$20.5bn – occurred in a relatively inactivehurricane year and therefore would havebeen hard to forecast. Second, thecorrelation between forecasted hurricaneactivities and insured loss is thought to betoo low to be useful, especially at the timeof the traditional 1 January renewal.

Several ideas and developments havebeen combined to demonstrate thebusiness relevance of seasonal US hurricaneforecasts for the first time. Foremost is thesubstantial recent progress made byseasonal hurricane forecasts in terms oflead-time and skill. US hurricane hindcasts

Hurricanes rank historically aboveearthquakes and floods as themajor geophysical cause of

property damage in the US. The annualmean insured damage bill and its standarddeviation for hurricanes striking thecontinental US, 1900-2002, is $2.9bn and$6.7bn respectively at 2002 prices andexposures. As a consequence, the US EastCoast and US Gulf Coast are among theregions with the highest density ofproperty insurance and propertyreinsurance in the world.

Insurers and reinsurers have longrecognised the strong correlation link(0.72; 1900-2002) between US hurricaneactivity and insured loss. As a result, it iswell appreciated that skilful long-rangeforecasts of seasonal US hurricane activitycould be used either to create an additionalprofit margin for a seller of reinsurancecoverage or to reduce costs for buyers ofcoverage. However, two facts have takenthe edge off the use of seasonal hurricaneforecasts in re/insurance business decisionsto date. First, Hurricane Andrew – themost expensive insured loss on record, at

from 1 August (the beginning of the mainAtlantic hurricane season) anticipate thecorrect anomaly sign for US hurricaneinsured loss in 70% of years, meaning thatthe high intensity seasons and the lowintensity seasons are correctly anticipatedin 70% of years. The question is whetherthis seasonal hurricane forecast skill is highenough to create, through appropriateselling or buying of reinsurance products,either an additional profit margin or asignificant arbitrage opportunity to benefitre/insurance business?

A second fundamental premise is to

Niklaus Hilti, Mark Saunders andBenjamin Lloyd-Hughes consider the

business application of seasonalhurricane forecasts in property

catastrophe reinsurance.

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H u r r i c a n e

FORECASTINGSTRONGER

PROFITS

Figure 1: The annual cycle for hurricanes andintense hurricanes striking the US 1950-2002.

Figure 2: Observed and simulated return periods forUS hurricane insured losses ($bn) corrected to 2002prices and exposures.

This article appeared in the July/August 2004Edition of Global Reinsurance.

consider the buying or selling of re/insurancecovers incepting either at 1 July or 1 August(i.e. in lieu of or in addition to a 1 Januaryrenewal). The justification for such a renewalstrategy is that 96% of all intense (category 3to 5) hurricane strikes on the US and 87%of all hurricane hits on the US occur after 1 August (Figure 1). A product which allowsthe buying or selling of re/insurance coverson 1 August is the Industry Loss Warranty(ILW). ILWs are transparent and simple butstandard reinsurance, retrocession orcatastrophe bonds may also be applied.

Testing the strategiesThe re/insurance business application ofseasonal hurricane forecasts has beenexamined from the point of view of buyingor selling US hurricane Industry Loss

Warranty (ILW) covers starting at 1 August. Depending on the forecastedactivity for the upcoming hurricane seasona decision is made whether to buy or sellILW reinsurance covers.

Two different strategies are examined:● Forecast Sell – the strategy of sellingILW cover to create an additional profitdepending on the forecast activity for theupcoming season. ● Forecast Buy – the strategy of buyingILW cover contingent upon the predictedactivity of the upcoming season.

These strategies have been tested on the1950-2002 period of historical insuredlosses (as-if 2002 values) and over a 50,000year period of simulated US hurricanestrikes and losses. The simulation is asophisticated and complex model which

employs fitteddistributions tohistorical as-if lossesand frequencydistributions (e.g.Figure 2). Thismodel will bereported in detailelsewhere. In thisarticle only thebusiness benefitsfrom the simulationmodel arediscussed.

The annualprofitability ofalways selling asingle $10m coverwith onereinstatement isshown in Figure 3as a function offorecast USlandfallinghurricane activityindex and ILWtrigger. The netprofits are clearlyrelated to theactivity forecastindex and thus maybe predicted inadvance of theseason. Annualprofits for the $5bnILW trigger displaythe largestsensitivity to theactivity forecastindex with profits inyears of low forecastactivity (indexvalue of 0.1 to 0.2)being 30% largerthan the meanprofit, and profits inyears of high

forecast activity (index value of 0.8 to 0.9)being 30% less than the mean profit. Theseresults lead to the conclusion that anopportunistic capacity allocation contingenton the seasonal forecast will lead to a 10%-30% increased profitability for a reinsurerselling hurricane ILW cover which follows aForecast Sell strategy.

The Forecast Buy strategy wasbenchmarked against the traditionalAlways Buy strategy where the sameamount of cover is always boughtirrespective of any forecasts. The reason tobuy reinsurance or retrocession is not tomake a profit but to reduce the volatility inannual losses. Thus the Forecast Buystrategy was benchmarked by comparingthe premium spent per recovery atconstant volatility or risk. The analysis wasmade using different risk measuresincluding standard deviation, Value at Riskand Expected Capital Shortfall, though allgave similar results. The results (Figure 4)show that for a 50-year window are/insurer pursuing the Forecast Buystrategy pays about 10%-30% less for thesame amount of protection (i.e. to have thesame recoveries without any increase involatility or risk). Similar benefits are seenfor ILW triggers of $10bn and $20bn.

Skillful forecastsIn addition to the property catastrophere/insurance applications described above,these innovative results offer other businessapplications. For example, the prices paidfor catastrophe bonds within the secondarymarkets should be influenced by skilfulseasonal hurricane forecasts. Also,hurricane forecasts will create an arbitrageopportunity should a new hurricaneactivity index be developed for tradingwithin the capital markets.

Now the proof is there that seasonalhurricane forecasts benefit propertycatastrophe reinsurance business,opportunities exist to improve theprofitability of a range of hurricanere/insurance products.

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Niklaus Hilti is Head of ActuaryReinsurance, Helvetia Patria, and

Designated Head Alternative Investments,Bank Leu, Switzerland.

Dr Mark Saunders is Lead Scientist andProject Manager, Tropical Storm Risk at the

Benfield Hazard Research Centre,University College London, UK.

Dr Benjamin Lloyd-Hughes is ResearchFellow in Business Applications, TropicalStorm Risk at Benfield Hazard Research

Centre, University College London, UK.

By Niklaus Hilti, Mark Saunders and BenjaminLloyd-Hughes

Figure 3: Annual expected profits from ILW sales as afunction of activity forecast index and ILW trigger.The simulation is for 50,000 years.

Figure 4: Savings in premium afforded by the ForecastBuy strategy compared to Always Buy for the samereduction in capital risk. Savings are assessed over a 50-year window (repeated 10,000 times) for $5bn ILWpurchase. Error bars show the 10th and 90th percentilesof the premium reduction.