As double materiality gains prominence in sustainable finance, financial institutions increasingly require reliable climate data to assess their environmental impact and transition risks. Existing datasets overlook Small and Medium Enterprises (SMEs), contributing to 63% of emissions in the European Union. This paper introduces a method to generate climate indicators for SMEs, addressing this data gap. The approach requires only basic firm inputs—products,
business type, and location—without needing sustainability expertise, ensuring SME suitability. Two firm-level indicators, the Relative Emission Reduction Potential and Transition Risk, are derived by integrating product-level Life Cycle Assessment (LCA) data with climate scenario models. We showcase a dataset of about 50,000 firms applying our method and code, demonstrating the method’s scalability. The product-level granularity enhances SME coverage beyond industry averages, while the methodology’s transparency fosters trust in Environmental, Social and Governance (ESG) reporting. A key limitation is the focus on climate, which restricts its applicability to the environmental (E) dimension of ESG. However, LCA data support the future inclusion of broader environmental indicators. Practical implications: Granular, scalable climate indicators for SMEs enable double materiality assessments without direct outreach, especially for financial institutions with large SME portfolios. The data allows financial institutions to identify SMEs with high emission reduction potential or transition risk based on products. Since SMEs are the backbone of our European economy, such targeted approaches are crucial for adequate transition financing. To the best of the author’s knowledge, they are the first to develop a transparent method for constructing climate indicators for SMEs at scale.
