Assessing Climate-Related Flood Risk for Climate Adaptation in the Financial Sector: A Risk Assessment Framework for Future Flood Risk to Real-Estate
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Introduction Climatic change results in an increase in flooding, posing a threat to the world’s economic system. Especially real-estate assets are at risk. There is increasing demand for financially material climate-related risk information. While providers of this information exist, methodologies are proprietary, and results are divergent – indicating the need for a standardized flood risk assessment framework: How can financial institutions quantify the financial risk posed by flooding to their real-estate portfolios in future climate change scenarios? Theory The literature illustrates an increasing need for financial firms to understand their risk to climate change. Current guidance to climate risk assessment exists in the form of general recommendations. However, these are often too vague. At the same time, global coverage flood models exist that predict flood occurrence in future climate change scenarios. The research defines climate-related flood risk in financial and hydrological terms. Methods After defining climate-related flood risk in both a hydrologically sound and financially material manner, the relevant concepts are operationalized as variables. This includes a state-of-the-art global flood model is consulted, the Aqueduct Flood tool. This is applied to construct a global flood risk assessment framework that predicts flood risk in future climate change scenarios. Risk is expressed as Expected Annual Damage (EAD). Results are illustrated with the use of a representative case study: a sample of a real-estate portfolio owned by a Dutch pension fund investment manager. Results The flood risk assessment framework is summarized into three key steps: 1. defining the model parameters, 2. collecting flood risk data, and 3. identifying flood risk. Each step is illustrated with results from the case study. Flood risk may be identified by plotting total EAD along axes of scenarios and timeframes to understand how risk develops over time. Risk hotspots are identified using maps. Discussion The model’s degree of reliability and validity primarily relates to uncertainty in datasets. Moreover, model output cannot be validated as the data exist in the future. The utility of risk assessment for global financial stability and climate adaptation remains a topic of current debate. However, the value of the tool lies in increasing firm-level resilience to climate change by exposing hotspots. Conclusion The proposed framework may be used as a point of departure to model, understand, and manage future flood risk to real-estate. A standardized framework is expected to aid in firm resiliency to climate change and promoting global financial stability in uncertain climate futures.