Raw Risk Datasets
The Global Risks Alliance (GRA) offers comprehensive and interoperable raw risk data product suite—engineered for institutional AI/ML pipelines, ESG disclosure systems, financial risk modeling, climate stress testing, and open-source innovation. Built to meet the demands of asset managers, insurers, regulators, research labs, and sovereign risk actors, GRA’s raw datasets are curated from authoritative global sources, spanning satellite, actuarial, financial, environmental, cyber, geopolitical, and health domains.
Spanning over four decades of spatially and temporally indexed intelligence—from 1984 to present—our raw data layers are sourced from ESA, UN systems, IMF/WB registries, capital markets, public health observatories, and planetary-scale sensors. Datasets are delivered in machine-readable, schema-linked formats optimized for training large language models (LLMs), risk classifiers, generative AI systems, simulation engines, and advanced econometric applications.
Key Domains Covered:
- Earth Observation (EO): raw satellite bands, SAR, multispectral, NDVI, DEMs
- Environmental & Climate: GHG concentrations, emissions, land cover change, deforestation
- Financial & Economic: historical markets, sovereign bond curves, trade flows, credit events
- Actuarial & Insurance: claims registries, catastrophe models, parametric triggers
- Cyber & Digital: breach reports, DNS/SSL records, threat vectors, dark web signals
- Health & Pandemic: morbidity data, epidemic curves, surveillance reports
- Geopolitical & Social: protests, conflicts, migration, legal filings
- IoT & Industrial: sensor telemetry, anomaly logs, utility load curves
- AI Trace & Model Data: raw training corpora, output logs, annotation datasets
All raw data layers are accessible via secure API endpoints, cloud-hosted data lakes, and direct download bundles, with tiered access licenses for public, research, and commercial use. Metadata includes full provenance, uncertainty bounds, regulatory classifications, and applicable sectoral standards (e.g. IFRS, Basel III, SFDR, TCFD, NGFS, and national ESG mandates).
Whether training advanced AI systems, testing macroprudential scenarios, or building predictive models for sovereign risk portfolios, GRA’s raw risk data library provides the foundational building blocks for future-proof resilience modeling, financial decision systems, and trusted governance tools.
Multi-domain raw datasets (1984–present) from ESA, IMF, UN, markets, satellites, insurers, and public observatories with spatio-temporal tagging and compliance metadata
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Strategy
Centralized access to decentralized risk signals—legal-grade raw data pipelines for innovation, supervision, and capital foresight
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Design
Standards-linked, zero-trust-ready, machine-readable, multi-sector input-grade data architecture
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Client
Asset managers, AI labs, insurers, regulators, universities, sovereign funds, think tanks, and financial analysts