Spatial Intelligence for Financial Services

Hedge funds and investment firms cannot efficiently process massive satellite imagery, shipping data, and foot traffic datasets to generate alpha-generating signals, missing opportunities to predict earnings before public disclosure

Analyze petabytes of satellite imagery and geospatial alternative data extracting investment signals at planetary scale. E.g. retail parking lot traffic, agricultural crop health, or oil storage tank levels

Post-catastrophe response is too slow, taking days to assess exposure across affected areas while policyholders wait and losses mount

Accelerate catastrophe response to hours with distributed processing that analyzes millions of affected properties against event footprints in near real-time.

Investment managers lack the ability to spatially analyze how thousands of holdings are exposed to location-based risks such as natural disasters or socioeconomic factors. Limiting their ability to reduce risk in portfolios.

Integrate diverse geospatial datasets with portfolio holdings data to visualize and quantify location-based exposures, enabling data-driven rebalancing decisions and scenario analysis at scale.

Retail banks cannot efficiently analyze demographic shifts, competitor locations, and customer mobility patterns across thousands of locations, resulting in suboptimal retail location placement and resource allocation.

Process massive demographic, foot traffic, and transaction datasets to optimize branch networks, identify underserved markets, and forecast performance based on location-specific factors.