Bridging the SME reporting gap: A new model for predicting Scope 1 and 2 emissions

Abstract We present a novel statistical model for predicting Scope 1 and 2 emissions for small and medium‐sized enterprises (SMEs). Trained on financial transaction data from over 100,000 UK SMEs, the model targets a business segment excluded from formal emissions reporting and often under‐engaged in sustainability efforts. By leveraging scalable, objective data, our approach offers an accessible alternative to existing methods that rely on either coarse sectoral averages or detailed, resource‐intensive firm‐level activity data. In developing the model, we evaluate a range of predictors and find that incorporating industry‐level variables beyond basic emission intensity significantly enhances predictive accuracy. We also observe diminishing returns from additional model complexity, reinforcing the value of a parsimonious, low‐input design. The final model achieves RSQ values of 0.89 for Scope 1 and 0.72 for Scope 2, improves accuracy by up to 50% compared to sector‐level estimates, and performs reliably on out‐of‐sample data. Our findings provide a simpler approach to emissions estimation for SMEs, supporting broader climate engagement among smaller actors.