An insight into Swiss Re's pandemic modelling
As Swiss Re's Group Chief Underwriting Officer, the COVID-19 pandemic is an intensely busy time. However, thanks to the support the of Swiss Re's teams across the world I feel that this situation is manageable, both operationally and financially. This means that Swiss Re can continue to support our clients by providing coverage and paying valid claims.
After almost 30 years in business and having been through both the 9/11 and the global financial crises, I've learned that it is important to learn from these extreme situations. They offer opportunities to test ourselves, to make ourselves more resilient for the future and to come up with better ways to help our clients to be more resilient. This pandemic is no exception.
The path to a pandemic model
Back in 2003, I was Chief Underwriting Officer of Swiss Re's Asian business based in Hong Kong when SARS hit. Alongside the challenging situation this presented on the work front, SARS also meant family disruption, with a delay of some months before my family could join me in Hong Kong.
For Swiss Re, SARS really sharpened our focus on pandemic risk management. As one of the world's largest mortality reinsurers with a strong commitment to the Asian life insurance market, it was clear that we needed a robust way to model pandemic risk and understand the financial stress of large pandemic scenarios.
Therefore, in 2006 Swiss Re started developing our own pandemic model. The model allows us to undertake stress tests on our portfolio – in a similar way to large natural catastrophe risks. In turn, this information informs key business decisions, such as setting our risk appetite or managing our capital.
Since 2006, the model has evolved. It has been constantly improved and updated as new knowledge has emerged. It has also received regulatory approval and is regularly audited.
Understanding diseases and the societies they affect
Swiss Re's pandemic model is a probabilistic model, which uses large data sets to calculate the likely losses from different pandemic scenarios. In simple terms, it is based on understanding the characteristics of diseases, such as influenza, that could result in a pandemic. We then combine this with data that helps us understand society's ability to cope with a pandemic event.
For the diseases themselves, the model draws on data around which viruses might potentially cause a pandemic, how quickly these diseases can spread, how lethal they are likely to be and what types of other factors, such as available medications, might accelerate or decrease the rates of infection.
The ability of communities to deal with a pandemic is a very important factor that we incorporate into our modelling. For example, demographic data allows us to understand the exposure of high-risk groups such as the elderly.
Perhaps the most important feature of the model is that it is evolving as more data sources and more insights into pandemics come to light.
50 000 different pandemic scenarios
Currently, the model statistically analyses 50 000 different pandemic scenarios to see what the impact of a certain strength of pandemic might be on a modelled portfolio.
To illustrate this, we can take the example of a severe, 1 in 200-year modelled pandemic. Our model estimates the percentage of people who would be affected in each scenario and combines that with the percentage of those people who might die. For a 1 in 200-year pandemic, the result comes to 1 to 1.5 additional deaths for every 1000 people in the modelled population, when compared to the expected mortality rate without a pandemic.
This range will vary as the model processes the variables for the modelled population in different countries. In China, for example, a 1 in 200-year scenario would see a higher additional mortality rate of 1.82 per thousand (which would correspond to about 2.5 million people if applied to the entire Chinese population). In the UK it would be about 1.2 additional people per thousand (or about 80 000 additional people if this were applied to the whole population). These figures give us a feeling for the context of a 1 in 200-year pandemic, however, it is very important to keep in mind that drawing conclusions from a modelled insured population to the general population is not that straight forward - as insured populations will display important differences to the general population, such as their age profile.
This modelled mortality estimate can then be mapped to our existing life portfolios to help us calculate the potential financial exposure in our mortality book.
A model only — not a prediction for COVID-19
Given the current situation with COVID-19, it is tempting to ask whether this model can isolate the current pandemic and therefore predict the financial impact.
The answer is no. The final impact of the COVID-19 pandemic remains uncertain and will be unique in terms of insurance impact, lives lost and its impact on the global economy.
We need to be extremely careful about making assumptions, drawing conclusions or extrapolating from the model to the current specific situation. For example, the underlying populations used in the modelled scenarios are different from the general population. In our model, the results are based on an insured population and not comparable to the statistics we read in the media, which might be based on a percentage of the total population, or a percentage of people known to have the disease.
Staying strong for our clients
The spread and mortality rate of COVID-19 is introducing a range of new complexities for insurers in claims, underwriting, policy terms and more. Swiss Re continues to support our clients as they face these complexities, applying our expertise across the value chain to help them understand and address their specific situations.
This is not an easy time. However, thanks to tools such as our pandemic model, we can manage the situation and maintain a strong balance sheet. Our financial strength is the basis for the support we give to our clients. The pandemic model helps us stay strong by significantly increasing the understanding of the financial risks we face and using that knowledge to manage our capital over the long-term.
Learning as we look forward
There will be many learnings from this crisis. It will certainly improve our understanding of pandemic risk. It will also offer insights into how we can better prepare for disasters – as individuals, businesses, and clearly at a societal and political level.
The word "pandemic" derives from Greek, and basically means "all people" – and it is clear to my mind that more cooperation across all levels of society is the best way to deal with this crisis. This means building trust in institutions at local, national, and supranational levels. The best way to do that is to base our decisions on scientific facts - making sure we expand our knowledge when we don't yet know the answers. In this way, families, communities and business leaders can all make the right decisions to support well-being and reduce suffering as much as possible - for all people.
Unlike the situation with SARS in Hong Kong, this time around I am united with my family here in Zurich. For us, "cooperation" has become a very important concept. As my wife and our 14- and 19-year-old daughters are at home most of the time, the everyday chores such as cooking, baking, cleaning the kitchen have come to be seen as positive shared responsibilities — work that brings us together.
It's a challenging time, but in our family's philosophical discussions at the dinner table, we have clearly concluded that crises bring out the very best in people.