The Sendai Framework for Disaster Risk Reduction (SFDRR) calls upon the systematic collection of damage and loss data between 2015 and 2030 to monitor a number of disaster indicators. These indicators include the number of deaths, number of injured people, number of people affected by disasters, and direct economic losses. These results can then be compared with previous periods in order to track progress in disaster risk reduction. However, there is an important limitation with such an approach when measuring disaster risk due to earthquakes. Even in countries with significant seismic risk, it is plausible to witness a 15 year period without any destructive earthquakes (e.g., Nicaragua, Haiti, Myanmar). This situation can lead to the perception that efficient measures are being undertaken to reduce the impact of earthquakes, when in reality the trend could be the opposite. An alternative approach to monitor the SFDRR indicators is through probabilistic risk models. These models allow the estimation of the indicators of the SFDRR probabilistically (e.g., average annual economic losses, average annual fatalities), which do not depend on the occurrence of destructive events during the period of interest. Although seismic activity can be assumed as stationary over several decades, in order to evaluate the evolution of the SFDRR over these time frames, the consistent updating of the risk model has to be considered in order to reflect the evolution and change of the built environment and its vulnerability, such as the introduction of new design regulations or the implementation of retrofitting campaigns. A comparison of the various risk indicators throughout time allows assessing whether the potential losses caused by earthquakes are decreasing or increasing, as well as where risk reduction measures should be prioritized. This study discusses how the global seismic risk model released in December 2018 by the Global Earthquake Model (GEM) Foundation and its partners can be explored to monitor the SFDRR, and more importantly, how it can be modified to assess which measures should be endorsed to respect the 2030 targets.