Swiss Re Estimates Major UK Storm Could Cause Insured Damage of GBP 9 Billion

Natural catastrophes are by far the biggest risk in non-life property insurance.

Based on its own risk assessment models, Swiss Re estimates, for example, that a major UK storm could lead to economic losses amounting to GBP 12 billion and insured damage of some GBP 9 billion. The consequences of a major flood event could be about half that size. At a London market seminar held Thursday, Swiss Re presented an update on the current state of catastrophe risk globally and in the UK, and explained recent hazard trends and model developments. The speakers emphasized how data quality and transparency are vital prerequisites for accurate catastrophe risk modelling.

Floods and their insurability are an increasing cause for concern for direct insurers, who have had to contend with new loss records on almost an annual basis. According to the Association of British Insurers, in 2000 the UK had its wettest autumn in more than 270 years. Record rainfall caused flooding in approximately 700 locations across England and Wales, damaging some 10,000 properties at a cost to insurers of over GBP 1 billion.

On a European scale, floods and storms have caused losses that rank amongst the top ten most costly insurance events of all time.

According to Swiss Re’s Economic Research & Consulting unit, winter storm Daria in January 1990 led to a bill for insurers of USD 6.3 billion. The storms that battered the UK and Europe in October 1987 cost the industry more than USD 4.7 billion (prices indexed to 2002).

The increasing losses are attributable to factors including higher population densities, a concentration of insured risks in high-risk areas, the vulnerability of certain materials and construction techniques, an increase in building on the flood plain, and the reported poor maintenance of flood defences – a subject of longstanding discussion between UK insurers and government.

Swiss Re’s Chief Underwriting Officer, Werner Schaad reinforced the need for the insurance and reinsurance industry to play an active role in mitigating natural hazard risk: “Natural catastrophes are the source of the biggest loss potentials for the industry, and the catastrophe loss burdens continue to grow. Yet there is a tendency to underestimate these risks, particularly when a catastrophe has not occurred for a long time.

“Specific catastrophe events are clearly unpredictable and totally random in nature, but our understanding of the causes and effects of such extreme events has improved dramatically over the past few decades. Our ability to model the risk, i.e. accurately quantify frequencies and loss potentials, is a vital basis for insuring and reinsuring the risk in a reliable and economically feasible way,” he said.

Severe European winter storm could cost USD 35 billion
Hazard models cannot stop natural catastrophes from occurring. But if insurers can predict, over a long time span, how many loss events will occur and how severe they will be, it increases their ability to provide cover at a price appropriate to the risk. Swiss Re uses its natural hazard models to monitor dozens of natural catastrophe scenarios around the globe, to assess the loss potential for the market as a whole and for its own portfolio. One of the most severe scenario estimates suggests that a large winter storm in Europe could cost the insurers in the region of USD 35 billion.

The seminar was also addressed by Ruurd de Fluiter, CEO of Swiss Re UK, who outlined the importance pricing natural catastrophe cover accurately: “Whilst the cost of (re)insurance cover may come at a premium, the fact that the risk can be assessed and priced more accurately is an essential prerequisite of a viable market for flood and storm cover going forward,” he said.

Quality data in: quality data out
The call for more accurate exposure data to be provided by insurers to their reinsurer(s) was taken up by Gordon Fox, Head of Underwriting for Swiss Re UK’s property treaty: “Models can only be reliable if the data used to establish a picture of loss scenarios is accurate and sufficiently comprehensive. There are a number of areas in which the quality of natural hazard modelling could be improved. These include the accuracy and quality of information on the location, value and characteristics of the risk.

“Clearly, the data used in our proprietary models, and other models available to the industry, is derived from multiple sources. Despite positive noises in terms of forthcoming improvements of flood risk data produced by the UK Environment Agency, this public data is not designed with underwriting in mind and is, in itself, therefore, insufficient to enable us to underwrite and price business accurately and competitively. The real viability of hazard models depends on a more reliable flow of data between insurers and reinsurers.”