The team at Roko Labs designed and implemented a robust, end-to-end data pipeline that unified, enriched, and operationalized ESG risk data across Moody’s global footprint. The solution began with integrating enterprise and location data to establish a clear and consistent mapping between companies and their physical assets. By connecting internal datasets and resolving corporate hierarchies, the system created a reliable foundation for location-level ESG analysis. Building on this foundation, external financial and market data was incorporated to provide additional context. This enrichment ensured that ESG risk signals could be analyzed alongside financial performance, strengthening the relevance of the insights for credit evaluation. A key component of the solution was the development of a scalable input pipeline for the ESG scoring API. This pipeline standardized and normalized data from multiple sources, preparing it for consumption by third-party models. It enabled Moody’s to incorporate a wide range of environmental and geopolitical risk factors, including climate exposure, extreme weather events, and regional instability. To support reliability and transparency, the entire data flow was orchestrated through a structured cloud architecture. Data was processed through layered stages - from raw ingestion to refined, analytics-ready datasets - ensuring consistency, traceability, and auditability at every step.