4 www.insuranceday.com| Monday 1 September 2014

www.insura 4 nceday.com| Monday 1 SPECIALREPORT/UNMODELLEDRISKS September 2014

Map: South Korea’s industrial density Sandy: expected event, unexpected consequences Seoul Industrial exposure Yet there are solutions that exist gatelow-resolutiondatatoahigher density by Dong to enable firms to compile expo- resolution, to perform exposure $/square kilometre sure information automatically accumulation analysis and post- and apply deterministic probable event exposure reporting with Superstorm Sandy shows how the maximum losses to monitor expo- increased accuracy. The datasets Less than $1m Waterfront homes damaged sure accumulations in specified also include information on the $1m to $5m influence of uncertainty can by storm surge from Sandy geographic zones. All perils for all characteristics of the exposure, in Mantoloking, New Jersey $5m to $10m business lines in all countries can which can be used to complete create incalculable consequences be managed in this way. companies’ existing data. $10m to $50m The better the exposure data, the To help companies to determine More than $50m Almost immediately, the insur- moreconfidenceaninsurercangain high-risk geographic zones within Kevin H Kelley ance industry found itself in a when writing business in regions which to set accumulation con- Ironshore quagmire as controversy erupted withoutcatastrophemodels. trols, RMS is releasing a suite of as to whether Sandy was a “wind” Exposure data quality is crucial: flood risk hazard maps and event Ulsan event or a “flood” event. Political the completeness and accuracy of scenarios covering inland flood influencers weighed in to protect the data are both important. In and coastal flood, and a global tsu- eteorologists, scien- their constituents, while the Fed- regions without catastrophe mod- nami catalogue. The maps will ena- tists and weather eral Emergency Management els, aggregate data is the norm – ble companies to manage their experts warned of Agency was struggling with accom- typically consisting of an insured portfolios relative to natural haz- the magnitude of modating the severity of loss to total for an entire administrative ard risk zones. They enable quick Mwhat was first considered to make individual property owners and area. This is particularly problem- analysis and reporting and the landfall as a category one hurri- displaced families in communities atic because some administrative application of limits in certain cane in the days leading up to the reaching from the New Jersey well, characteristics of storms such Post-event supply of construc- No dislocation areas are very large, but the exact zones to reduce the risk of cata- arrival of hurricane Sandy. While coastline to the Long Island Sound. asSandyposegreatervulnerability tion resources was insufficient to Lack of market dislocation contrib- locationoftheexposurecouldhave strophic wipeout of a significant businesses and area residents Outdated building codes for com- in the outcomes of those models. facilitate the demand for rebuild- uted to the collective distraction abigimpactontheactualrisklevel. proportion of the portfolio. alongtheeasterncoastline,inMan- mercial buildings in Lower Man- Sandy, however, was a flood or ing efforts, which raised the costs from future loss mitigation. The For example, flood risk can vary For example, portfolio manag- hattan and on Long Island braced hattan allowed for underground “water-pushing” event, much like ofprofessionalservicesandmate- insurance industry shouldered the greatly over even relatively short ers could place a limit on the total the flood risk for each location in-50-year return period tsunami for an unprecedented weather electrical infrastructure despite hurricane Karina, but aggravated rials above pre-storm levels. The insured losses from Sandy’s distances.Consequently,havingan exposure in the one-in-200-year Undoubtedly, in the before underwriting and flag cer- zone given the higher severity and event, the insurance industry was the area being a designated flood by severe cold fronts and inoppor- enormity and unpredictability of impact, which was the third-costli- accurate view on the amount of floodzonetoamaximumof10%of future catastrophe tain locations for high-risk zones destructivepotentialofatsunami. assessing its aggregate risk expo- zone. Businesses and residential tuneweatherconditions,including Sandy’s strength prompted wide- est hurricane in US history. Total risk requires higher resolution thetotalexposureacrosstheentire models for an even for further attention. Portfolio managers and under- sure. The industry’s long-standing properties congregating the coast- a full moon at high tide. Storm spread power outages through- insured losses exceeded $25bn, of data than often available. portfolio and combine that with a wider range of perils Insurers can easily build deter- writerscanalsoapplybufferzones approach to event risk manage- line, whether new or aged con- surge, combined with the other out New Jersey, most of which 75% was covered by private To address this problem, Risk limit on the total exposure within will be developed to fill ministic loss models using the haz- around known sources of poten- ment focuses on data aggregation, struction, were not built to event perils, caused severe prop- Manhattan and surrounding bor- insurance companies. Access to Management Solutions (RMS) has the footprint of a one-in-200- the gaps in the cat risk ard maps. Applying loss ratios to tial catastrophes, such as volca- portfolio exposure assessment, withstand the impact of Sandy’s erty damage to homes and busi- oughs, Long Island and areas of excess market capacity reflects the recently released economic expo- year typhoon flooding in Hanoi, as landscape. Yet with the the exposures within high-risk noes and apply exposure limits post-event claims analysis and wrath. Public transportation was nesses along Sandy’s destructive Connecticut. Thousands of homes resounding health of the industry sure databases and industrial clus- well as another limit on the total inexorable growth in zones will enable the estimation of within