RS Metrics announced this week that it is making asset-level ESG data accessible in real-time to investors and customers by making ESGSignals solution available on Cloud marketplace.
ESGSignals provides over 100 analysis ready metrics such as biodiversity, greenhouse gas emisions, water stress, land usage and physical risks.
Independent insight is essential as there is increased skepticism in self-reported company disclosures. Typically self-reported data, in addition to being incomplete, lacks asset level detail crucial for investors.
ESGSignals will be available on Google Cloud Marketplace and includes a native solution for asset managers, personal wealth managers and rating agencies. As ESG continues to mature and investment flows continue, the market is looking at independent data that is easy to retrieve in real-time. Customers will be able to upload their own geolocated assets.
“Cloud technologies that help companies assess and track metrics important to their sustainability goals have become increasingly important for both business planning and meeting external commitments,” said Dai Vu, Managing Director, Marketplace & ISV GTM Programs, Google Cloud. “With the coming availability of ESGSignals® on Google Cloud Marketplace, RS Metrics is demonstrating its commitment to providing customers with the technologies they need to make data-driven decisions with critical ESG data.”
Maneesh Sagar, Chairman and CEO was recently interviewed by Banking Exchange in its offices, and was asked about the initiative, and why it matters to financial institutions. He said, “We have been focused on developing ESGSignals® and this partnership with Google Cloud marks a major milestone in democratizing ECP data by offering ESGSignals® as a SaaS, with rapid configuration by Google Cloud developers. This allows end users to create rapidly deployable dashboards and applications for financial services, rating agencies, assurance companies, and corporates and provide here-to unavailable ECP insights.”
RS Metrics’ proprietary, patented technology platform leverages advanced computer vision and machine learning, and a scaled QC workflow to generate accurate, predictive, and consumable information.