Natural Catastrophes And Man-Made Disasters In 2015
No 1 /2016 Natural catastrophes and 01 Executive summary man-made disasters in 2015: 02 Catastrophes in 2015: lobal overvie Asia suffers substantial losses 0 eional overvie 1 ian in: a pule of ris€ accumulation an‚ coverae terms 1 ƒeverain technoloy in ‚isaster manaement 21 ables for reportin year 2015 „ erms an‚ selection criteria
Executive summary “n 2015… there ere a recor‚ 1†‡ natural here ere 5 ‚isaster events in 2015… of hich 1†‡ ere natural catastrophes… catastrophesˆ the hihest ever recor‚e‚ in one yearˆ here ere 155 man‰ma‚e eventsˆ Šore than 26 000 people lost their lives or ent missin in the ‚isasters… ‚ouble the number of ‚eaths in 201„ but ell belo the yearly averae since 1††0 of 66 000ˆ he biest loss of life – close to †000 people – came in an earthŒua€e in Nepal in Aprilˆ –lobally… total losses from ‚isasters ere otal economic losses cause‚ by the ‚isasters in 2015 ere Ž‘’ †2 billion… ‚on Ž‘’ †2 billion in 2015… ith most in from Ž‘’ 11 billion in 201„ an‚ belo the inflation‰a‚ uste‚ averae of Ž‘’ 1†2 Asiaˆ Close to †000 people ‚ie‚ in an billion for the previous 10 yearsˆ Asia as har‚est hitˆ he earthŒua€e in Nepal as earthŒua€e in Nepalˆ the biest ‚isaster of the year in economic‰loss terms… estimate‚ at Ž‘’ 6 billion… inclu‚in ‚amae reporte‚ in “n‚ia… China an‚ ”anla‚eshˆ Cyclones in the •acific… an‚ severe eather events in the Ž‘ an‚ Europe also enerate‚ lare lossesˆ “nsure‚ losses ere Ž‘’ billion… lo –lobal insure‚ losses from catastrophes ere Ž‘’ billion in 2015… ell belo relative to the previous 10‰year averaeˆ the inflation‰a‚ uste‚ previous 10‰year averae of Ž‘’ 62 billionˆ he relatively lo level of losses as larely ‚ue to another benin hurricane season in the Ž‘ˆ El Niño in 2015 contribute‚ to eather patterns ‚eviatin from averae climate normsˆ ˜or instance… tropical cyclone activity in the North Atlantic as suppresse‚… hile the •acific ™cean basin ha‚ a very active seasonˆ he biest insure‚ loss of the year came ™f the insure‚ losses in 2015… Ž‘’ 2‡ billion ere attribute‚ to natural catastrophes from the explosions that roc€e‚ the •ort šabout the same as in 201„› an‚ Ž‘’ † billion to man‰ma‚e events šup from of ian in in China in Auustˆ Ž‘’ billion›ˆ he biest insure‚‰loss as cause‚ by the to massive explosions at the •ort of ian in in China in Auust… ith an estimate‚ property loss of Ž‘’ 2ˆ5 billion to Ž‘’ ˆ5 billion… ma€in it the larest ever recor‚e‚ man‰ma‚e insure‚ loss event in Asiaˆ he next biest insure‚‰loss event as a inter storm in the Ž‘ in ˜ebruaryˆ Another feature of 2015 as that it ill ’espite a harsh inter season in the Ž‘… overall 2015 as the hottest year since 1 o ‚on as the hottest year on recor‚ˆ 1‡50ˆ Exceptionally hih temperatures an‚ lac€ of rainfall cause‚ ‚rouht an‚ Šany reions experience‚ ‚rouht an‚ il‚fires in many reionsˆ “n Europe… summer temperatures remaine‚ above 0°C for il‚fires … lon stretchesˆ Countries in Eastern Europe ere particularly har‚ hit ith ‚rouht con‚itions linerin throuh to the en‚ of the yearˆ he Ž‘ experience‚ its orst year for il‚fires since 1†60 because of the heat an‚ ‚ry con‚itionsˆ žeataves claime‚ a number of lives all over the orl‚ˆ … althouh some countries… such as here ere also severe precipitation eventsˆ “n “n‚ia… the city of Chennai as “n‚ia… the ŽŸ an‚ the Ž‘… experience‚ paralyse‚ by floo‚in after accumulate‚ rainfall of more than 500 mm in November severe rain an‚ floo‚in eventsˆ aloneˆ ƒare sathes of the northern ŽŸ ere un‚er ater in ’ecember ‚ue to heavy rains from three separate stormsˆ •reliminary estimates put the insure‚ losses from the ŽŸ floo‚s at aroun‚ Ž‘’ 2 billionˆ “n several states in the Ž‘… tropical storm activity enerate‚ heavy rains an‚ severe floo‚in in certain areasˆ Countries in Africa… in particular Šalai… Ÿenya an‚ Ša‚aascar… experience‚ severe floo‚s alsoˆ his sigma inclu‚es to feature “n vie of the lare earthŒua€e that struc€ Nepal in April 2015… tremors of hich chapters… one on the ian in explosions ere also felt in ’elhi… this sigma assesses the loss potential of a similarly intense an‚ another on the use of technoloy in event closer to the “n‚ian capital cityˆ he result is total losses in ’elhi of at least ‚isaster manaementˆ Ž‘’ „ billion… larely uninsure‚ˆ he sigma also inclu‚es a special chapter on the explosions in ian in… hich have put a spotliht on accumulation ris€ in lare transportation hubs such as portsˆ Šany assets in ian in – in particular hih‰value cars in transit at the port – ere ‚estroye‚ by the explosionsˆ his… an‚ the imposition of an exclusion one at the site… ma‚e it very ‚ifficult for insurers to assess the lossesˆ ˜inally… there is also a feature on the use of aerial an‚ ‚iital technoloies in ‚isaster ris€ manaementˆ 1 “2015: the armest year on recor‚… scientists say”… metoffice.gov.uk… 16 ¤anuary 2016… http://ˆmetofficeˆovˆu€/nes/releases/archive/2016/2015‰lobal‰temperature Swiss Re sigma No 1/2016 1
Catastrophes in 2015: lobal overvie Number of events: 5 here ere 1†‡ natural catastrophes in ”ase‚ on sigma criteria… there ere 5 catastrophe events across the orl‚ in 2015… an‚ 155 man‰ma‚e ‚isaster 2015… up from † in 201„ˆ ™f those… 1†‡ ere natural catastrophes… the hihest eventsˆ ever recor‚e‚ in one year… an‚ up from 1†1 in 201„ˆ he remainin 155 events ere man‰ma‚e ‚isasters… also more than the 1„‡ that occurre‚ in 201„ˆ Figure 1 300 Number of catastrophic events… Natural catastrophes 1†0–2015 250 Man-made disasters 200 150 100 50 0 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 Man-made disasters Natural catastrophes ‘ource: ‘iss e Economic esearch ¦ Consultin an‚ Cat •erilsˆ he sigma event selection criteriaˆ An event is classifie‚ as a catastrophe an‚ inclu‚e‚ in the sigma ‚atabase hen insure‚ claims… total losses or the number of casualties excee‚ certain threshol‚s… ‚etaile‚ in able1ˆ Table 1 “nsure‚ losses šclaims› he sigma even selection criteria… 2015 Šaritime ‚isasters 1†ˆ million Aviation †ˆ million ™ther losses „‡ˆ‡ million or otal economic losses †ˆ million or Casualties ’ea‚ or missin 20 “n ure‚ 50 žomeless 2000 ‘ource: ‘iss e Economic esearch ¦ Consultin an‚ Cat •erilsˆ 2 Swiss Re sigma No 1/2016
Number of victims: more than 26 000 Šore than 26 000 people lost their lives Šore than 26 000 people lost their lives or ent missin in natural an‚ man‰ma‚e in ‚isaster events in 2015ˆ ‚isasters in 2015ˆ he number of lives lost as more than ‚ouble that in 201„… but as still ell belo the yearly averae of aroun‚ 66 000 ‚eaths since 1††0ˆ Šore than 1† 000 people ‚ie‚ in natural Šore than 1† 000 people ere €ille‚ or ent missin in natural catastrophes… the catastrophesˆ ma ority in the ‚evastatin earthŒua€e that struc€ Nepal in Aprilˆ žeataves an‚ other severe eather events in many reions also claime‚ a number of livesˆ here ere nearly 000 ‚eaths in here ere nearly 000 ‚eaths in man‰ma‚e ‚isasters… compare‚ to approximately man‰ma‚e events… many ‚ue to maritime 5†00 in 201„ˆ he sin€in of a boat carryin mirants off the ƒibyan coast on ‚isastersˆ 1† April 2015 €ille‚ more than ‡00… the hihest loss from a sinle event in the Še‚iterranean ‘ea on sigma recor‚sˆ he total number of reporte‚ ‚eaths in maritime ‚isasters rose to 2„‡ from 211‡ in the previous yearˆ Šany more are believe‚ to have ‚ie‚ in unreporte‚ inci‚ents of boats sin€in hile carryin mirants fleein ar‰torn lan‚sˆ A stampe‚e… ma or fires an‚ explosions ™ther man‰ma‚e catastrophes claimin a hih number of victims inclu‚e‚ a an‚ airplane crashes claime‚ many stampe‚e at the annual ža pilrimae in ‘au‚i Arabia here… accor‚in to victimsˆ overnment sources… 6† people ‚ie‚ˆ Aviation ‚isasters too€ 6‡5 lives in 2015… ‚on from †60 in 201„ˆ Šost of the fatalities ere in to crashesˆ “n Šarch… a pilot committe‚ suici‚e by crashin the plane he as flyin into the ˜rench Alps… ta€in ith his the lives of the other 1„† people on boar‚ˆ An‚ in ™ctober… a et crashe‚ in the ‘inai in Eypt… allee‚ly ‚ue to a bomb blast on the plane… €illin 22„ peopleˆ here ere other in‚ivi‚ual man‰ma‚e ‚isasters in 2015… inclu‚in ma or fires an‚ explosions hich too€ 112 victimsˆ Figure 2 10 000 000 Number of victims… 1†0–2015 1 1†0: ”anla‚esh s torm 1 000 000 2 1†6: anshan earthŒua€e… China 1 2 6 1††1: Cyclone –or€y… ”anla‚esh 3 4 5 „ 200„: “n‚ian ™cean earthŒua€e 100 000 an‚ tsunami 7 8 5 200‡: Cyclone Naris… Šyanmar 10 000 6 2010: žaiti earthŒua€e 201: yphoon žaiyan… •hilippines ‡ 2015: EarthŒua€e in Nepal 1000 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 Man-made disasters Natural catastrophes Note: scale is loarithmic – the number of victims increases tenfol‚ per ban‚ˆ ‘ource: ‘iss e Economic esearch ¦ Consultin an‚ Cat •erilsˆ Swiss Re sigma No 1/2016
Catastrophes in 2015: global oeriew otal economic losses: Ž‘’ †2 billion 2 otal economic losses in 2015 ere ell he estimate‚ total economic losses from natural catastrophes an‚ man‰ma‚e belo the 10‰year averaeˆ ‚isasters across the orl‚ ere Ž‘’ †2 billion in 2015ˆ his is less than the Ž‘’ 11 billion total loss in 201„… an‚ is ell belo the inflation‰a‚ uste‚ averae of the previous 10 years šŽ‘’ 1†2 billion›ˆ Catastrophe losses in 2015 ere 0ˆ12§ of lobal ross ‚omestic pro‚uct š–’•› versus the 10‰year averae of 0ˆ2‡§ˆ –lobal natural catastrophe‰relate‚ losses Natural catastrophe‰relate‚ total losses ere aroun‚ Ž‘’ ‡0 billion in 2015… ere aroun‚ Ž‘’ ‡0 billionˆ stemmin mostly from earthŒua€es… tropical cyclones… other severe storms an‚ ‚rouhts in Asia… North America an‚ Europeˆ Table 2 Regions S bn o otal losses… in Ž‘’ billion an‚ § of North America 2† 0ˆ1„§ lobal –’•… 2015 ƒatin America ¦ Caribbean 0ˆ1„§ Europe 1 0ˆ06§ Africa 1 0ˆ05§ Asia ‡ 0ˆ15§ ™ceania/Australia 0ˆ20§ ‘eas / space 1 Total €2 ¨orl‚ total 0ˆ12§ 10‰year averae ©© 1†2 0ˆ2‡§ © roun‚e‚ numbers ©© inflation a‚ uste‚ ‘ource: ‘iss e Economic esearch ¦ Consultin an‚ Cat •erilsˆ Šan‰ma‚e ‚isasters cause‚ Šan‰ma‚e ‚isasters are estimate‚ to have cause‚ Ž‘’ 12 billion of the total lobal Ž‘’ 12 billion in total lossesˆ losses in 2015… up from Ž‘’ † billion in 201„ˆ 2 ˜rom hereon… referre‚ to as “total losses”ˆ „ Swiss Re sigma No 1/2016
