the Moody's RMS
insights to help
The catastrophe analytics team at a major intermediary was keen on better understanding how business interruption was captured by the Moody’s RMS Terrorism Model, and in particular if it encompassed added elements such as removal of debris and additional living expenses. Based on a range of scenarios (both conventional and chemical, biological, radiological, and nuclear attacks), the broker wanted to clarify – with a high level of detail and certainty – what business interruption losses could arise and how they would be captured.
The broker worked closely with the Knowledge Center and its skilled team of subject matter experts, terrorism analysts, product managers, model developers, and other specialists. Moody’s RMS was able to explain which elements of business interruption are captured by the terrorism model and what underlying assumptions are made.
We also covered how Moody’s RMS conducts vulnerability assessments and reconnaissance work, to understand the true nature of different attacks, and how business interruption losses could arise, both for the initial target and neighboring properties (for commercial and residential). The team explained how additional elements of prolonged business interruption, caused by evacuation and the introduction of exclusion zones, are factored in.
Clients often demand a greater level of transparency for emerging, man-made catastrophes, such as cyber or terrorism, because risk is much more dynamic. This broker considered trust, transparency, and customer service critical to building sustainable relationships with its clients.
The broking team partnered with the Moody's RMS Knowledge Center to better communicate the drivers of terrorism risk. Together, they interpreted the Probabilistic Terrorism Model and took a closer look into what drives losses in terrorism events. Moody's RMS served as a trusted guide, answering any question the broking team had about the model. Armed with these insights, the broker’s catastrophe analytics team was better equipped to advise clients on modeling results and model suitability, empowering them to make more informed, data-driven decisions on risk transfer and pricing.