Finance
Alternative public-web data for research, risk and diligence
Financial institutions increasingly rely on alternative data to sharpen research and monitor risk between reporting cycles. The public web — company sites, public filings interfaces, job boards, marketplace pricing, app ecosystems — carries early evidence of operational change long before it reaches standardized datasets.
Heroku structures those signals with the discipline finance requires: documented methodology, point-in-time correctness for backtesting, and quality metrics that make the data defensible in investment-committee and model-risk contexts.
What teams actually do with this
Company activity monitoring
Track public web footprint changes for coverage universes — site structure, product pages, public communications.
Point-in-time datasets
Observation-timestamped history designed for backtesting without look-ahead contamination.
Category demand proxies
Pricing and availability trends in relevant consumer categories as leading indicators.
Due-diligence support
Structured public-web assessments of target companies' digital commercial footprint.
The observation layer
Where teams start
Most finance programs begin with monitoring and intelligence, then add delivery into internal systems.
Public-web intelligence for finance
Tell us the decisions your team is making this quarter. We'll map the signals that inform them — feasibility first.
1 comment
Point-in-time correctness gets a paragraph here and a whole chapter in our model-risk policy. Nice to see a vendor treat it as a feature.