“nsure‚ losses: Ž‘’ billion “nsure‚ losses ere belo averae aain he insurance in‚ustry covere‚ almost Ž‘’ billion – less than half – of the total last year … losses from natural an‚ man‰ma‚e ‚isasters in 2015… an‚ ell belo the inflation‰ a‚ uste‚ previous 10‰year annual averae of Ž‘’ 62 billionˆ Natural catastrophes resulte‚ in claims of Ž‘’ 2‡ billion… the loest since 200† an‚ aain much loer than the previous 10‰year inflation‰a‚ uste‚ annual averae šŽ‘’ 55 billion›ˆ ƒare man‰ma‚e ‚isasters le‚ to claims of Ž‘’ † billion… up from Ž‘’ billion in 201„ˆ … an‚ eŒuivalent to 0ˆ05§ of –’•ˆ he 2015 natural catastrophe insure‚ losses amounte‚ to 0ˆ0„§ of –’•… an‚ 1ˆ‡§ of ‚irect premiums ritten 𒕍› on property lobally… belo the respective 10‰year annual averaes of 0ˆ0‡§ an‚ ˆ§ˆ ™verall insure‚ losses from natural catastrophes an‚ man‰ma‚e ‚isasters ere 0ˆ05§ of –’• an‚ 2ˆ„§ of ’•¨ˆ Figure ‚ 140 “nsure‚ catastrophe losses… 6 9 1†0–2015… Ž‘’ billion at 2015 prices 120 100 1 1††2: žurricane An‚re 2 1††„: Northri‚e earthŒua€e 80 10 1†††: ¨inter ‘torm ƒothar „ 2001: †/11 attac€s 60 5 5 200„: žurricanes “van… Charley… ˜rances 1 4 8 6 2005: žurricanes Ÿatrina… ita… ¨ilma 40 2 200‡: žurricanes “€e… –ustav 20 ‡ 2010: Chile… Ne «ealan‚ earthŒua€es † 2011: ¤apan… Ne «ealan‚ 0 earthŒua€es… hailan‚ floo‚ 10 2012: žurricane ‘an‚y 190 195 1980 1985 1990 1995 2000 2005 2010 2015 Earthquake/tsunami Weather-related catastrophes Man-made disasters ‘ource: ‘iss e Economic esearch ¦ Consultin an‚ Cat •erilsˆ he larest sinle insure‚‰loss event as he larest insurance loss event lobally… of both natural an‚ man‰ma‚e ‚isasters… the ian in port explosions in Chinaˆ as the to explosions at the •ort of ian in in China… hich triere‚ property claims of Ž‘’ 2ˆ5 to Ž‘’ ˆ5 billionˆ he next larest event as a ˜ebruary inter storm in the Ž‘ resultin in insure‚ losses of Ž‘’ 2 billionˆ “n 2015… seven ‚isasters triere‚ insure‚ claims of Ž‘’ 1 billion or more šsee able 6›… compare‚ ith 10 in 201„ˆ he lobal insurance protection ap as ˜iure „ shos the ‚ifference beteen insure‚ an‚ total losses over time… terme‚ Ž‘’ 55 billion in 2015ˆ the insurance protection or fun‚in apˆ “t is the amount of financial loss enerate‚ by catastrophes not covere‚ by insuranceˆ “n 2015… the lobal protection ap as Man-made disasters Ž‘’ 55 billionˆ he rate of roth of total losses has outpace‚ the roth of insure‚ losses over the last 5 yearsˆ “n terms of 10‰year rollin averaes… insure‚ losses Weather-related catastrophes re at 10§ beteen 1†† an‚ 2015… an‚ total losses by 10ˆ„§ˆ As a percentae of –’•… uninsure‚ losses rose from 0ˆ0‡§ in 1†6–1†‡5 to 0ˆ1§ in 2006–2015ˆ Earthquake/tsunami Swiss Re sigma No 1/2016 5
Catastrophes in 2015: global oeriew Figure ƒ 450 “nsure‚ vs uninsure‚ losses… 1†0–2015… Ž‘’ billion in 2015 prices 400 350 300 Uninsured losses 250 200 Insured losses 150 100 50 0 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 Insured losses 10-year moving average (total insured lossses) Uninsured losses 10-year moving average (total economic lossses) otal losses ¬ insure‚ ® uninsure‚ lossesˆ ‘ource: ‘iss e Economic esearch ¦ Consultin an‚ Cat •erilsˆ 6 Swiss Re sigma No 1/2016
eional overvie he hihest insure‚ losses in 2015 ere ¨inter storms in the Ž‘… alon ith floo‚s an‚ tropical cyclones in many parts of the in Asia an‚ North Americaˆ orl‚ cause‚ the hihest insure‚ losses in 2015ˆ “n Asia… the explosions in ian in an‚ ma or storms cause‚ the biest insure‚ losses in the reion… hile the Nepal earthŒua€e too€ most lives an‚ cause‚ the hihest economic loss of the yearˆ Table ‚ „nsured losses …conomic losses Number of events… victims… economic an‚ Region Number †ictims in in S bn in in S bn in insure‚ losses by reion… 2015 North America 51 2‡ 1ˆ1§ 1ˆ „ˆ1§ 2‡ˆ6 1ˆ2§ ƒatin America ¦ Caribbean 25 „6 2ˆ‡§ ˆ2 ‡ˆ§ ˆ5 ‡ˆ2§ Europe „1 2612 †ˆ†§ 6ˆ2 1ˆ0§ 12ˆ6 1ˆ§ Africa „† „1 1ˆ0§ 0ˆ0 0ˆ1§ 1ˆ2 1ˆ§ Asia 15† 1‡ †16 1ˆ‡§ ˆ0 1†ˆ0§ ˆ „1ˆ1§ ™ceania/Australia 1 5 0ˆ2§ 2ˆ1 5ˆ§ ˆ0 ˆ§ ‘eas / space 15 1† 1ˆ2§ 0ˆ† 2ˆ„§ 1ˆ1 1ˆ2§ ¨orl‚ 5 26 5† 100ˆ0§ 100ˆ0§ †2 100ˆ0§ ‘ource: ‘iss e Economic esearch ¦ Consultin an‚ Cat •erilsˆ North America “n the Ž‘… severe storms… a har‚ inter “n North America… insure‚ losses ere Ž‘’ 1 billion… the hihest of all reionsˆ Šost an‚ floo‚s cause‚ most lossesˆ of the losses came from inter storms… other severe storms… such as thun‚erstorms an‚ torna‚oes… an‚ floo‚ events in the Ž‘ˆ here ere relatively fe catastrophes in Cana‚aˆ ƒosses from the harsh inter season “t as a harsh inter storm season in the Ž‘ for the secon‚ year in a roˆ here ere ere above averaeˆ many inter storms ith heavy snofall an‚ very lo temperaturesˆ “n mi‚‰˜ebruary… a lare storm an‚ relate‚ ice accumulation cause‚ i‚esprea‚ ‚amae in 1 states… ith Šassachusetts har‚est hitˆ he associate‚ insure‚ losses ere estimate‚ to be over Ž‘’ 2 billion… mainly from burst froen ater pipes an‚ ice eiht/ater ‚amae to propertyˆ “nsure‚ losses from all the Ž‘ inter storms toether amounte‚ to Ž‘’ ˆ2 billion… ‚ouble the annual averae of the previous 10 yearsˆ orna‚o activity as averae hile Accor‚in to a preliminary count from the ‘torm •re‚iction Centre of the National insure‚ losses from severe storms ere ™ceanic an‚ Atmospheric A‚ministration šN™AA›… there ere 1252 torna‚oes in loer than averaeˆ 2015… the most in one year since 2011 an‚ in line ith the annual averae š1222› of the ’oppler ra‚ar era from the early 1††0sˆ Nevertheless… insure‚ losses from torna‚o outbrea€s an‚ thun‚erstorms ere estimate‚ to have been aroun‚ Ž‘’ 10 billion… loer than in 201„ šŽ‘’ 1 billion› an‚ the previous 10‰year annual averae šŽ‘’ 12 billion›ˆ ™nly one thun‚erstorm cause‚ losses of Ž‘’ 1 billion or more… hile an outbrea€ of E˜ an‚ E˜„ torna‚oes at the en‚ of ’ecember in exas an‚ neihbourin states cause‚ a hih number of fatalitiesˆ he North Atlantic hurricane season he 2015 Atlantic hurricane season pro‚uce‚ 11 name‚ storms šeiht in 201„›… four pro‚uce‚ a belo‰averae number of of hich became hurricanes šsix in 201„› an‚… li€e in 201„… to š’anny an‚ ¤oaŒuin› storms aainˆ attaine‚ the status of ma or hurricanes šCateory or stroner on the ‘affir‰‘impson scale›ˆ žurricane ¤oaŒuin as the stronest hurricane of the season an‚ the stronest observe‚ in the Atlantic since žurricane “or in 2010ˆ ƒast year as the 10th year in „ succession that no ma or hurricane ma‚e Ž‘ lan‚fall… the lonest stretch since the 1‡60sˆ Accor‚in to the N™AA’s Climate •re‚iction Centre… El Niño curbe‚ storm ‚evelopment iven a combination of stable atmospheric con‚itions… ‚rier air an‚ 5 hih in‚ shear in lare parts of the main hurricane eneration reionˆ 3 E˜¬ Enhance‚ ˜u ita ‘cale 4 ¨hen it ma‚e lan‚fall… žurricane ‘an‚y in 2012 pro‚uce‚ the thir‚‰biest loss ever from a storm eventˆ žoever… it ‚oes not reister as a “ma or” hurricane on the ‘affir‰‘impson scaleˆ 5 “”elo‰normal Atlantic hurricane season en‚s³ active eastern an‚ central •acific seasons shatter recor‚s”… noaanews.noaa.gov… 1 ’ecember 2015…http://ˆnoaanesˆnoaaˆov/ stories2015/120115‰belo‰normal‰atlantic‰hurricane‰season‰en‚s‰active‰eastern‰an‚‰central‰pacific‰ seasons‰shatter‰recor‚sˆhtml Swiss Re sigma No 1/2016
Regional oeriew žeavy rainfalls triere‚ many severe Even thouh no hurricane ma‚e Ž‘ lan‚fall in 2015… tropical storm activity affecte‚ floo‚ events ‚urin the yearˆ several states in the form of intense precipitation… lea‚in to severe floo‚inˆ “n the sprin… the remnants of tropical storm ”ill brouht heavy rain an‚ floo‚in to ™€lahoma an‚ exasˆ “n ™ctober… ‚onpours ‚ue to žurricane ¤oaŒuin hit ‘outh Carolina an‚ li€eise le‚ to heavy floo‚inˆ ¨il‚fires are an ever‰present haar‚ in ™ther parts of the Ž‘ ere ‚ry… an‚ there ere several il‚fires ‚urin the yearˆ the Ž‘ˆ ’rouht con‚itions fuelle‚ il‚fires in California… the most fire‰prone stateˆ he most ‚estructive fire in terms of buil‚ins ‚estroye‚ š10› an‚ number of hectares burne‚ šover 0 000› as the ´alley ˜ire in ƒa€e County… Californiaˆ he insure‚ losses from this event alone ere ust over Ž‘’ 0ˆ† billion… ran€in sixth as the most costly il‚fire in the Ž‘ everˆ here ere also il‚fires in the estern states of ¨ashinton… ™reon an‚ Alas€a… an‚ in Cana‚aˆ “n terms of acres burnt š10ˆ1 million›6… 2015 as the orst year for il‚fires in the Ž‘ since 1†60ˆ µet hile the fires spanne‚ hue areas… only a fe urban areas ere impacte‚ meanin that resi‚ential property‰relate‚ losses ere limite‚ˆ “nsure‚ losses ere belo averae in “n Cana‚a… there ere fe natural ‚isasters in 2015 for a secon‚ year runninˆ he Cana‚aˆ biest loss‰in‚ucin event as a series of thun‚erstorms in Calary… Alberta… in mi‚‰Auust… lea‚in to insure‚ losses of Ž‘’ 0ˆ2 billionˆ Europe ˜loo‚in cause‚ the heaviest losses… “n Europe… natural catastrophes an‚ man‰ma‚e ‚isasters cause‚ total losses of particularly in the ŽŸˆ Ž‘’ 1 billion in 2015ˆ ™f those… Ž‘’ 6 billion ere insure‚ˆ he main losses came from heavy precipitation in estern countriesˆ “n ’ecember… severe floo‚in cause‚ ’urin the first ee€ of ’ecember… ‘torm ’esmon‚ brouht very heavy rainfall to ‚evastation across many parts of the north an‚ northest Enlan‚ˆ Šore than 500 houses ere floo‚e‚… most in north an‚ north estern ŽŸˆ Cumbria… an‚ several bri‚es ere ‚estroye‚ˆ ‘tartin from 22 ’ecember… ‘torm Eva brouht usts of more than 5 miles per hour… an‚ pushe‚ the rains south into µor€shire… ƒancashire an‚ –reater Šanchesterˆ hen… ‚urin the last ‚ays of the year… ‘torm ˜ran€ brouht more heavy rain across northern Enlan‚… “relan‚… Northern “relan‚ an‚ ‘cotlan‚ˆ “t as the ettest calen‚ar month an‚ the armest ’ecember in the ŽŸ since recor‚s bean in 1†10ˆ “n total… about 16 000 homes ere inun‚ate‚ as floo‚ ‚efences ere breache‚ˆ •reliminary estimates put the insure‚ losses from all the ’ecember rains an‚ floo‚in in the ŽŸ at aroun‚ Ž‘’ 2 billionˆ žoever… 2015 as also a hot an‚ ‚ry Earlier in the year… in ™ctober heavy rains an‚ floo‚in hit southeastern ˜ranceˆ year in Europe… lea‚in to increase‚ žoever… overall 2015 as a hot an‚ ‚ry year in continental Europeˆ “n ¤une an‚ mortality an‚ ‚rouhtˆ ¤uly… temperatures remaine‚ above 0°C for lon stretches in many countriesˆ A prolone‚ rainfall shortae that bean in April an‚ the hih summer temperatures cause‚ severe ‚rouht… hich affecte‚ soil moisture content an‚ veetation con‚itionsˆ Countries in Eastern Europe… particularly omania… ere severely affecte‚ an‚ ‚rouht con‚itions linere‚ throuh to the en‚ of the yearˆ he hih summer temperatures also claime‚ a number of victims across Europeˆ •reliminary estimates from statistical offices in‚icate a ‚eath toll of at least 1200ˆ here ere to terror attac€s in •aris in ™f man‰ma‚e ‚isasters… the most prominent event as a series of coor‚inate‚ 2015… the most ‚ea‚ly on 1 Novemberˆ terrorist attac€s in the ˜rench capital •aris on 1 November 2015ˆ ™ne hun‚re‚ an‚ thirty people lost their lives in simultaneous mass shootins… suici‚e bombins an‚ hostae ta€in at various locations in the city… an‚ 51 ere in ure‚ˆ “t as the biest loss of life in one event in continental Europe last yearˆ Also in •aris… in ¤anuary the offices of satirical maaine Charlie žeb‚o ere attac€e‚ˆ Eleven people ‚ie‚ˆ 6 “”illion‰’ollar ¨eather an‚ Climate ’isasters: able of Events”… ncdc.noaa.gov… accesse‚ in ¤anuary 2016… http://ˆnc‚cˆnoaaˆov/billions/events 7 “ecor‚in the eather across the ŽŸ”… blog.metoffice.go.uk… ¤anuary 2016… http://bloˆmetofficeˆovˆu€/2016/01/0‡/reportin‰the‰eather‰across‰the‰u€/ an‚ “2015 eather summary – ’ecember”… metoffice.gov.uk, 12 ¤anuary 2016… http://ˆmetofficeˆovˆ u€/climate/u€/summaries/2015/‚ecember ‡ Swiss Re sigma No 1/2016
