Alternative data analytics specialist QuantCube Technology today announced its Asset Mapping database, designed to fill the data gap facing banks, insurance companies, asset managers and corporates as they seek to monitor the risk exposure of the physical assets they own and invest in.
The solution enables firms to understand the exposure of their investment portfolios to environmental, social and governance (ESG) risks at a granular level and to address the European Banking Authority’s Pillar 3 disclosures on ESG risk – due to be reported in early 2025.
QuantCube uses advanced computer vision and big data analytics to mine alternative data sources including satellite and geolocation data, providing detailed insights into companies' physical asset portfolios. The database covers both direct and indirect asset ownership, tracking more than 1 million physical assets owned by more than 10,000 companies globally. It enables financial institutions to understand the importance of each asset in an organisation’s portfolio, including where its production facilities are based, and the physical risk of its assets being impacted by climate and environmental events.
Alice Froidevaux, Director of Product Development and CFA ESG at QuantCube Technology, commented: “With the newly introduced Asset Mapping solution, users can access precise data on the location of companies' physical assets. The database also provides a clear understanding of ownership structures through comprehensive analysis of both listed and non-listed companies. Combined with granular insights from satellite imagery and geolocation analysis, the Asset Mapping database significantly enhances the ability to monitor portfolio risk exposure, particularly from a macroeconomic and ESG perspective.”
The QuantCube Asset Mapping database covers companies globally across 11 key sectors: metals & mining, oil & gas, utilities, automotive, construction materials, real estate, chemicals, transportation services, telecommunications, food & beverage, and electronics. ¬¬¬Using Natural Language Processing (NLP) and robust graph theory to standardize and curate different kinds of raw and unstructured data related to companies and their assets, QuantCube ensures data accuracy and completeness, providing precise information on asset location, ownership structure and related activity.
The database provides a detailed 3D view of buildings, including height and surface area, and a precise geolocation that can be cross-referenced with meteorological data. As a result, asset owners and investors can evaluate the risk to each building in relation to extreme climate events such as droughts, floods or wildfires. By applying physical risk models at the asset level and aggregating the results at the firm level, QuantCube’s methodology ensures that the results are comparable between assets and between firms.