Sea level rise exacerbates flood risk for coastal communities globally. Multiple studies have shown that significant property values are already at risk this century, especially in high-emission scenarios. Thus, sea level rise poses major challenges that cannot be effectively addressed by many existing flood risk management methods. Some challenges include managing uncertainties, time dependence, and the interplay between mean sea level rise and extremes. Here, these components are integrated into a joint probabilistic framework, with the novelty of the approach being the direct connection of these factors to economic risk. The resulting framework provides a probabilistic assessment of flooding loss conditioned on user-defined emission scenario probabilities. The framework fits well as a tool for risk assessment, uncertainty quantification, and decision support. A major takeaway is that the risk increase accelerates with warming. Another takeaway is that the objectivity of flood risk assessments decreases significantly with increasing assessment length, with flood risk becoming more dependent on mean sea level change. The framework requires only readily available data and an open source model, enabling better-informed risk assessments through improved data utilization. The framework is validated using data from Kalmar city, one of Sweden’s oldest cities, located in the south and known for its rich cultural heritage.