Asia Asia has suffere‚ the most loss of life As in the previous three years… loss of life ‚ue to natural an‚ man‰ma‚e catastrophes from catastrophic events for four years as hihest in Asia in 2015ˆ “n all… there ere aroun‚ 1† 000 victimsˆ he total cost runninˆ of ‚isaster events in the reion as estimate‚ to be aroun‚ Ž‘’ ‡ billion… of hich more than Ž‘’ billion ere insure‚ˆ ™n 25 April 2015… an earthŒua€e of manitu‚e Š ‡ Aroun‚ † 000 people ‚ie‚ in the ˆ‡ struc€ Nepalˆ he epicentre earthŒua€e that struc€ Nepal in Aprilˆ as beteen the capital Ÿathman‚u šhome to 1ˆ2 million people› an‚ •o€hara… the nation’s secon‚ larest cityˆ he resultin ‚estruction spanne‚ lare parts of central Nepal… affectin almost half of its ‚istricts inclu‚in isolate‚ mountainous areasˆ he earthŒua€e as ‡ˆ2 €m belo the earth’s surface an‚ cause‚ severe ‚amae in Ÿathman‚uˆ he city lies on a ‚ry la€e be‚… the soil of hich is soft an‚ ust 650 metres ‚eep… hich accentuate‚ the ‚estructive poer of the Œua€eˆ “n all… close to †000 people ere €ille‚… ma€in it the orst ‚isaster in Nepal in over ‡0 yearsˆ he earthŒua€e’s impact ent beyon‚ Nepal… ith casualties an‚ ‚amae reporte‚ in “n‚ia… China an‚ ”anla‚esh alsoˆ otal losses from the earthŒua€e ere estimate‚ to be Ž‘’ 6 billion… most of hich ere uninsure‚ˆ yphoon –oni cause‚ the hihest ¨ith respect to insure‚ losses… the biest natural catastrophe event in Asia as insurance loss of all natural catastrophes yphoon –oni… hich ma‚e lan‚fall in ¤apan on 25 Auustˆ he insure‚ losses ere in Asiaˆ estimate‚ to be Ž‘’ 1ˆ2 billionˆ he typhoon claime‚ ‡† lives… most in the •hilippines an‚ North Ÿorea rather than in ¤apanˆ žeavy monsoon rains hit southern “n‚iaˆ Elsehere… “n‚ia as hit by severe floo‚inˆ “n mi‚‰November… repeate‚ heavy monsoon rains cause‚ floo‚s in the southern states of amil Na‚u an‚ An‚hra •ra‚esh… an‚ in the union territory of •u‚ucherryˆ he cities of Chennai… Cu‚‚alore an‚ Ÿancheepuram an‚ neihbourin ‚istricts ere most affecte‚ˆ he total losses ere estimate‚ to be at least Ž‘’ 2 billionˆ “nsure‚ losses ere Ž‘’ 0ˆ‡ billion… ma€in the floo‚s the secon‚ costliest insurance event in “n‚ia on sigma recor‚sˆ A lare part of the losses oriinate‚ from commercial lines as Chennai is home to several manufacturin companies… particularly in the motor in‚ustryˆ he city of Chennai as paralye‚ by the Chennai is a ma or urban an‚ in‚ustrial centre in southern “n‚ia… ith a population of resultin flash floo‚sˆ about ‡ˆ5 millionˆ ¨hile heavy rains in the area are common… ‚urin the northeast monsoon š™ctober–’ecember› of last year… the accumulate‚ rainfall in November alone as in excess of 500 mmˆ ‘ome areas ha‚ more than 250 mm rainfall in ust 2„ hoursˆ his extreme rainfall volume over a short ‚uration paralye‚ Chennai… ith ma or ‚isruption to critical infrastructureˆ he event hihlihts the vulnerability of rapi‚ly roin urban areas to flash floo‚s oriinatin from heavy rainsˆ 8 Š is the moment manitu‚e… base‚ on the seismic moment… hich “is a measure of the sie of an earthŒua€e base‚ on the area of fault rupture… the averae amount of slip… an‚ the force that as reŒuire‚ to overcome the friction stic€in the roc€s toether that ere offset by faultinˆ” ‘ee http://earthŒua€eˆ ussˆov/learn/lossary/¹term¬seismic§20moment Swiss Re sigma No 1/2016 †
Regional oeriew ‡iing on the edge: earthˆua‰e haŠard emanating rom the ‹imalaŒan region he žimalayas are one of the orl‚’s he žimalayas… forme‚ by the continental collision of the “n‚ian an‚ Eurasian plates… most seismically haar‚ous reionsˆ have the hihest mountain pea€s in the orl‚ˆ he reion is also one of the most seismically active loballyˆ his is because the northboun‚ un‚er‰thrustin of the “n‚ia plate beneath the Eurasia plate continues to‚ay… at a rate of –„ centimeters per yearˆ he map belo shos the alinment of more recent earthŒua€es alon the plate boun‚ary line… runnin from Assam in the east šhere there as an Š ‡ˆ6 Œua€e in 1†50› to Ÿashmir in the est šthe site of an Š ˆ6 earthŒua€e in 2005›ˆ Figure 5 he žimalayan plate boun‚ary line an‚ the ‚ates of ma or earthŒua€es ‘ource: ‘iss eˆ houh 50 €m aay from the epicentre… remors oriinatin from the epicentre of the April 2015 earthŒua€e in Nepal ere ’elhi felt the tremors of the April Œua€e in also felt in ’elhi… the capital of “n‚ia… almost 50 €m aayˆ Accor‚in to 2011 census Nepalˆ ‚ata… aroun‚ †0§ of ’elhi’s buil‚in stoc€ falls in the cateory of unreinforce‚ masonry… hich is not earthŒua€e resistantˆ Šoreover… ’elhi is locate‚ on the ban€s of iver µamuna on a be‚ of very soft soil… hich can amplify seismic aves an‚ their ‚amae‰causin potentialˆ he presence of a seismic ap in central he žimalayan plate has a seismic ap… that is… an area here plate movement has žimalayas is a ris€ for ’elhiˆ alrea‚y pro‚uce‚ lan‚ ‚eformation but – as of yet – no release of associate‚ enery in the form of an earthŒua€eˆ he ap exten‚s from the reion near the Ÿanra earthŒua€e in 1†05 šsee ˜iure 5› to the epicentre of the 1†„ Nepal earthŒua€e šaroun‚ 00 €m›ˆ he li€elihoo‚ of earthŒua€es in seismic aps is very hih… an‚ the expecte‚ manitu‚e of such an earthŒua€e in the žimalayas is Š ‡ˆ0–‡ˆ5ˆ ’elhi is much closer to certain areas of the seismic ap than to the epicentre of the April 2015 earthŒua€eˆ “n other or‚s… the city is vulnerable to earthŒua€e ris€ˆ he economic loss from a ma or o assess the loss potential of such an event in ’elhi… ‘iss e simulate‚ the impact earthŒua€e near ’elhi coul‚ amount to of an earthŒua€e of Š ‡ˆ0 manitu‚e ust 1†0 €m aay from the city… ith its as much as Ž‘’ „ billionˆ epicentre in the žimalayan seismic ap… usin the proprietary Šulti‘NA• toolˆ he simulation assume‚ an insurance penetration rate in ’elhi of 1ˆ„§ˆ† he outcome as a total economic loss of at least “N 20 billion šŽ‘’ „ billion›… ith insure‚ losses of aroun‚ “N 25ˆ2 billion šŽ‘’ „00 million›ˆ An‚… ’elhi is one of “n‚ia’s most populous cityˆ A lare earthŒua€e there oul‚ li€ely also mean lare loss of lifeˆ 9 Indian non-life insurance industry yearbook 2014–15… –eneral “nsurance Council… 2015ˆ https://ˆicouncilˆin/‚onloa‚sˆaspx 10 Swiss Re sigma No 1/2016
Explosions in the port of ian in in China ¨ith respect to man‰ma‚e ‚isasters… the larest insurance loss event of 2015 cause‚ the larest insure‚ loss of 2015ˆ happene‚ in Asiaˆ ™n 12 Auust… to massive explosions at the •ort of ian in in northeast China claime‚ 1 victims an‚ in ure‚ many moreˆ he explosions affecte‚ an area of €m ra‚ius… causin lare‰scale ‚amae to surroun‚in property an‚ infrastructureˆ he property insurance loss is estimate‚ to be Ž‘’ 2ˆ5 billion to Ž‘’ ˆ5 billionˆ ea‚ more in the special chapter on ian in in this sigmaˆ ƒatin America an‚ the Caribbean “nsure‚ losses in ƒatin America ere over Natural catastrophes an‚ man‰ma‚e ‚isasters cause‚ total losses above Ž‘’ billion Ž‘’ billion in 2015ˆ in ƒatin America an‚ the Caribbean in 2015ˆ “nsure‚ losses ere over Ž‘’ billionˆ he main ‚rivers ere earthŒua€es… hurricanes an‚ floo‚sˆ ˜loo‚s hit northern Chileˆ ™n Šarch 25–26… there ere very heavy rains in the Atacama ’esert in northern Chile… one of the ‚riest places on earthˆ he Copiapó iver hich… accor‚in to overnment sources… ha‚ been ‚ry for 1 years… rapi‚ly fille‚ ith rainater an‚ 10 overfloe‚ˆ he roun‚’s roc€ surface an‚ lac€ of veetation meant that the hih volumes of rainater ere not absorbe‚ˆ “nstea‚… there ere massive mu‚flos that hit the cities of Copiapó an‚ Antofaasta in the Atacama an‚ Antofaasta reionsˆ Accor‚in to overnment estimates… the total ‚amae amounte‚ to Ž‘’ 1ˆ5 billionˆ 0 b “nsure‚ losses ere aroun‚ Ž‘’ ˆ„5 illion… the larest insure‚ loss from a natural catastrophe in the reionˆ El Niño/EN‘™ is associate‚ ith arm an‚ et eather alon the coast of •eru an‚ Chileˆ •atricia as the stronest hurricane on ‘imilarly… in 2015 El Niño fuelle‚ the tropical storm season in the eastern •acific… recor‚ in the eastern North •acific an‚ accor‚in to the N™AAˆ he eastern •acific sa 1‡ name‚ storms… inclu‚in 1 Atlantic basinsˆ hurricanes… nine of hich ere ma orˆ “t as the first year since 1†1 that there ere nine ma or hurricanes in the eastern •acificˆ ¨ith in‚ spee‚s of 20 €m/h… žurricane •atricia as the stronest hurricane on recor‚ in both the Atlantic an‚ the 11 eastern North •acific basinsˆ žoever… it ‚i‚ not hit heavily populate‚ areas hen it ma‚e lan‚fall in Šexico… an‚ the insure‚ losses ere mo‚erateˆ he remnants of •atricia ‚i‚ brin rainfall to exas… thouhˆ he combine‚ Šexico/exas insure‚ losses are estimate‚ to have been Ž‘’ 0ˆ billionˆ here ere some lare man‰ma‚e A fire an‚ explosion on a ‚rillin platform in the ”ay of Campeche… Šexico… cause‚ ‚isasters in ƒatin America in 2015ˆ the biest man‰ma‚e loss of the reionˆ “n another ‚isaster in November… a tailins ‚am at an iron ore mine in Šinas –erais… ”rail… burst causin sinificant ‚amae an‚ environmental pollution as mu‚ travelle‚ throuh ateraysˆ 10 “˜loo‚in in Chile’s Atacama ’esert after years’ orth of rain in one ‚ay”… climate.gov, 16 April 2015… https://ˆclimateˆov/nes‰features/event‰trac€er/floo‚in‰chile§E2§‡0§††s‰atacama‰‚esert‰ after‰years§E2§‡0§††‰orth‰rain‰one‰‚ay 11 “žurricane •atricia is stronest recor‚e‚ in Eastern Nortn •acific”… orld eteorlogical rganiation… 12 ™ctober 2015… https://ˆmoˆint/me‚ia/content/hurricane‰patricia‰stronest‰recor‚e‚‰eastern‰ north‰pacific Swiss Re sigma No 1/2016 11
