This study develops a conceptual framework that uses active learning to accelerate compound flood risk assessments. A case study of Charleston County shows that the framework achieves faster and more accurate risk quantification compared to the state-of-the-art. This win–win allows for an increase in the number of flooding parameters, which results in an 11.6 % difference in the expected annual damages. Therefore, this framework allows for more comprehensive compound flood risk assessments.