those zones. For example a future loss mitigation. interrupted and a return to daily path. Coastline communities were and businesses suffered without as a whole following a depressed ters catalogues across Asia. The exposure within the one-in-200- the global population, possible losses owing to potential limitontotalexposedvaluewithin Management of weather event normality remained an uncer- wiped out, with families still dis- heat, electricity, and water for up economic period. While some com- new suite of exposure datasets pro- year tsunami risk zone along the wealth and industrial catastrophe events. For example, 50 km radius of the Mount Gede risk using modelling tools and ana- tainty. New Jersey Transit, for placed almost two years after the to three weeks after the storm. mercial policyholders that vides the location, configuration coastofTaiwan. output, new risks an assumption could be a 30% loss volcano in Indonesia could be lytics can be most beneficial. Mod- example, relocated trains from one event, and Lower Manhattan was More than 70% of claims filed incurred significant losses did and economic values of exposure The hazard maps can also be continue to emerge ratio within a one-in-100-year applied, or locations flagged up in elling platforms enable insurance flood zone area to another yard, virtually out of business for with private insurance compa- experience upward rate pressure concentrations to enable compa- used for underwriting risk selec- flood zone for all residential prop- this zone for further investigation companies to aggregate exposure, subsequently labelled a flood- months. At the height of the storm, nies for insured losses were from atrenewal,therewaslittleindustry nies develop a more comprehen- tion and rating once the data has erty, or a 90% loss ratio for the one- beforeunderwriting. n assess measured loss and deter- prone area following damage to Battery Park surge level reached homeowners. widepost-eventpriceadjustment. siveviewofriskinAsia.Companies been disaggregated. Users can mine bottom line impact in a worst inoperable passenger trains. nearly 14 ft, surpassing the old Prudent risk management Superstorm Sandy was an event can use these datasets to disaggre- implementanautomaticlook-upof Claire Souch is senior vice-president case scenario. Eventual outcomes recordof10ftsetin1960.TheNew requires attention to mitigation for anomaly. The insurance industry’s of model product strategy at Risk of catastrophic weather events, Complications York Harbour’s surf measured prevention of future loss. In the approach to risk management of Open platformsManagement – Solutions a new approach to loss estimation however, are ultimately deter- The New Jersey coastline pre- record 32.5 ft waves, 6 ft higher months following the event, insti- weathereventswasminimalisedby mined by the uniqueness or spe- sented geographic complications. than the 25 ft level recorded for tutions and public entities pro- available capacity for claims pay- cific “DNA” of the named storm. Of the more than 15 million coastal hurricane Irene in 2011. duced numerous proposals, ment and waning interest in future Sandy presented itsownsetofchal- homes in the world, one-third are The largest percentage of insured studies and reports as visionary lossmitigationagainstcoastalexpo- Whilethereisnoperfectriskmodelling lenges, resulting in unexpected located in the US. The vast majority losses for commercial and residen- solutions against another massive suretomega-stormdestruction. industry consequences. The most of coastal homes are situated along tial properties resulted from water storm surge occurrence. Superstorm Sandy is a testament solution,withanopenplatform surprising industry dynamic in the the Eastern Seaboard and flooding triggered by the storm Coastal flood models to calculate to how the confluence of factors model. Unmodelled perils can be app centages of insured post-Sandy environment was the equipped to withstand historical surge. While water generally cre- potential storm surge loss and pre- surrounding a severe weather Karen Clark hazards not sufficiently contem- roa underwriterscanconstructarobust value will be lost at dif- absence of market dislocation. experience of wind events. Con- ates more damage than wind, flood- cise flooding patterns event can be calculated and mod- Karen Clark & Company plated by the vendor models, ch ferent probability lev- Two unknown factors that test centration of high-value proper- ing tends to be a peril specific to the continue evolving to chart new elledwithacertaindegreeofaggre- such as tsunamis, or particular is tomodelthatisfullytransparent,which els – for example, 10% theindustry’sapproachtoriskman- ties, which typically cannot be characteristic of the storm. Not sur- realities spotlighted by Sandy’s gate accuracy at the outset, yet the regional events for which third- cre-theyunderstandandareincontrolof of total insured value agement are human behaviour and modelled effectively, creates prisingly, storm surge models can damage scenario. Ironically, influence of uncertainty can create party models do not yet exist, such ate with a 1% probability. increasing uncertainty. Sandy trig- heightenedexposureforinsurance be the weakest for data and loss risk-mitigation efforts regarding incalculable consequences.n n unmodelled peril as Morocco earthquakes. an theimportantassumptions New open plat- gered both, neither of which could companies as resultant losses can analysis because of the variability storm surge and flood controls typically refers to a To address unmodelled perils, industry loss curve, then base com- distribution. Another simple forms for catastrophe risk man- have been quantified, modelled or be underestimated. While wind of a storm’s DNA and surrounding stalled as the sense of urgency Kevin H Kelley is chief executive peril for which there is some insurers and reinsurers have pany loss estimates on assumed method is to assume certain per- interpretedattheoutset. risk models perform reasonably weatherconditions. faded with time. of Ironshore A no third-party vendor developed simple approaches. One market shares of the industry loss