Regional oeriew ™ceania Šany ‚isasters cause‚ insure‚ losses for Natural catastrophes an‚ man‰ma‚e ‚isasters in 2015 cause‚ insure‚ losses of Ž‘’ 2ˆ1 billion in ™ceania… mainly in Ž‘’ 2ˆ1 billion in ™ceania… primarily from thun‚erstorms an‚ tropical cyclonesˆ “n Australiaˆ April… a poerful storm system brouht lare hail an‚ stron in‚s to Ne ‘outh ¨ales… causin insure‚ losses of Ž‘’ 0ˆ billion… the costliest catastrophe event in Australia an‚ the reion last yearˆ ™ther severe storms… tropical cyclone Šarcia an‚ bushfires a‚‚e‚ to the overall insure‚ tally for the reionˆ Šarcia as the most intense cyclone to ma€e lan‚fall… an‚ also the most intense recor‚e‚ so far south on 12 the eastern coast of Australiaˆ ‘everal outbrea€s of bushfires ‚estroye‚ homes an‚ vast areas of crop lan‚ in ‘outh Australia… ´ictoria an‚ ¨estern Australia last yearˆ Africa “n Africa… over 000 people ‚ie‚ in Natural catastrophes an‚ man‰ma‚e ‚isasters in Africa claime‚ „1 lives an‚ ‚isaster events in 2015ˆ cause‚ total losses of Ž‘’ 1ˆ2 billion in 2015ˆ he insure‚ losses ere minorˆ At the beinnin of the year… 2‡6 people ‚ie‚ in floo‚s in Šalai… an‚ close to 250 000 people ere left homelessˆ ƒosses from the thousan‚s of houses ‚estroye‚ or ‚amae‚ ere estimate‚ to be Ž‘’ 0ˆ„ billionˆ ˜loo‚s also hit Ÿenya… hile Ša‚aascar as affecte‚ by both floo‚s an‚ tropical storm Che‚aˆ µet aain… terrorism contribute‚ to lare loss of life in the reionˆ “n a un attac€ at a Žniversity in –arissa… Ÿenya… 1„‡ stu‚ents lost their livesˆ 12 “Annual Climate eport 2015”… bom.gov.au… 2016 http://ˆbomˆovˆau/climate/annual½sum/2015/Annual‰Climate‰eport‰2015‰ƒˆp‚f 12 Swiss Re sigma No 1/2016
ian in: a pule of ris€ accumulation an‚ coverae terms he explosions in ian in in 2015 ™n 12 Auust 2015… to massive explosions at a arehouse in the •ort of ian in in enerate‚ accumulate‚ losses across China claime‚ 1 victims… in ure‚ close to ‡00… an‚ cause‚ lare‰scale ‚amae to multiple lines of insurance businessˆ surroun‚in property an‚ infrastructureˆ he severity of the blasts an‚ lare asset exposures at the time mean that the ian in event is the biest man‰ma‚e insurance loss event ever recor‚e‚ in Asiaˆ he i‚e rane of insurance policies impacte‚ by the explosions… an‚ the complexity of interpretation of coverae beteen policy classes… ma€e for an interestin case stu‚yˆ he ian in experience also puts a spotliht on ris€ accumulation controls at ma or tra‚in hubs an‚ in‚ustrial par€sˆ he event ian in’s port is the ateay to ”ei in ian in is in northeast Chinaˆ “t is the closest startin point to the Asia‰Europe lan‚ an‚ China’s in‚ustrial northeastˆ bri‚e an‚ ateay to the country’s capital ”ei inˆ “n 201… it ran€e‚ as the orl‚’s 1 thir‚ larest port in terms of caro volume an‚ the 10th for container trafficˆ “t has 2 an in‚ustrial an‚ petrochemicals complex coverin about 115 €m ˆ he port is the main loistics hub for China’s automotive in‚ustry… accountin for „0§ of all car imports an‚ exports… an‚ serves the same function for components an‚ materials for a number of other in‚ustries… inclu‚in healthcare an‚ electronicsˆ o hue blasts rippe‚ throuh a he to explosions at ian in on 12 Auust ere triere‚ by a fire in a arehouse in loistics par€ at the port in Auustˆ one of the port’s several loistics par€sˆ he arehouse as storin haar‚ous an‚ 1„ flammable materials… such as ammonium nitrateˆ ™f the 1 victims … 10„ ere firefihters calle‚ out to extinuish the initial fireˆ Accor‚in to the China EarthŒua€e A‚ministration… the first blast reistere‚ a manitu‚e of Š 2ˆ an‚ the secon‚ Š 15 2ˆ†ˆ he explosions enerate‚ a fireball an‚ sent shoc€aves across an area of several‰€ilometre ra‚ius… leavin a lare crater in the roun‚ˆ •roperties a‚ acent to the site of the blasts… mostly container yar‚s an‚ automotive storae facilities… ere ‚estroye‚… as ere thousan‚s of ne vehicles in transit par€e‚ nearbyˆ Accor‚in to a recently issue‚ official report from the Chinese authorities… 0„ buil‚ins… 12 „2‡ 16 vehicles an‚ 5 containers ere ‚estroye‚ˆ “n a‚‚ition… ‚ue to the sheer intensity of the blasts… thousan‚s of vehicles an‚ properties ithin a 5 €m ra‚ius sustaine‚ ‚amae ranin from severe to non‰structural še… shattere‚ in‚os or ust ‚ust cover›ˆ “nsurers estimate the total number of affecte‚ cars to be a multiple of the 12 „2‡ mentione‚ in the official reportˆ “ronically… the port’s shippin terminals ere larely unscathe‚ˆ As the blasts happene‚ in one of many storae an‚ loistic operations areas… overall port activity as shut ‚on for a fe ‚ays onlyˆ Accor‚in to the official report… Accor‚in to reports of official sources… the fire starte‚ in a arehouse after the auto‰inition of nitro‰cotton spar€e‚ a ettin aent €eepin a supply of nitro‰cotton in a container ‚amp… evaporate‚ in fire that le‚ to the explosionsˆ the hih temperatures an‚ auto‰inite‚ˆ he fire Œuic€ly sprea‚ to other chemicals store‚ at the site inclu‚in ammonium nitrate… hich triere‚ the ‚evastatin 1 explosionsˆ here is an alternative an‚ i‚ely‰hel‚ belief that attempts by firefihters to put out the initial fire coul‚ have triere‚ the blasts or manifie‚ their intensityˆ he overnment… hoever… maintains that this as not the caseˆ Either ay… the event calls for a revie of safety reulations for the storin of haar‚ous materials… an‚ stroner enforcement of associate‚ proce‚uresˆ 13 orld ort anking 201 … American Association of •ort Authorities http://ˆaapa‰portsˆor/“n‚ustry/contentˆcfm¹“temNumber¬†00¾‘tatistics 14 165 people ere €ille‚ an‚ eiht are still missinˆ ‘ee A ’uc€ett… “ian in blast blame‚ on mismanaement”… €e ‚€emical ƒngineer… ‡ ˜ebruary 2016… http://ˆtceto‚ayˆcom/latest§20nes/2016/february/tian in‰blast‰blame‚‰on‰mismanaementˆ aspx¾ˆ´rn2c½2a1 15 “‘tatement of Šr •u µun ¿iao… member of the China EarthŒua€e A‚ministration”… as reporte‚ in “ ”… „in€ua… 1 Auust… 2015… http://nesˆxinhuanetˆcom/science/2015‰ ‡/1/c½1„511†61ˆhtm 16 “ian in blast probe suests action aainst 12 people”… „in€ua… 5 ˜ebruary 2016… http://nesˆ xinhuanetˆcom/enlish/2016‰02/05/c½150‡†0ˆhtm 17 A ’uc€ett… opˆ citˆ Swiss Re sigma No 1/2016 1
TianŽin: a puŠŠle o ris‰ accumulation and coerage terms he authorities enforce‚ an exclusion “n a‚‚ition to flammable materials… lare amounts of toxic so‚ium cyani‚e ere one to facilitate clean‰up or€ˆ bein store‚ at the siteˆ he ris€ of follo‰up explosions prompte‚ the authorities to impose a €m exclusion one aroun‚ the blast area until 25 Auustˆ Access ithin a 1ˆ5 €m ra‚ius remaine‚ restricte‚ even thereafter ‚ue to onoin clean‰up operationsˆ he challene of loss estimation an‚ claims a‚ u‚ication in ian in he exclusion one has ‚elaye‚ he ian in explosions have presente‚ insurers ith a number of challenes… not assessment of the full lossˆ least lac€ of access to the affecte‚ area to assess the full extent of ‚amae an‚ resultin insurance claimsˆ he imposition of the exclusion ones meant that formal loss a‚ ustment ithin those areas as not possibleˆ he exclusion ones ere lifte‚… but access remaine‚ restricte‚ˆ As such… the level of insure‚ losses in the ones še… to cars an‚ caro containers› have been estimate‚ in total loss terms… or have been 1‡ base‚ on forensic accountinˆ ’rones an‚ satellite imaery enable‚ a obots an‚ pre‰ an‚ post‰event ‚rone an‚ satellite imaery have helpe‚ loss first assessment of exposuresˆ assessmentˆ ’rones ere sent in to ta€e pictures of the ‚isaster site imme‚iately after the explosionsˆ hese imaes ere compare‚ ith satellite imaes of the site ta€en prior to the eventˆ he comparison provi‚e‚ a vie of the extent of ‚estruction… an‚ also of the hih number of vehicles an‚ containers on the site at the time of the explosionˆ “nitial loss assessments have been base‚ on this informationˆ “nitial estimates in‚icate insure‚ losses ”ase‚ on ‘iss e’s latest estimates… the total insure‚ property loss of the ian in cause‚ by the blasts ill total Ž‘’ explosions is li€ely to be aroun‚ Ž‘’ 2ˆ5 billion to Ž‘’ ˆ5 billion… ma€in it the 2ˆ5 billion to Ž‘’ ˆ5 billionˆ larest man‰ma‚e insure‚ loss event in Asia ever recor‚e‚ˆ he estimate is base‚ on… amon other… the net loss estimates from re/insurers’ thir‚‰Œuarter or full‰year 2015 results… here availableˆ Assumptions ere ma‚e for those insurers hich have not yet release‚ claims estimatesˆ he estimate is a or€in assumption an‚ is sub ect to revisionˆ ’estroye‚ an‚ ‚amae‚ vehicles As first claims ere file‚… it became clear that ‚amae to the thousan‚s of ne account for most of the lossesˆ vehicles par€e‚ at an‚ near the blast site oul‚ ma€e up most of the insurance claimsˆ he containers there at the time ere mostly empty… an‚ ‚amae to containers… caro… arehouses… infrastructure… machinery an‚ eŒuipment account for a much smaller proportion of the lossesˆ ”usiness/continent business interruption… aviation… liability… personal acci‚ent an‚ life claims li€eise account for a small portion of the lossesˆ “f the par€e‚ vehicles ere in transit… Even thouh the main loss – to ne cars – is €non… uncertainties ith respect to claims oul‚ come un‚er marine caro the types of policies involve‚ remainˆ “f the vehicles at the site at the time of the insurance coveraeˆ explosion ere in transit… they oul‚ li€ely be covere‚ by marine insurance policiesˆ ‘tan‚ar‚ marine caro insurance usually covers onshore storae up to a certain number of ‚ays… ‚epen‚in on policy terms… once the caro is loa‚e‚ off the shipsˆ ”ut if ian in as the final port of “f ian in as the final port of ‚estination for the vehicles… their next transfer bein to ‚estination for the vehicles… claims coul‚ a point‰of‰sales in China… claims coul‚ come un‚er property insuranceˆ žoever… this be un‚er property insuranceˆ transfer is often ‚one throuh a local holesaler li€e China Automobile ra‚in Co šCAC›… hile other car manufacturers have their on ‚istribution operationsˆ “f car imports are channele‚ throuh a local holesaler or subsi‚iary… it is not Œuite so simple to ‚etermine hether the manufacturer’s caro policy or the local entity’s property or ‚omestic transport policy respon‚s… or hether the to covers are overlappinˆ ˜urther… it is sometimes ‚ifficult to ascertain hich entity hel‚ title to the par€e‚ vehicles at the time of the explosions an‚… accor‚inly… hether the loss falls un‚er the marine caro or property insurance policies ta€en outˆ 18 he branch of accountin use‚ for enaements resultin from actual or anticipate‚ ‚isputesˆ ‘ee https://enˆi€ipe‚iaˆor/i€i/˜orensic½accountin 1„ Swiss Re sigma No 1/2016
