Identify and Evaluate Risk and Opportunity

Geospatial data and analytics can enable intelligent, data-driven investment decisions by identifying risks, trends, and opportunities.

Geospatial projects in insurance and financial services face a number of challenges

High-quality data requirements

High-quality data requirements

Geospatial financial analysis comes down to accurately identifying changes and predicting risk. To do this effectively, high-resolution optical and radar data is vital.

Many different variables

Many different variables

Asset values, market trends, and risks to financial and insurance portfolios can only be evaluated when a wide range of disparate variables are taken into account.

Data and insight integration

Data and insight integration

From satellite and aerial imagery to detection algorithms to map data, geospatial solutions in financial services must find a cohesive way to integrate insights into a single tool.


Insurance and Financial Services

Build geospatial products for financial services

Combine high-resolution optical, radar, and aerial imagery processed by cutting-edge algorithms to gain an edge as you assess risks, spot trends, and evaluate investment opportunities.

  • Access high-resolution commercial and open satellite imagery
  • Process your data with machine-learning algorithms
  • Export data and insights into your analytics platforms via API

Use case spotlight

Identify and mitigate risks across your financial portfolio

High-resolution imagery and weather data

Access high-resolution Sentinel-2 optical imagery for broad areas of interest. Augment analysis with 1000 historical and forecasted weather parameters.

Predict water-related geohazards

Use out-of-the-box machine learning algorithms processing Sentinel-2 data to predict flooding or exposure to water bodies for your areas of interest.

Gain a holistic view of portfolio risk

Combine weather and geohazard predictions with your own algorithms applied to high-resolution satellite data to get a full picture of your portfolio risk.


Additional Insurance and financial services use cases built with UP42


The building blocks for insurance and financial services solutions

High-resolution satellite data

High-resolution satellite data

Access high-resolution archive imagery or task satellites for a date range, guaranteeing high-quality, low cloud coverage imagery for your AOI.

Pre-processing algorithms

Pre-processing algorithms

Enhance image quality, convert input data, or clip raster images into tiles to ensure that your input image is ready for further analysis.

Machine-learning algorithms

Machine-learning algorithms

Process satellite data with object detection algorithms and forecast the risk of major water-related geohazards.

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