Risk measures are tools that enable consistent measurement of financial risk and quantify the risk exposure to an associated hazard. In finance, there is a broad spectrum of risk measures which reflect different asset performance goals and the risk appetite of the decision-maker. In this study, the authors leverage advancements in financial risk management to examine the role of risk measures to quantify the seismically induced financial risk, measure the benefit of seismic upgrading, and relate the benefit of seismic risk reduction to a degree of the implemented seismic upgrade. The findings demonstrate that the relation between the financial benefits of a seismic upgrade, quantified using risk measures that consider the full range of earthquake events, and the degree of the seismic upgrade are concave, that is, the incremental financial benefit reduces gradually with increasing degree of seismic upgrading. The opposite holds if the risk measures consider only the high-severity low-likelihood events. Therefore, the study shows that the selection of the risk measure plays a crucial role in determining the target degree of seismic upgrading. Equivalently, quantifying the financial benefits of seismic risk mitigation using different risk measures might lead to different seismic upgrading decisions for the same structure.

Earthquakes can cause widespread damage to the built environment, disrupt the function of many residential buildings to provide safe housing capacities and thus, potentially induce severe long-term societal consequences. Rapid recovery significantly improves the short-term resilience of communities after an earthquake. However, time pressure and scarce information on the severity and the spatial distribution of damage complicate the decision-making. Therefore, early damage estimates are produced using regional earthquake risk models with rapid earthquake intensity data and typological building vulnerability functions. While the precision of the former depends, amongst other issues, on the density of seismic network stations and the region-specific geological knowledge, the typological classification of buildings often involves attribution models correlating exposure data, such as building height and age, with typological seismic vulnerability classes. Typological attribution models are approximate and locally add to the uncertainties resulting from the average representation of buildings forming one building class. Employing probabilistic machine-learning tools, the continuous inspection data inflow is leveraged to dynamically update initial regional earthquake risk predictions by updating simultaneously the functions that govern typological attribution and building damage. Hence, while completing inspection of all affected buildings may take several weeks, the limited information becoming available in the first days following an earthquake helps constraining underlying uncertainties. This leads to more reliable rapid estimates of losses of building functions and their respective spatial distribution. The framework is demonstrated on a region in Switzerland subjected to a fictitious earthquake scenario.

The potentially large spatial footprint of earthquake disasters and the increased concentration of population and values in dense urban areas call for an explicit consideration of seismic risk at a regional, building portfolio level. The relation between the building‐level seismic risk and the portfolio‐level seismic risk is helpful if one wants to meet a specific regional seismic risk tolerance level by specifying seismic risk targets for individual buildings. We examine four types of common risk measures and point to the importance of subadditivity, a risk measure mathematical property, for deriving a conservative upper‐bound relation between the building‐specific and the building portfolio seismic risks. Subadditive risk measures, such as the Expected Shortfall, allow estimates of conservative upper bounds of the portfolio‐level seismic risk. In a case study, we show that nonsubadditive risk measures commonly used in earthquake engineering can lead to counter‐intuitive and nonconservative perceptions of the regional seismic risk, especially when one extrapolates from individual buildings to the entire building portfolio. We also illustrate the advantages of subadditive risk measures for regional seismic risk assessment.

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