ax treatment ill affect the final “n a‚‚ition… if the vehicles ha‚ one throuh customs an‚ ere ‚eeme‚ to be valuation of vehicle claimsˆ importe‚ into China alrea‚y… the ‚eclare‚ oo‚s šsale› price… inclu‚in import levies… coul‚ apply for loss assessment purposes… ‚epen‚in on policy termsˆ hat oul‚ be consi‚erably hiher than the manufacturin or replacement value: custom ‚uties an‚ taxes on importe‚ cars in China can ma€e up for up to 50§ of the retail sellin price… or even more ‚epen‚in on the sie of the enineˆ he total number of cars in the affecte‚ area at the time may be €non… but it is not possible to ascertain from the par€in position alone hether customs ‚uties an‚ taxes have alrea‚y been pai‚ on these vehiclesˆ he extent of ‚amae to vehicles further ´ehicles outsi‚e the 1ˆ5 €m exclusion one but ithin the €m an‚ even further out aay from the centre of the blast is not ere also ‚amae‚… an‚ it is not clear ho ba‚lyˆ “n these cases… the Œuestion for clear… hich further complicates loss assessment purposes is hether the vehicles shoul‚ be “ritten‰off” as valuation assessmentˆ unsaleable… or hether they have resale value post cleanin an‚ repairˆ “f the latter… an actual sale price or neotiate‚ ‚epreciation rate for repaire‚ vehicles coul‚ be applie‚ to ‚etermine the resi‚ual value of a carˆ žoever… until a sufficient number of such sales have ta€en place… it ill be ‚ifficult to assess the amount of ‚epreciationˆ ˜urther… so‰calle‚ bran‚ clauses coul‚ increase loss estimates… ‚epen‚in on policy termsˆ ‘ome bran‚ clauses ive i‚e ‚iscretion to the insure‚ to claim total loss for a car ith ust limite‚ ‚amae… because sellin a repaire‚ vehicle coul‚ harm bran‚ reputationˆ his oul‚ be particularly relevant for cars ith no physical ‚amae… but here customers coul‚ have concerns about buyin a vehicle that as in the port of ian in hen the explosions occurre‚ˆ “™pen policies” for caro insurance a‚‚ ˜or caro an‚ containers… there is an a‚‚e‚ complexityˆ he i‚ely‰use‚ system of another un€non factor in final valuationˆ open policies for caro insurance šith a rate base‚ on turnover for a storae facility rather than ‚eclarations of the precise shipment› means that an insurer ‚oes not €no hat insure‚ caro is in a specific container or the exact value of its contentsˆ “n‚ications are that most of the vehicle “nformation alrea‚y publishe‚ by re/insurers suests that the ma ority of vehicle claims ill ultimately fall un‚er property claims in ian in fall un‚er the property insurance cateory… mostly arisin from hih‰ insuranceˆ value importe‚ cars at the onshore storae stae of their ourney to mar€etˆ žoever… the sheer volume of the ‚estroye‚ an‚ ‚amae‚ cars an‚ the numerous loss a‚ ustment an‚ a‚ u‚ication challenes as ‚escribe‚ above leaves the total insurance loss in a state of fluxˆ he very hih number of cars on the site suests some may have been there for an exten‚e‚ perio‚ˆ his coul‚ in‚icate that car manufacturers or importers use ports as interme‚iate storae facilities… somethin insurers may not have been aare of previouslyˆ he hih number of par€e‚ vehicles coul‚ also be in‚icative of the recent ‚onturn in the Chinese economyˆ •uttin the pieces of the pule toether •roperty an‚ caro present ma or ris€ he sie of the insure‚ loss of any ‚isaster event is larely ‚riven by the accumulation accumulation factors in ports… especially of ris€s simultaneously expose‚ to the same eventˆ •orts… arehouses… caro storae in bi centres li€e ian inˆ facilities an‚ in‚ustrial par€s are amon the locations ith most ris€ accumulation potentialˆ he concentration of store‚… loa‚e‚ an‚ unloa‚e‚ caro… infrastructure an‚ other in‚ustrial an‚ commercial activities mean in‚ustrial acci‚ents in… an‚ severe eather events at… these locations can enerate ma or accumulate‚ losses across multiple lines of businessˆ ‘uch as the case in ian inˆ he explosions happene‚ in a property close to lare storae an‚ transit spaces… here many hih‰ value ne cars ere par€e‚… an‚ also close to other in‚ustrial an‚ commercial buil‚ins typical of a ma or tra‚in hubˆ he explosions impacte‚ many ris€s simultaneously… an‚ there ere lare losses across many lines of businessˆ rac€in caro exposure is challeninˆ he shippin in‚ustry an‚ marine an‚ property insurers are ell aare of the potential for lare losses from accumulation of ris€sˆ žoever… Œuantifyin losses in caro areation points such as very lare container vessels or ports at any iven time is ‚ifficultˆ ‘ome re/insurers have ‚evelope‚ formal mo‚els to better un‚erstan‚ these ris€s… an‚ so improve the insurability of potential accumulate‚ lossesˆ žoever… ian in also shos that there nee‚s to be more ris€ mappin in areation points to better un‚erstan‚ exposure accumulationsˆ Swiss Re sigma No 1/2016 15
TianŽin: a puŠŠle o ris‰ accumulation and coerage terms Capturin the spatial ‚istribution of caro Catastrophe mo‚ellin has tra‚itionally focuse‚ on static ris€s… such as buil‚ins an‚ is critical to an un‚erstan‚in of port infrastructures… inclu‚in those ithin portsˆ Šo‚ellin mobile ris€s such as ships accumulationˆ an‚ caro… an‚ ho the ris€s accumulate in ‚istribution centres… has alays been a 1† challeneˆ Accumulation manaement for caro usually involves co‚in the exposure as arehouse content usin fixe‚ location ‚ata… such as the central point of the portˆ žoever… ports are lare an‚ framente‚… often consistin of separate areas spannin €ilometers… as is the case of ian inˆ •roper caro mo‚elin must correctly account for the eoraphic ‚istribution of exposureˆ A‚vance‚ metho‚s are reŒuire‚ to a‚‚ress the complexity of these ‚istributionsˆ he shippin in‚ustry an‚ insurers can EŒuippin expensive oo‚s an‚ caro containers ith active sensors coul‚ help use the ian in experience to better‰ trac€ exposureˆ ”i ’ata an‚ smart analytics coul‚ ma€e marine ‚ata more un‚erstan‚ ris€ accumulation in ports… accessible… enablin better assessment of caro ris€ accumulations an‚ creatin an‚ on vessels tooˆ reater scope for mo‚ellinˆ he shippin in‚ustry an‚ insurers shoul‚ use the ian in experience as an opportunity to promote more robust un‚erstan‚in of ho exposures accumulateˆ “t is not only fires an‚ explosions that pose a ris€ˆ •orts an‚ ships can also be struc€ by natural catastrophes… as in the case of žurricane ‘an‚y in 2012ˆ20 “n all cases… a complex pule of marine an‚ property cumulative loss scenarios can resultˆ he complexities presente‚ by the he ian in explosions are a remin‚er that lare‰scale man‰ma‚e in‚ustrial explosions have challene‚ the catastrophe events ‚o happenˆ he ‚isaster also thros liht on some ne insurance in‚ustryˆ consi‚erationsˆ “n particular… the sheer volume of motor vehicles involve‚ turne‚ some simple coverae issues into one of the biest challenes that the insurance in‚ustry has ever face‚ˆ ian in also shos that man‰ma‚e ‚isasters can have a ma or impact on a lobal an‚ complex scale… iven the lare number of sta€ehol‚ers sprea‚ across ‚ifferent uris‚ictions… each ith their on reulatory frameor€ˆ he ian in experience also hihlihts the ian in coul‚ ultimately become one of the larest man‰ma‚e insurance loss events ne potential ris€s facin ‚evelopin orl‚i‚e ever recor‚e‚ šsee able „›ˆ he event shos the lare loss potential in a countries ith rapi‚ly‰‚evelopin country li€e China… ith a fast‰roin economyˆ “f further evi‚ence is nee‚e‚… in economiesˆ 201 a fire at a ma or hih‰tech semicon‚uctor plant in ¨uxi… also in China… cause‚ insure‚ losses of Ž‘’ 0ˆ† billionˆ 2015 as the thir‚ year in a ro that the biest man‰ma‚e loss lobally oriinate‚ from an emerin mar€et… a remin‚er of the importance of insurance for ‚evelopin countriesˆ ˜inancial protection throuh insurance is €ey to restorin business operations an‚ recoupin lossesˆ Accurate assessment of exposures… appropriate coverae terms an‚ a‚eŒuate pricin are li€eise crucialˆ ˜or re/insurers… they nee‚ to actively i‚entify… monitor an‚ manae exposures in haar‚ ones an‚ in areas ith hih asset‰value concentrationsˆ Table ƒ ‘ear CountrŒ …ent „nsured loss †ictims ƒarest man‰ma‚e insure‚ losses 2001 Ž‘ error attac€ on ¨C… •entaon… other buil‚ins 25ˆ2 2 †‡2 lobally… in Ž‘’ billion at 2015 prices 1†‡‡ ŽŸ Explosion on platform •iper Alpha ˆ0 16 2015 China Explosions at a arehouse storin haar‚ous 2ˆ5 to ˆ5© 1 chemicals at ian in •ort 1†‡† Ž‘ ´apour clou‚ explosion at petrochemical plant 2ˆ„ 2 1†† Ž‘ ’amae at nuclear poer station 1ˆ„ 2001 ˜rance Explosion ‚estroys fertilier plant 1ˆ 0 ©provisional ‘ource: ‘iss eˆ 19 …afe €avens† easuring natural catastro‡€e eˆ‡osure to cargo traded t€roug€ ‡orts… ‘iss e… 2010ˆ 20 žurricane ‘an‚y ‚estroye‚ thousan‚s of recreational boats alon the eastern coast of Ž‘ an‚ cause‚ sinificant ‚amae on many of the facilities of the •ort of Ne µor€ an‚ Ne ¤erseyˆ 16 Swiss Re sigma No 1/2016
ƒeverain technoloy in ‚isaster manaement Žsin technoloies to buil‚ €nole‚e echnoloy can be use‚ to better he lessons of past ‚isaster events can help buil‚ reater resilience by informin un‚erstan‚ the ris€s pose‚ by ‚ifferent ‚ecisions ith respect to puttin in place mitiatin infrastructure an‚ financial perils … resources špublic an‚ private sector›ˆ his chapter loo€s at ho aerial an‚ ‚iital technoloies are use‚ to better un‚erstan‚ the ris€s pose‚ by perils… but is not a comprehensive revie of all opportunitiesˆ he chapter specifically covers: ̤ Žnmanne‚ aerial vehicles šŽA´›… such as ‚rones… an‚ ho these can help in post‰ ‚isaster assessment an‚ response³ ̤ emote sensin techniŒues… such as “nterferometric synthetic aperture ra‚ar š“n‘A – see box “Šonitorin roun‚ ‚eformations from space”›³ an‚ ̤ “mprove‚ location intellience… early arnin an‚ relief response via social me‚ia an‚ cro‚sourcinˆ21 … an‚ also inform post‰‚isaster response hese technoloies can be important tools in ‚isaster ris€ manaement strateyˆ an‚ loisticsˆ hey can improve post‰‚isaster assessment an‚ response loistics… an‚ can be use‚ to buil‚ a €nole‚e profile of an area or specific property… inclu‚in proximity to natural catastrophe ris€sˆ his is information that can also be use‚ for insurance purposes – in ris€ mo‚ellin… un‚erritin… an‚ real‰time ‚isaster trac€in an‚ loss assessment… an‚ in the ‚esin of catastrophe insurance solutionsˆ Figure ’ Ne technoloies in ‚isaster ris€ manaement ‘ource: ‘iss e Economic esearch ¦ Consultinˆ ost-disaster assessment and response mechanisms ŽA´s are increasinly bein use‚ as he rapi‚ ‚evelopment of ŽA´ technoloy has enable‚ reater use of ‚rones as remote sensin an‚ imain ‚evices in imain platforms to complement the visuals pro‚uce‚ by satellites an‚ manne‚ post‰‚isaster reconnaissanceˆ aircraftˆ ’rones have the a‚vantae of bein small… lo‰cost an‚ able to closely survey an‚ photoraph lare areas more efficientlyˆ ’amae‚ areas sometimes cannot be seen by satellites an‚ manne‚ aircraft… for example ‚ue to clou‚ cover… or may be inaccessible for first‰han‚ human inspection ‚ue to contamination or transport outaes after a ‚isaster eventˆ ’rones can also survey ob ects from the si‚e rather than ust from above… an‚ can facilitate ’ reconstruction of an environment usin stereoscopic camerasˆ hese are valuable inputs for improve‚ ‚amae assessmentˆ 21 Cro‚sourcin is the practice of solicitin contributions from a lare roup of peopleˆ ‘ee https://enˆi€ipe‚iaˆor/i€i/Cro‚sourcin Swiss Re sigma No 1/2016 1
