the recovery and growth rate over time
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