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.
Geospatial projects in insurance and financial services face a number of challenges
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
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
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
- 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
Access high-resolution archive imagery or task satellites for a date range, guaranteeing high-quality, low cloud coverage imagery for your AOI.
Enhance image quality, convert input data, or clip raster images into tiles to ensure that your input image is ready for further analysis.
Process satellite data with object detection algorithms and forecast the risk of major water-related geohazards.
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