‡eeraging technologŒ in disaster management “n 2015… the commercial ‚eployment of he first ‚eployment of ‚rones in a ‚isaster event came after žurricane Ÿatrina in ‚rones in ‚isaster situations became 2005ˆ en years later… their use has become mainstreamˆ ˜or example: mainstreamˆ ̤ “n the •ort of ian in… ‚rones ere use‚ to ta€e pictures of the site hit by the ‚evastatin explosions of 12 Auust 2015 imme‚iately after the eventˆ hese ere compare‚ ith satellite imaes ta€en prior to the blasts hich shoe‚ the number of vehicles… caro an‚ containers on site at the time of the explosionˆ he before an‚ after comparison enable‚ initial loss assessmentˆ his oul‚ not have been possible ithout ‚rones because of the €m‰ra‚ius exclusion one enforce‚ at the siteˆ he alternative oul‚ have been to use manne‚ aircraft to ta€e pictures after the event from hih altitu‚e… hich oul‚ have been more expensive an‚ may not have pro‚uce‚ the same Œuality imaesˆ ̤ “n ’ecember 2015… ‚rones ere use‚ to ta€e pictures over Cumbria in the ŽŸ after lare areas ere floo‚e‚ ‚ue to ‘torm ’esmon‚ˆ he imaes alloe‚ for better response plannin… an‚ loss a‚ usters use‚ them to i‚entify the orst‰ affecte‚ areas an‚ properties for hich claims ere reporte‚… hich in turn facilitate‚ initial claims reservinˆ22 ̤ ‘imilarly… for the first time in Australia… insurers use‚ ‚rones to assess the ‚amae cause‚ by bushfires in ´ictoria on Christmas ’ay 2015ˆ2 ̤ “n the Ž‘… the use of ‚rones by insurers is a roin tren‚ an‚… for the first time… in 2015 the ˜e‚eral Aviation A‚ministration rante‚ reulatory approval to insurance firms to use ‚rones for commercial purposesˆ2„ ‘ocial me‚ia is becomin a valuable ‘ocial me‚ia can li€eise be hihly effective in ‚isaster situations… for example to communications tool in ‚isaster sen‚ early arnin sinalsˆ ¨hen an Š 5ˆ† manitu‚e earthŒua€e hit near scenariosˆ ichmon‚… ´irinia in the Ž‘ in Auust 2011… itter users in Ne µor€ rea‚ about the Œua€e 0 secon‚s before they themselves felt the roun‚ sha€inˆ25 “n some situations… such as ‚urin žurricane ‘an‚y in 2012… social me‚ia platforms li€e itter an‚ ˜aceboo€… an‚ voice over internet protocol š´o“•›‰base‚ applications such as ‘€ype… can be a primary source of communicationˆ ‘an‚y €noc€e‚ out poer to millions of people in Ne ¤ersey… ho instea‚ receive‚ up‚ates from the authorities an‚ the emerency services before an‚ ‚urin the storm usin their mobile ‚evicesˆ26 ‘ocial me‚ia has infiltrate‚ less‰connecte‚ populations alsoˆ “n an example of “technoloy leapfroin”… in the aftermath of the ‚evastatin earthŒua€e that hit Ÿathman‚u in April 2015… the fe people ith connection to the li€es of ˜aceboo€ ere able to use the netor€s to collect an‚ share informationˆ2 ‡ocation intelligence ƒocation intellience is crucial for Ÿnole‚e of the location of insurable assets an‚ their proximity to natural ‚isaster ‚isaster ris€ manaement an‚ ris€s… couple‚ ith ne analytical tools… can improve ris€ mitiationˆ emote sensin un‚erritinˆ tools such as “n‘A can be use‚ to support these efforts an‚ help insurers improve ris€ mo‚els an‚ pricin šsee belo›ˆ 22 “’rones ill transform loss a‚ ustin”… Insurance ‰ay… 2 ¤anuary 2016ˆ 23 “Australia: “A– is first to use ‚rones to assess Nat CA ‚amae”… Šsia Insurance eview… 1 ¤anuary 2016… http://ˆasiainsurancerevieˆcom/Nes/´ie‰Nesƒetter‰Article/i‚/„6†/ype/e’aily 24 “žo “nsurers Are acin o A‚opt ’rones “n ™ne Chart”… ‚‹ Insig€ts… „ ¤anuary 2016… https://ˆ cbinsihtsˆcom/blo/insurance‰firm‰‚rone‰exemptions/ 25 ˆ ˜or‚… “East Coast resi‚ents rea‚ about ’ˆCˆ earthŒua€e before feelin it themselves”… t€e€ollywoodre‡orter.com… 2 Auust 2011… http://ˆhollyoo‚reporterˆcom/nes/earthŒua€e‰ titter‰users‰learne‚‰tremors‰226„‡1 26 Šˆ Šussoline… “‘an‚y •roves ‘ocial Še‚ia Can ”e •oerful in a žurricane”… accuweat€er.com, 1 Auust 201… http://ˆaccueatherˆcom/en/eather‰nes/social‰me‚ia‰an‚‰hurricanes‰ ‚isasters/†55052 An‚… accor‚in to a recent stu‚y by the Žniversity of ‘an ˜rancisco… in the Ž‘ over 0§ of people in ‚isaster situations use social me‚ia to communicate ith relativesˆ ‘ee ‘ˆ homas… “‘ocial Še‚ia Chanin the ¨ay ˜EŠA espon‚s to ’isaster”… National ’efense Šaaine… ‘eptember 201ˆ 27 “‘ocial Še‚ia ”ecomes a ƒifeline in the Nepal EarthŒua€e Aftermath”… globalvoices.org… 26 April 2015… https://lobalvoicesˆor/2015/0„/26/lobal‰social‰me‚ia‰lifeline‰in‰nepal‰earthŒua€e‰aftermath/ 1‡ Swiss Re sigma No 1/2016
“onitoring ground deormations rom space “n‘A is a mappin tool of roun‚ “nterferometric synthetic aperture ra‚ar š“n‘A› is a techniŒue for mappin roun‚ ‚eformations usin ra‚ar imaesˆ ‚eformationsˆ o ‚etect chanes in the earth’s surface… to or more ra‚ar imaes of a select area are ta€en from approximately the same position in space… but at ‚ifferent timesˆ ”y bouncin sinals from a ra‚ar satellite off the roun‚ in successive orbits an‚ comparin the imaes… “n‘A can ‚etect even subtle chanes 2‡ in the lan‚ surface – up… ‚on or si‚eays šsee ˜iure ›ˆ Figure ” “n‘A maps rea‚ roun‚ ‚eformation by measurin reflecte‚ echo of ra‚ar sinals from an earth‰orbitin satellite ‘ource: ¤et •ropulsion ƒaboratory… NA‘Aˆ Active… but previously thouht ‚ormant… “n‘A has been use‚ to monitor an‚ analyse volcanos in Alas€a an‚ in the estern volcanos have been ‚iscovere‚ usin Ž‘ˆ A surprisin ‚iscovery as that some volcanos lon thouht to be ‚ormant… are “n‘Aˆ actually ‚eformin an‚ coul‚ eventually eruptˆ2† “n‘A can also be use‚ to estimate the overall ‚amae after an earthŒua€e by comparin built‰up areas before‰ an‚ after earthŒua€e eventsˆ 0 he “o can help ‚evelop location he “nternet of hins š“o› has a stron potential for ris€ mitiationˆ A central intellience an‚ be use‚ for early component of “o are sensors… mostly inbuilt ‚evices that can monitor various arnin communicationsˆ rea‚ins such as of temperature… roun‚ movement an‚ ra‚iationˆ his information can provi‚e early ‚etection an‚ onoin monitorin of events li€e fires… earthŒua€es an‚ ra‚iation lea€sˆ A recent stu‚y foun‚ that the –•‘ receivers in smartphones can ‚etect earthŒua€es an‚ can be use‚ to buil‚ cro‚source‚ earthŒua€e early arnin systemsˆ1 he sensors can also help locate victims after a catastropheˆ Cro‚sourcin platforms are ™nline cro‚sourcin platforms can also be helpful ‚urin crisesˆ ˜or instance… the 2 increasinly bein use‚ in ‚isaster Žshahi‚i crisis map platform as use‚ in the response proram after the Š 5ˆ„ situationsˆ manitu‚e earthŒua€e in žaiti in 2010ˆ “nformation an‚ reports ere athere‚ throuh social me‚ia an‚ text messaes sent via mobile phones an‚ plotte‚ on the map in real time by an international roup of volunteersˆ hese reports… alon ith their specific locations… ere available to anyone ith internet connectionˆ Emerency respon‚ers on the roun‚ soon bean to use them in ‚eterminin here an‚ ho to ‚irect resourcesˆ Another example is ‘afecast … a cro‚sourcin platform in ¤apan create‚ to furnish more availability of public information about contamination after the Šarch 2011 earthŒua€e an‚ tsunami… an‚ subseŒuent melt‚on of the ˜u€ushima ’aiichi nuclear poer plantˆ 28 “Šonitorin –roun‚ ’eformation from ‘pace”… Œ… ‰e‡artment of t€e InteriorŽŒ… ‘eological …urvey… ¤uly 2005… http://volcanoesˆussˆov/activity/metho‚s/insar/public½files/“n‘A½˜act½ ‘heet/2005‰025ˆp‚f 29 “bi‚ 30 he “o is a massive netor€ of heteroeneous ‚evices… mostly battery‰poere‚… an‚ interconnecte‚ via ireless netor€ interfacesˆ 31 “esearchers est ‘martphones for EarthŒua€e ¨arnin”… Œ… ‘eological …urvey… April 2015… http:// ˆussˆov/nesroom/articleˆasp¹“’¬„1‡†¾ˆ´Œ0Œe•5f2u„ 32 Žshahi‚i is a cro‚sourcin platform ‚evelope‚ to map of reports of post‰election violence in Ÿenya in 200‡ˆ he platform has since been use‚ in a rane of situations… inclu‚in the žaiti earthŒua€e of 2010ˆ ‘ee ˆushahi‚iˆcom 33 ‘ee http://safecastˆor/tilemap/ Swiss Re sigma No 1/2016 1†
‡eeraging technologŒ in disaster management ™pen source platforms can also improve he –lobal EarthŒua€e Šo‚el š–EŠ› ˜oun‚ation is a public‰private initiative to catastrophe mo‚elsˆ promote a‚vances in seismic haar‚ an‚ ris€ assessmentˆ –EŠ is ‚evelopin a lobal stan‚ar‚ie‚ exposure ‚atabase of property stoc€ ith ‚etaile‚ information on spatial… structural an‚ occupancy ratesˆ –EŠ has been or€in on explorin the possibility of usin ‚ata… typically buil‚in inventory… cro‚source‚ throuh a social me‚ia platform calle‚ ™pen‘treetŠap š™‘Š› to mo‚el earthŒua€e ris€ˆ„ ™‘Š is a free lobal map of human settlements štransport netor€s… buil‚ins… amenities etcˆ› an‚ the natural environmentˆ ‘imilar to ¨i€ipe‚ia… the information is contribute‚ by the eneral public… voluntarily an‚ anyhere in the orl‚ˆ “f platforms li€e ™‘Š ain traction… there ill be an accumulation of ranular location‰specific information available free of chare to the public at lareˆ “nsurers ill be able to inclu‚e these inputs into their mo‚els… turnin hat has‰to‰‚ate been a labour‰intensive ‚ata atherin process more automate‚ˆ ˜or overnments… particularly in emerin mar€ets here systematic ‚ocumentation on the construction of ne buil‚ins in rapi‚ly roin cities may be lac€in… these ‚ata can be use‚ to inform stratey on strenthenin urban resilienceˆ echnoloy can also be use‚ in insurance he aforementione‚ technoloies can also be use‚ in the ‚esin of ne insurance pro‚uct ‚esinˆ solutionsˆ ”elo is an example of ho satellite technoloy can be use‚ to trier ariculture insurance pay‰outs in reions prone to ‚rouht con‚itionsˆ Satellite pasture insurance pilot in “e•ico ‘iss e has partnere‚ ith