This paper proposes a quantitative storm surge risk assessment method for data-deficient regions. A coupled model is used to simulate five storm surge scenarios. Deep learning is used to extract building footprints. Economic losses are calculated by combining adjusted depth–damage functions with inundation simulation results. Zoning maps illustrate risk levels based on economic losses, aiding in disaster prevention measures to reduce losses in coastal areas.