As the catastrophe bond market continues to expand into new perils and more complex structures, broad and credible modelling coverage becomes highly important. However, reinsurer Swiss Re\u2019s proprietary catastrophe models allow the firm to analyse a wider range of risks, which according to executives expands the \u201cinvestable universe\u201d while maintaining a well-understood risk-return profile.![\"\"](\"https:\/\/www.europesays.com\/ch\/wp-content\/uploads\/2026\/03\/mariagiovanna-guatteri-balz-grollimund-swiss-re.jpg\")
Artemis recently spoke to Balz Grollimund, PhD, Head of Catastrophe Perils, and Mariagiovanna Guatteri, PhD, Chief Investment Officer of Swiss Re Insurance-Linked Investment Advisors Corp. (SRILIAC), who both explained how Swiss Re\u2019s in-house catastrophe modelling capability works in practice, and how it also supports investment decisions.<\/p>\n
Across the reinsurance space, Swiss Re is a very well-known name. However, within the insurance-linked securities (ILS) industry, the firm is known for being both an issuer or fund manager for ILS. We asked the executives what this multi-faceted role means for ILS investors.<\/p>\n
\u201cSwiss Re, as a group, has a Catastrophe Perils team, which develops in-house natural catastrophe models that support all its risk taking activities. SRILIAC (the ILS fund management arm of Swiss Re) can access that insight directly, meaning that we have access to the same risk models to support investment decisions that Swiss Re uses as a basis for underwriting,\u201d Guatteri told Artemis.<\/p>\n
She continued: \u201cSo investors know that we have a consistent risk view that strengthens our alignment of interests, as the models and guidance we\u2019re using are the same used by Swiss Re to take risk decisions for its own balance sheet. And of course, the risk information is proprietary.\u201d<\/p>\n
In regard to how these cat models are produced, Swiss Re\u2019s team has more than 50 scientists who are directly involved on the production side.<\/p>\n
According to Grollimund this team consists of PhDs and specialists across the relevant scientific disciplines: seismologists, hydrologists, atmospheric scientists, as well as engineers who help the firm understand how hazards translate into physical damage and financial loss.<\/p>\n
\u201cThat scientific inhouse capability is complemented by dedicated technology and IT teams who support model development and implementation. But what I think really creates an edge is that the team understands how the models are actually used. Many rotate through underwriting or work closely with investment and portfolio management teams, so there is a constant feedback loop between model development and every-day application\/ use,\u201d Grollimund said.<\/p>\n
The executives then outlined why it matters for investors whether investment team use the same models as underwriters.<\/p>\n
Guatteri, explained: \u201cWe\u2019ve covered how this allows for a consistent risk view and can contribute to the alignment of interests. The other advantages are transparency, consistency and speed.<\/p>\n
\u201cIn practice, when the Cat Perils team issues a model update or new guidance \u2014 whether following a catastrophe event or reflecting new scientific or socioeconomic insights \u2014 that guidance is implemented directly into the tools we use for investment analysis in a consistent and timely manner, so we are not blindsided by sudden and infrequent model updates. We don\u2019t need to adjust or second-guess the underlying risk views, because we\u2019re so close to the team that produces them.<\/p>\n
\u201cAnd because our portfolios are already analysed within Swiss Re\u2019s systems, we can rapidly assess potential portfolio and industry losses from live nat cat events, and react accordingly.\u201d<\/p>\n
Guatteri also explained how these models enable Swiss Re to explore perils which the ILS industry has not previously covered.<\/p>\n
\u201cAs the catastrophe bond market expands into new perils and more complex structures, broad and credible modelling coverage becomes increasingly important. Swiss Re\u2019s internal models allow us to analyse a wider range of risks \u2014 including secondary perils \u2014 and to assess structures that may be less standardised.<\/p>\n
\u201cWhat\u2019s important for us and for investors is that it actually expands the investable universe while maintaining a well-understood risk-return profile, which is ultimately what institutional investors should care about,\u201d Guatteri said.<\/p>\n
Providing further context, Grollimund shared how Swiss Re\u2019s risk views differ from commercial vendor models.<\/p>\n
\u201cThe most important thing to keep in mind is that catastrophe models are never perfect, and each new event comes with learnings. This is why it is crucial to respond quickly to events, to check whether new insights have been provided by events that warrant a model adjustment, and to update the model quickly if that is the case,\u201d Grollimund said.<\/p>\n
\u201cFor investors, the key point is not that one model is \u201cright\u201d and another is \u201cwrong\u201d, but how quickly and pragmatically insights are incorporated into risk decisions.\u201d<\/p>\n
2025 saw a number of severe convective storm events take place in Europe, which led to a number of losses that surprised the reinsurance market. However, according to Grollimund, in many cases, the issue was not the hazard model itself, but the data that was feeding into it.<\/p>\n
\u201cExposure data often failed to capture recent changes, such as the rapid installation of photovoltaic panels or modern insulation materials, which turned out to be highly vulnerable to hail damage. If sums insured and building characteristics are not up to date, losses will be underestimated,\u201d he said.<\/p>\n
\u201cThis underlines the importance of understanding not just the model, but the whole process to form a risk view, including the quality and completeness of exposure data and underlying loss estimates that are used to calibrate the model.\u201d<\/p>\n
Despite their advantages, proprietary models are sometimes criticised as \u2018black boxes\u2019 due to their opaque nature. We asked the executives how Swiss Re addresses these concerns<\/p>\n
\u201cFor those using them, a proprietary model is the opposite of a black box,\u201d Guatteri said.<\/p>\n
\u201cSwiss Re\u2019s models are fully transparent internally, with direct access to event sets, hazard footprints, assumptions, and \u2014 critically \u2014 the teams that design, maintain, and review them. That allows us to understand the drivers of risk and to engage directly with the modelling process. And to Balz\u2019s point just now: it helps us that we can understand not just the model itself but also the quality and completeness of the source data. We know where limitations are.<\/p>\n
\u201cFor end-investors, different risk views can be benchmarked using common reference portfolios, such as the catastrophe bond market, so that investors can assess relative differences in risk assessment and outcomes across modelling approaches,\u201d she added.<\/p>\n
To end, Grollimund shared how he sees catastrophe modelling evolving over the next few years, and what investors should expect to see within the space too.<\/p>\n
\u201cThe fundamental structure of catastrophe models is unlikely to change dramatically in the near term. But there is significant potential to improve how models are built, maintained, updated and integrated into underwriting processes,\u201d Grollimund said.<\/p>\n
Concluding: \u201cWe are exploring ways in which advanced analytics and AI can help accelerate parts of the modelling process. The goal is not novelty, it\u2019s faster, better-informed insights that improve underwriting and investment decisions. For investors, that ultimately can mean fewer surprises and a more disciplined approach to managing catastrophe risk.\u201d<\/p>\n
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