a local ‘iss e’s Aro einsurance •ro‚uct Center has oine‚ forces ith a local insurer in player in Šexico to ‚evelop a macro‰ Šexico… •rotección Aropecuaria Compañía ‚e ‘euros… ‘A š•roAro› to ‚evelop an level in‚ex‰base‚ insurance pro‚uct for in‚ex‰base‚ insurance pro‚uct to protect cattle pro‚ucers in the event of severe severe ‚rouhtˆ ‚rouht losses to their pastures an‚ rain lan‚ˆ he pro‚uct is ‚esine‚ to allo for Œuic€ an‚ timely payouts to the insure‚ so they can buy supplementary fo‚‚er to 5 maintain their her‚sˆ ”ecause it is parameter base‚ … the insurance is operationally more efficient than tra‚itional livestoc€ insurance… hich reŒuires a livestoc€ an‚ farm inspection to establish a claimˆ he pro‚uct is base‚ on N’´“ˆ •ay‰outs he pro‚uct is base‚ on the “Normalie‚ ’ifference ´eetative “n‚ex” šN’´“›… an are triere‚ if the measure‚ N’´“ value in‚icator of veetation roth con‚itions estimate‚ from satellite imaery… an‚ falls belo a pre‰‚efine‚ threshol‚ˆ hich auments ‚rouht‰monitorin informationˆ he un‚erlyin principle is to establish a historical N’´“ ‚atabase for each ‚efine‚ pixel area on a ri‚ an‚ to calculate the averae N’´“ value for that area over the roin seasonˆ •ayouts are triere‚ if… ‚urin the insurance perio‚… the actual measure‚ N’´“ value in a pixel of a satellite imae of the area falls belo a pre‰‚efine‚ threshol‚ of the historical averae N’´“ value in that pixelˆ he threshol‚ is set at a level to reflect the onset of pasture pro‚uction losses ‚ue to ‚rouhtˆ An‚… to calibrate the in‚ex an‚ minimie the inherent basis ris€6 … measurements of biomass in ran‚om samples of roun‚ soil in the pastures are ta€en to verify the fin‚ins observe‚ in the satellite imaesˆ “t ill be pilote‚ in Šay 2016ˆ he pro‚uct is ‚ue to be pilote‚ in Šay 2016 in select states in Šexicoˆ ‘mart use of technoloy can ma€e the his example shos ho… by usin technoloy‰‚riven innovation an‚ or€in orl‚ more resilientˆ closely toether… local sta€ehol‚ers an‚ re/insurers can play an important role in ma€in the orl‚ more resilientˆ 34 “En‚‰to‰en‚ ‚emonstration of the “nventory ’ata Capture ools”… ‘lobal’uakemodel.org… ¤anuary 201„… http://ˆlobalŒua€emo‚elˆor/me‚ia/publication/’AA‰CA•ŽE‰–EЉEn‚toEn‚‰“’C‰’emo‰ 201„06‰´01ˆp‚f 35 •arametric insurance pay‰outs are triere‚ base‚ on the physical parameters of a catastrophic event… such as in‚ spee‚… location of a hurricane… or manitu‚e of an earthŒua€eˆ 36 ”asis ris€ is the ris€ that actual losses borne by the buyer of protection ill ‚eviate from the payoffs receive‚ un‚er the contractˆ 20 Swiss Re sigma No 1/2016
ables for reportin year 2015 Table 5 ƒist of ma or losses in 2015 accor‚in to loss cateory „nsured loss Number as †ictims as šin Ž‘’ m› as “an-made disasters 155 ƒ‚–€ ’€€ƒ 2’–5 —€—‚ 2ƒ–5 “aŽor ires˜ e•plosions ƒ— 1‚–’ 112‚ ƒ–‚ 5’2€ 15–ƒ žotels 1 0 100 ™ther buil‚ins 11 21 ‡„ ™il… as † 10 155 ™ther fires… explosions 10 1 0 “n‚ustry… arehouses 1 „„† ‡† “iscellaneous ƒ0 11–‚ 220’ —–ƒ 2ƒ 0–1 errorism 2 10‡2 0 ™ther miscellaneous losses 10 1102 0 ‘ocial unrest 22 2„ “ining accidents — 2–‚ ‚52 1–‚ ƒ50 1–2 “aritime disasters ‚1 —–— 2ƒ—” €–ƒ 1’”€ ƒ–’ •assener ships 20 225† 65 ’rillin platforms 5 „5 155 ™ther maritime acci‚ents „ 16„ 0 ˜reihters 2 1† 62 ™iation disasters 1’ ƒ–5 ’—5 2–’ 1001 2–” ‘pace 5 0 66„ Crashes † 6‡5 25‡ Explosions… fires 1 0 † ’amae on roun‚ 1 0 „0 Rail disasters šincl– cablewaŒs› 12 ‚–ƒ 1ƒ1 0–5 200 0–5 Natural catastrophes 1€— 5’–1 1€ ‚’5 ”‚–5 2” ”—€ ”5–’ ‘torms 102 2011 20 62„ EarthŒua€es 1 †500 510 ’rouht… bush fires… heat aves 2 „†55 20„ ˜loo‚s 55 252‡ „06 ™ther natural catastrophes 1 50 0 žail 0 06 Col‚… frost 1 21 0 Total ‚5‚ 100–0 2’ ‚5€ 100–0 ‚’ ””2 100–0 ‘ource: ‘iss e Economic esearch ¦ Consultin an‚ Cat •erilsˆ Swiss Re sigma No 1/2016 21
Tables or reporting Œear 2015 ‚” Table ’ he 20 most costly insurance losses in 2015‡ „nsured loss šin Ž‘’ m› †ictims‡ ate šstart› …ent CountrŒ 2500 to 1 12ˆ0‡ˆ2015 •ort of ian in ‰ explosions at a arehouse storin haar‚ous China 500 chemicals 20‡1 0 16ˆ02ˆ2015 ‘evere inter storm… stron in‚s… heavy snofall an‚ ice Ž‘ accumulations 1„61 1 2ˆ05ˆ2015 hun‚erstorms… torna‚oes… hail… severe floo‚in in exas an‚ Ž‘ ™€lahoma 120„ 2 0ˆ0„ˆ2015 hun‚erstorms… lare hail… torna‚oes… flash floo‚s Ž‘ 1150 ‡† 1‡ˆ0‡ˆ2015 yphoon –oni ¤apan… •hilippines… North Ÿorea 102 – 22ˆ12ˆ2015 ˜loo‚s š‘torms Eva an‚ ˜ran€› ŽŸ… “relan‚ 100† 11 0ˆ0ˆ2015 ¨inter ‘torm Ni€las† –ermany… Netherlan‚s… etˆ alˆ †† – 1‡ˆ0„ˆ2015 hun‚erstorms… lare hail… torna‚oes… flash floo‚s Ž‘ †21 „ 12ˆ0†ˆ2015 ¨il‚lan‚ fire “´alley ˜ire” Ž‘ †1„ 1 21ˆ06ˆ2015 hun‚erstorms… lare hail… torna‚oes… flash floo‚s Ž‘ ‡‡„ 0„ˆ12ˆ2015 Cumbria floo‚s š‘torm ’esmon‚› ŽŸ… Noray ‡50 „ 06ˆ05ˆ2015 orna‚o outbrea€ š122›… hail… stron in‚s… flash floo‚s Ž‘ ns „ 01ˆ0„ˆ2015 ˜ire an‚ explosion on a ‚rillin platform Šexico 55 2‡† 2‡ˆ11ˆ2015 ‘evere flash floo‚s in Chennai “n‚ia 6†1 20ˆ0„ˆ2015 ‘torm šEast Coast ƒo›… flash floo‚s… storm sure… hail Australia 6‡ „ 2„ˆ0„ˆ2015 hun‚erstorms… lare hail… torna‚oes… flash floo‚s Ž‘ 65† – 02ˆ0‡ˆ2015 hun‚erstorms… lare hail… flash floo‚s… torna‚oes Ž‘ 652 20 0ˆ10ˆ2015 orrential rains brin flash floo‚s ˜rance 66 „ 26ˆ12ˆ2015 hun‚erstorms… torna‚oes šE˜„ an‚ E˜›… bliar‚s… flash floo‚s Ž‘ ns – 1ˆ0‡ˆ2015 –as lea€ at a petrochemicals plant causes an explosion an‚ Cech epublic ensuin fire ‘ource: ‘iss e Economic esearch ¦ Consultin an‚ Cat •erilsˆ† 37 •roperty an‚ business interruption… exclu‚in liability an‚ life insurance losses³ Ž‘ natural catastrophe fiures base‚ on •roperty Claim ‘ervices… inclu‚in National ˜loo‚ “nsurance •roram šN˜“•› losses šsee pae „… “erms an‚ selection criteria” section› 38 ’ea‚ an‚ missinˆ 39 ƒoss numbers for ‘torm Ni€las are ‘iss e estimates base‚ on ‚ata from •erils A–ˆ 22 Swiss Re sigma No 1/2016
Table ” he 20 orst catastrophes in terms of victims 2015 „nsured losses †ictimsƒ0 šin Ž‘’ m› ate šstart› …ent CountrŒœregion ‡†60 160 25ˆ0„ˆ2015 EarthŒua€e šŠ ˆ‡›… avalanche on Šount Everest… aftershoc€s Nepal… “n‚ia… China… ”anla‚esh 22„‡ – 21ˆ05ˆ2015 žeatave “n‚ia 120 – 01ˆ06ˆ2015 žeatave •a€istan 1200 – 2†ˆ0ˆ2015 žeatave Europe ‡22 – 1†ˆ0„ˆ2015 ”oat carryin mirants capsies ƒibyan Arab ¤amahiriya 6† – 2ˆ0†ˆ2015 ‘tampe‚e an‚ crush at the annual ža pilrimae ‘au‚i Arabia „51 – 12ˆ01ˆ2015 ‘evere floo‚s Šalai… ŠoambiŒue… «imbabe „„2 – 01ˆ06ˆ2015 Cruise ship hit by stron in‚s an‚ rains capsies on µante China iver „00 – 1ˆ0„ˆ2015 ”oat carryin mirants capsies “taly… Še‚iterranean ‘ea †† – 26ˆ10ˆ2015 EarthŒua€e šŠ ˆ5› Afhanistan… •a€istan… “n‚ia 50 – 01ˆ10ˆ2015 ƒan‚sli‚e –uatemala 00 – 0‡ˆ02ˆ2015 ”oat carryin mirants capsies “taly… Še‚iterranean ‘ea 2†1 – 01ˆ02ˆ2015 Avalanches… lan‚sli‚es… floo‚s… heavy snofall Afhanistan 2‡† 55 2‡ˆ11ˆ2015 ‘evere flash floo‚s in Chennai “n‚ia 22„ ns 1ˆ10ˆ2015 Šetro et Airbus A21‰21 plane crashes shortly after ta€eoff Eypt allee‚ly ‚ue to bomb explosion onboar‚ 206 – 15ˆ0ˆ2015 Šonsoon floo‚s exacerbate‚ by tail en‚ of Cyclone Ÿomen “n‚ia 1† – 16ˆ0†ˆ2015 ™il tan€er overturns an‚ explo‚es³ local resi‚ents ha‚ athere‚ ‘u‚an to siphon fuel 1†0 – 0„ˆ06ˆ2015 Explosion at a as station –hana 1 2500 an‚ 12ˆ0‡ˆ2015 Explosions at a arehouse storin haar‚ous chemicals at China 500 ian in •ort 166 – 15ˆ0ˆ2015 Šonsoon floo‚s •a€istan ‘ource: ‘iss e Economic esearch ¦ Consultin an‚ Cat •erilsˆ 40 ’ea‚ an‚ missinˆ Swiss Re sigma No 1/2016 2
Tables or reporting Œear 2015 Table — Chronoloical list of all natural catastrophes 2015 Floods Number o ictimsœamount o damage ate CountrŒ …ent šhere ‚ata available›… local currency an‚/or Ž‘’ 5ˆ1ˆ–†ˆ2ˆ ”olivia… •eru… ƒa •a… ˜loo‚s cause‚ by heavy torrential rains 2 ‚ea‚ ChuŒuisaca… •otosí… ™ruro… 1000 homeless Cochabamba… ‘anta Cru 12ˆ1ˆ–1ˆ1ˆ Šalai… ŠoambiŒue… ‘evere floo‚s – 52 „ houses an‚ ‡† 110 ha of 2† ‚ea‚… 12 missin «imbabe crop lan‚ ‚amae‚ or ‚estroye‚ in Šalai… 2„‡ 620 homeless 21 ‡0 houses ‚estroye‚ an‚ 1„ 61 houses Ž‘’ „05m total ‚amae ‚amae‚ in ŠoambiŒue 2†ˆ1ˆ–12ˆ2ˆ –reece… ”ularia… ˜loo‚s… heavy snofall… stron in‚s… lan‚sli‚es „ ‚ea‚… 1 missin Šace‚onia Albania – severe ‚amae to ariculture 110 in ure‚ EŽ 6‡2m šŽ‘’ „1m› total ‚amae ‡ˆ2ˆ–1ˆ2ˆ “n‚onesia ˜loo‚s 6 ‚ea‚ ¤ava… ”ali… ¨est Nusa Ž‘’ 25m total ‚amae enara 1ˆ2ˆ–1„ˆ2ˆ Anola ˜lash floo‚s – 1‡ houses ‚estroye‚… more than 5 ‚ea‚ ƒuan‚a 2000 houses ‚amae‚ Šore than 2000 homeless 2ˆ2ˆ–1ˆˆ Ša‚aascar ˜lash floo‚s – „‡00 houses ‚estroye‚ 26 ‚ea‚ Antananarivo †ˆˆ–12ˆˆ Anola ‘evere flash floo‚s 6† ‚ea‚ ƒobito… ”enuela 10ˆˆ “ran ˜lash floo‚s – †00 houses ‚estroye‚ ‚ea‚ ”an‚ar Abbas Šore than 2000 homeless Ž‘’ 60m total ‚amae 20ˆˆ–1ˆˆ “n‚ia ˜loo‚s – 12 565 houses ‚amae‚ „„ ‚ea‚ ¤ammu an‚ Ÿashmir 25 in ure‚ 2†0 homeless “N 5bn šŽ‘’ 6m› total ‚amae 2„ˆˆ–26ˆˆ Chile ˜lash floo‚s… Copiapó iver overfloe‚ – 201 1 ‚ea‚… 16 missin Atacama… Antofaasta… houses ‚estroye‚… 625 houses ‚amae‚… Ž‘’ „50m insure‚ loss CoŒuimbo ‚amae to copper mines Ž‘’ 1ˆ5bn total ‚amae 2†ˆˆ ”urun‚i ƒan‚sli‚es cause‚ by heavy rains 10 ‚ea‚… 1 missin Šuhuta… ”u umbura 2 ‡0 homeless „ˆ„ˆ–15ˆ„ˆ China emnants of yphoon Šaysa€ brin floo‚s to 52 6 ‚ea‚ žunan… ¤ianxi tons in žunan an‚ to 1† „6 ha of croplan‚ Ž‘’ 20†m total ‚amae – more than 5000 houses ‚estroye‚… more than 10 000 houses ‚amae‚ 2‡ˆ„ˆ Afhanistan ƒan‚sli‚e cause‚ by heavy rains an‚ sno melt 52 ‚ea‚ ¤ero‰”ala… Ÿhaahan… ”a‚a€hshan •rovince ˆ5ˆ–21ˆ6ˆ anania ˜loo‚s 12 ‚ea‚ ’ar es ‘alaam… Arusha… 5000 homeless Ÿiliman aro… ana… Ÿaera †ˆ5ˆ Afhanistan ˜lash floo‚s – 1500 houses ‚estroye‚ ‚ea‚ ˜aryab 10 in ure‚ 000 homeless 10ˆ5ˆ–1‡ˆ5ˆ China ˜loo‚s – severe ‚amae to ariculture „‡ ‚ea‚ ˜u ian… ¤ianxi… žunan… Ž‘’ ‡00m total ‚amae –uan‚on… –uanxi… –uihou 1‡ˆ5ˆ Colombia ˜lash floo‚s trier lare mu‚sli‚e… ‚ebris flo † ‚ea‚ ‘alar „‡ in ure‚ 2‡ˆ5ˆ–1ˆ6ˆ China ˜loo‚s 1 ‚ea‚ –uihou… ChonŒin… Ž‘’ 500m total ‚amae ¤iansu… ˜u ian 2„ Swiss Re sigma No 1/2016
Number o ictimsœamount o damage ate CountrŒ …ent šhere ‚ata available›… local currency an‚/or Ž‘’ ˆ6ˆ–5ˆ6ˆ –hana ˜lash floo‚s 25 ‚ea‚ Accra 5000 homeless ÂŽ‘’ 12m total ‚amae 10ˆ6ˆ Nepal ˜loo‚s trier lan‚sli‚e 6 ‚ea‚ aple un ’istrict 1ˆ6ˆ–1„ˆ6ˆ –eoria ˜lash floo‚… lan‚sli‚e an‚ ensuin mu‚flo 1† ‚ea‚… missin bilisi cause‚ ´ere iver to overflo – nearby properties „5 in ure‚ floo‚e‚… partial collapse of the city’s hihay 00 homeless –Eƒ 55m šŽ‘’ 2m› total ‚amae 16ˆ6ˆ–20ˆ6ˆ China ˜loo‚s † ‚ea‚ –uihou… žubei… žunan… Ž‘’ 200m total ‚amae ¤ianxi… µunnan… «he ian 1†ˆ6ˆ–2†ˆ6ˆ “n‚ia Šonsoon floo‚s – 200 000 ha of ariculture lan‚ ‡1 ‚ea‚ ¨estern –u arat floo‚e‚ “N „0bn šŽ‘’ 60„m› total ‚amae 2„ˆ6ˆ–2‡ˆ6ˆ ”anla‚esh ˜lash floo‚s… lan‚sli‚es – 2 26† houses 22 ‚ea‚ Cox’s ”aar… Chittaon… ‚estroye‚… 0†0 houses ‚amae‚ 20 651 in ure‚ ”an‚arban Ž‘’ „0m total ‚amae 26ˆ6ˆ–2ˆˆ China ˜loo‚s 16 ‚ea‚ Anhui… ¤iansu… ‘ichuan Ž‘’ 5„5m total ‚amae 15ˆˆ–1†ˆ‡ˆ “n‚ia Šonsoon floo‚s exacerbate‚ by tail en‚ of 206 ‚ea‚ ¨est ”enal… ™‚isha… Cyclone Ÿomen a asthan… Šanipur 15ˆˆ–1†ˆ‡ˆ •a€istan Šonsoon floo‚s 166 ‚ea‚ Chitral šŸhyber •a€htun€ha›… •un ab 25ˆˆ–1†ˆ‡ˆ Nier… ”ur€ina ˜aso iver floo‚s 12 ‚ea‚ Aa‚e… ’osso… Šara‚i… 5„ in ure‚ Niamey… illabéry… ahoua… 552‡ homeless «in‚er Ž‘’ 1m total ‚amae 26ˆˆ–11ˆ‡ˆ Šyanmar š”urma› ‘evere monsoon floo‚s exacerbate‚ by tail en‚ of 125 ‚ea‚ Chin… a€hine Cyclone Ÿomen – 21 221 houses ‚estroye‚… ŠŠŸ 155bn šŽ‘’ 11†m› total ‚amae „6‡ 66 houses ‚amae‚ 1ˆ‡ˆ–5ˆ‡ˆ North Ÿorea Šonsoon šChanma› floo‚s – 1„ houses 2„ ‚ea‚… † missin North žamyon •rovince… ‚estroye‚ 5„1 homeless ‘outh žamyon •rovince… ‘outh žanhae •rovince ˆ‡ˆ Šace‚onia ˜lash floo‚s… ‚ebris flo… lan‚sli‚es 6 ‚ea‚ etovo † in ure‚ EŽ ‡0m šŽ‘’ ‡m› total ‚amae 10ˆ‡ˆ–1†ˆ‡ˆ Arentina ˜loo‚s ‚ea‚ ”uenos Aires… ‘anta ˜e Ž‘’ 1„6m total ‚amae 11ˆ‡ˆ–12ˆ‡ˆ “taly ˜lash floo‚s EŽ 102m šŽ‘’ 111m› total ‚amae Coriliano Calabro… ossano Calabro 1ˆ‡ˆ–11ˆ†ˆ “n‚ia Šonsoon rains cause floo‚s – ”rahmaputra iver 50 ‚ea‚ Assam burst its ban€s… 2000 villaes floo‚e‚ Ž‘’ 50m total ‚amae 0ˆ‡ˆ–11ˆ†ˆ Nieria ˜loo‚s cause‚ by torrential rains 0 ‚ea‚ «amfara… Anambra… ‘o€oto… 2000 homeless Ÿebbi… Ÿano †ˆ†ˆ–11ˆ†ˆ ¤apan ˜loo‚in an‚ „55 lan‚sli‚es ‚ue to tropical storm ‡ ‚ea‚ ¤oso š“bara€i›… ochii… Etau – Ÿinuaa iver burst its ban€s in the city of „6 in ure‚ Šiyai ¤oso… 16 houses ‚estroye‚… 102 houses seriously ¤•µ „0bn šŽ‘’ m› insure‚ loss ‚amae‚… 1‡ ‡‡2 houses floo‚e‚… more than Ž‘’ 500m total ‚amae 1000 people stran‚e‚ 1ˆ10ˆ–2ˆ10ˆ “n‚ia Šonsoon floo‚s – ‚amae to ariculture „† ‚ea‚ ‘outhern ami Na‚ul “N 1bn šŽ‘’ 15m› total ‚amae ˆ10ˆ–„ˆ10ˆ ˜rance orrential rains brin flash floo‚s 20 ‚ea‚ Alpes‰Šaritimes… ´ar… EŽ 600m šŽ‘’ 652m› insure‚ loss Côte ‚’Aur EŽ ‡50m šŽ‘’ †2„m› total ‚amae Swiss Re sigma No 1/2016 25
Tables or reporting Œear 2015 Number o ictimsœamount o damage ate CountrŒ …ent šhere ‚ata available›… local currency an‚/or Ž‘’ 1ˆ10ˆ–1†ˆ10ˆ “taly žeavy rains… flash floo‚s „ ‚ea‚ ”enevento šCampania›… EŽ 150m šŽ‘’ 16m› total ‚amae ƒaio… Abruo 1„ˆ10ˆ–1ˆ10ˆ ™man ˜lash floo‚s ‚ea‚ Nia… as Al ža‚‚… ”ahla 50 in ure‚ 16ˆ10ˆ–2ˆ10ˆ Aleria žeavy rains floo‚ ‘ahrai refuee camps an‚ 5 000 homeless in‚ouf south‰estern Aleria – 1 200 homes an‚ tents ‚estroye‚ 2‡ˆ10ˆ–6ˆ11ˆ “raŒ ˜lash floo‚s 5‡ ‚ea‚ ”ah‚a‚ 2650 homeless 2ˆ11ˆ–12ˆ11ˆ Ÿenya ˜lash floo‚s an‚ lan‚sli‚es 2 ‚ea‚ Naro€… ”unoma… ale€ ‡ˆ11ˆ–20ˆ11ˆ “n‚ia Šonsoon rains exacerbate‚ by remnants of a ‡1 ‚ea‚ An‚hra •ra‚esh… amil ‚eep ‚epression in the ”ay of ”enal – floo‚in in Ž‘’ 110m total ‚amae Na‚u… •u‚ucherry An‚hra •ra‚esh an‚ amil Na‚u 10ˆ11ˆ–15ˆ11ˆ China ˜loo‚s… lan‚sli‚es ‡ ‚ea‚ žunan Ž‘’ 10m total ‚amae 1ˆ11ˆ–„ˆ12ˆ ‘ri ƒan€a ˜loo‚s – 160 houses ‚estroye‚… 2656 houses ‚ea‚ ¤affna… Šullaitivu… ‚amae‚ 2600 homeless Ÿillinochchi… rincomalee… •uttalam… –ampaha 1†ˆ11ˆ–2„ˆ11ˆ ’emocratic epublic of iver floo‚ – N’‚ ili iver burst its ban€s 1 ‚ea‚ Cono ‡„‡0 homeless Ÿinshasa 25ˆ11ˆ–„ˆ12ˆ ¿atar… ‘au‚i Arabia ˜lash floo‚s 1 ‚ea‚ ’oha Ž‘’ 120m total ‚amae 2‡ˆ11ˆ “ran ˜lash floo‚s 6 ‚ea‚ “lam… ƒorestan… Ÿur‚istan… “ 000bn šŽ‘’ 2„m› total ‚amae Ÿermanshah 2‡ˆ11ˆ–„ˆ12ˆ “n‚ia ˜lash floo‚s in Chennai – 55 15 ha floo‚e‚ 2‡† ‚ea‚ Chennai šamil Na‚u›… 1000 in ure‚ An‚hra •ra‚esh… “N 50bn šŽ‘’ 55m› insure‚ loss •u‚ucherry Ž‘’ 2ˆ2bn total ‚amae 1ˆ12ˆ2015– Ÿenya ˜loo‚s – several rivers burst their ban€s ‡† ‚ea‚ 6ˆ1ˆ2016 –arissa… Šiori… ”usia an‚ in ure‚ žoma ”ay „ˆ12ˆ–6ˆ12ˆ ŽŸ… Noray ˜loo‚in as a result of ‘torm ’esmon‚ ‚ea‚ Cumbria… ƒancashire –”• 600m šŽ‘’ ‡‡„m› insure‚ loss –”• ‡00m šŽ‘’ 1ˆ2bn› total ‚amae 5ˆ12ˆ–0ˆ12ˆ Arentina… •arauay… ˜loo‚s an‚ lan‚sli‚es cause‚ by torrential rains 20 ‚ea‚ Žruuay… ”rail – ivers Žruuay an‚ •arauay burst their ban€s Ž‘’ 200m total ‚amae 22ˆ12ˆ–2‡ˆ12ˆ ŽŸ… “relan‚ ˜loo‚in as a result of storms Eva an‚ ˜ran€ –”• 00m šŽ‘’ 1ˆ0bn› insure‚ loss µor€… µor€shire… ƒancashire… – ivers Cal‚er… ibble… Ni‚‚… “rell… ™use… ˜oss… –”• ‡00m šŽ‘’ 1ˆ2bn› total ‚amae –reater Šanchester an‚ Aire burst their ban€s 2„ˆ12ˆ2015– Žnite‚ ‘tates ¨inter floo‚ alon Šississippi iver in Ši‚est 1 ‚ea‚ †ˆ1ˆ2016 Š™ š‘tˆ ƒouis›… “ƒ… A… N… – ma or floo‚in in Šissouri… “llinois ÂŽ‘’ 200m insure‚ loss Š‘… ƒA ÂŽ‘’ 600m total ‚amae 26 Swiss Re sigma No 1/2016
Storms Number o ictimsœamount o damage ate CountrŒ …ent šhere ‚ata available›… local currency an‚/or Ž‘’ „1 ‡ˆ1ˆ–11ˆ1ˆ –ermany… Noray… ŽŸ… ¨in‚storm Elon‰˜elix 2 ‚ea‚ ‘e‚en… ’enmar€ EŽ 2†m šŽ‘’ 5‡m› insure‚ loss EŽ 500m šŽ‘’ 5„m› total ‚amae 16ˆ1ˆ–1ˆ1ˆ Ša‚aascar ropical storm Che‚a – pump station responsible ‡0 ‚ea‚… † missin Analamana… ´atovavy… for ‚isposal of rain an‚ floo‚ ater collapse‚ Ž‘’ 6m total ‚amae ˜itovinany… Atsimo… exacerbatin floo‚in… 1‡1 houses ‚estroye‚ or Atsinanana… Šenabe ‚amae‚… 1 100 ha of pa‚‚y fiel‚s floo‚e‚ 1†ˆ1ˆ ™man ‘torms an‚ floo‚s Ž‘’ 221m total ‚amae Šuscat 26ˆ1ˆ–2‡ˆ1ˆ Žnite‚ ‘tates ¨inter storm šnor’easter› ith in‚s up to 2 ‚ea‚ C… ŠE… ŠA… Nž… Nµ… “ 10„ €m/h… heavy sno fall… coastal floo‚in Ž‘’ 50m insure‚ loss Ž‘’ ‡0m total ‚amae 1ˆ2ˆ–„ˆ2ˆ Žnite‚ ‘tates ¨inter storm… hih in‚s… heavy snofall an‚ 22 ‚ea‚ ŠA… Nµ… C… “ƒ… Š“… “N freein temperatures – 000 flihts cancelle‚ Ž‘’ 100–00m insure‚ loss Ž‘’ 150m total ‚amae 1ˆ2ˆ–15ˆ2ˆ Afhanistan Avalanches… lan‚sli‚es… floo‚s… heavy snofall 2†1 ‚ea‚ •an shir – 1„5„ houses ‚estroye‚… 11† houses ‚amae‚ †6 in ure‚ Ž‘’ m total ‚amae 5ˆ2ˆ–‡ˆ2ˆ ‘pain… “taly ”liar‚s… heavy snofall… stron in‚s… floo‚in ‚ea‚ – frost ‚amae to ariculture EŽ 6‡m šŽ‘’ m› insure‚ loss EŽ 150m šŽ‘’ 16m› total ‚amae ˆ2ˆ–11ˆ2ˆ Žnite‚ ‘tates ¨inter storm… heavy snofall – over 2000 flihts 2 ‚ea‚ ŠA… Nµ… C… “… Nž cancelle‚ Ž‘’ 100–00m insure‚ loss Ž‘’ 00m total ‚amae 1„ˆ2ˆ–15ˆ2ˆ Žnite‚ ‘tates ¨inter storm… heavy snofall… stron in‚s ‡ ‚ea‚ ŠA… Nµ… N¤… ´A… Š’… “… – 1600 flihts cancelle‚ Ž‘’ 00–600m insure‚ loss C… Nž… •A… ’E Ž‘’ 00m total ‚amae 16ˆ2ˆ–1ˆ2ˆ Žnite‚ ‘tates ¨inter storm… heavy sno… stron icy in‚s 10 ‚ea‚ ´A… –A… N… NC… ‘C Ž‘’ 25–100m insure‚ loss Ž‘’ 100m total ‚amae 16ˆ2ˆ–22ˆ2ˆ Žnite‚ ‘tates ‘evere inter storm… stron in‚s… heavy snofall 0 ‚ea‚ ŠA… Nµ… N… Š’… ´A… •A… an‚ ice accumulations – severe ‚amae in Ž‘’ 1–bn insure‚ loss Ÿµ… NC… Š“… “… Nž… ™ž… ‘C… Šassachusetts Ž‘’ bn total ‚amae “ƒ… ’C… ŠE… ´ 1†ˆ2ˆ–20ˆ2ˆ Australia ropical Cyclone Šarcia šCat 5› ith in‚s up to 1 ‚ea‚ µeppoon… oc€hampton… 20‡ €m/h – up to 2 000 houses ‚estroye‚ AŽ’ 5„„m šŽ‘’ †6m› insure‚ loss ”iloela… µeppoon… ”yfiel‚… AŽ’ 50m šŽ‘’ 5„6m› total ‚amae ¤ambin… Šarmor… Šonto… ¿ueenslan‚ ˆˆ–„ˆˆ anania hun‚erstorms… lare hail… flash floo‚s – 6„ „ ‚ea‚ Šsalala… ‘hinyana houses ‚estroye‚ 112 in ure‚… 500 homeless ˆˆ–5ˆˆ Žnite‚ ‘tates ¨inter storm… sleet an‚ sno fall 1 ‚ea‚ Nµ… •A… Ÿµ… ¨´… A Ž‘’ 100–00m insure‚ loss Ž‘’ 10m total ‚amae „ˆˆ–†ˆˆ “taly ¨inter storm Anton ith in‚s up to 200 €m/h… ‚ea‚ oscana… ƒiuria… Abruo… heavy snofall… floo‚s… lan‚sli‚es – severe EŽ 25„m šŽ‘’ 26m› insure‚ loss Žmbria… Šarche… •ulia… ‚isruption to transport… ‚amae to ariculture… EŽ ‡00m šŽ‘’ ‡6†m› total ‚amae Campania – explosion at as pipeline in Abruo 6ˆˆ–1‡ˆˆ “n‚ia ‘evere hailstorms… flash floo‚s – severe ‚amae 2 ‚ea‚ –u arat… •un ab… žimachal to ariculture “N bn šŽ‘’ 106m› insure‚ loss •ra‚esh… žaryana… “N 60bn šŽ‘’ †06m› total ‚amae Šaharashtra… ”ihar… Žttar •ra‚esh… Ša‚hya •ra‚esh… a asthan… ¤ammu ¦ Ÿashmir… ¨est ”enalere 41 ƒoss estimates for ¨in‚storm Elon‰˜elix from •erils A–ˆ Swiss Re sigma No 1/2016 2
Tables or reporting Œear 2015 Number o ictimsœamount o damage ate CountrŒ …ent šhere ‚ata available›… local currency an‚/or Ž‘’ †ˆˆ–15ˆˆ ´anuatu… uvalu… ‘olomon Cyclone •am šCat 5›… in‚s up to 20 €m/h – in 11 ‚ea‚ “slan‚s… Ne «ealan‚ ´anuatu… 20 000 houses ‚estroye‚ or ‚amae‚… 5 000 homeless anna… Erromano… Efate †5§ of ariculture sector ‚estroye‚ an‚ 0§ of ÂŽ‘’ 2‡m total ‚amae ater sources contaminate‚ 12ˆˆ–15ˆˆ Australia Cyclone ™lyn AŽ’ 6m šŽ‘’ „†m› insure‚ loss •ilbara… –ascoyne… AŽ’ ‡m šŽ‘’ 5m› total ‚amae –reenouh… “rin 2„ˆˆ–25ˆˆ China hun‚erstorms… flash floo‚s 2„ ‚ea‚ –uihou… ženan… ‘hanxi… 1„‡ in ure‚ ¤ianxi… ChonŒin… Ž‘’ 225m total ‚amae ‘ichuan… ‘haanxi 25ˆˆ Šexico hun‚erstorms… torna‚oes 1„ ‚ea‚ Ciu‚a‚ Acuna 22† in ure‚ 25ˆˆ–26ˆˆ Žnite‚ ‘tates hun‚erstorms ith in‚s up to 110 €m/h… 1 ‚ea‚ ™Ÿ… A… Š™… Ÿ‘ torna‚oes… hail 15 in ure‚ Ž‘’ 00–600m insure‚ loss Ž‘’ 500m total ‚amae 2†ˆˆ–1ˆˆ China ¨inter storm… heavy snofall Ž‘’ 10‡m total ‚amae ibet… Åin ian 0ˆˆ “ran hun‚erstorms… flash floo‚s in ure‚ Esfarvarin… ¿avin 0ˆˆ–1ˆ„ˆ –ermany… Netherlan‚s… ¨inter ‘torm Ni€las„2 11 ‚ea‚ Austria… ”elium… ŽŸ… EŽ †2‡m šŽ‘’ 1ˆ0†bn› insure‚ loss ‘iterlan‚ EŽ 1ˆbn šŽ‘’ 1ˆ„bn› total ‚amae 1ˆˆ–1ˆ„ˆ Šicronesia š˜e‚erate‚ yphoon Šaysa€ ith in‚s up to 250 €m/h 5 ‚ea‚ ‘tates of› – 600 houses ‚estroye‚ or ‚amae‚… ater 000 homeless Chuu€… µap sources contaminate‚… severe ‚amae to Ž‘’ 11m total ‚amae ariculture 1ˆˆ–1ˆ„ˆ Žnite‚ ‘tates hun‚erstorms… hail… flash floo‚s Ž‘’ 100–600m insure‚ loss A… Å… Aƒ… ™Ÿ… –A… N… Ž‘’ 200m total ‚amae Š‘ 1ˆ„ˆ–ˆ„ˆ ”anla‚esh Šultiple storms… torna‚oes šNor’ester› – over 5 ‚ea‚ ”ora… a shahi… Naoaon… 50 000 houses ‚amae‚ 200 in ure‚ ‘ira an … •abna… Ž‘’ „m total ‚amae ”rahmanbaria… ’ha€a 2ˆ„ˆ–ˆ„ˆ Žnite‚ ‘tates hun‚erstorms… torna‚oes… hail… flash floo‚s 2 ‚ea‚ Ÿ‘… Ÿµ… Š™ Ž‘’ 100–00m insure‚ loss Ž‘’ 20m total ‚amae „ˆ„ˆ–5ˆ„ˆ China hun‚erstorms… hail ‚ea‚ ‘ichuan in ure‚ 2500 homeless 6ˆ„ˆ–†ˆ„ˆ China hun‚erstorms… hail Ž‘’ 10m total ‚amae µunnan… ‘ichuan… –uihou… –uanxi ˆ„ˆ–10ˆ„ˆ Žnite‚ ‘tates hun‚erstorms… lare hail… torna‚oes šone E˜„›… 2 ‚ea‚ Š™… “ƒ… NC… “N… ™ž… Ÿµ… Å… flash floo‚s 22 in ure‚ “A… A… Š“… ¨´… ¨“… •A… Ž‘’ 1–bn insure‚ loss ™Ÿ… Ÿ‘… N Ž‘’ 1ˆ6bn total ‚amae 11ˆ„ˆ China ¨inter storm Ž‘’ 1„m total ‚amae žebei… ‘han‚on… ‘hanxi… ‘haanxi 16ˆ„ˆ–1ˆ„ˆ Žnite‚ ‘tates hun‚erstorms… hail… torna‚oes… flash floo‚s Ž‘’ 100–00m insure‚ loss Å… ™Ÿ… Ÿ‘ Ž‘’ 1„0m total ‚amae 1‡ˆ„ˆ–21ˆ„ˆ Žnite‚ ‘tates hun‚erstorms… lare hail… torna‚oes… flash floo‚s Ž‘’ 600m–1bn insure‚ loss Å… A… –A… •A… ‘C… Aƒ… Ž‘’ 1ˆbn total ‚amae N… Ÿ‘… ˜ƒ… ™Ÿ… Š‘ 42 ƒoss numbers for ‘torm Ni€las are ‘iss e estimates base‚ on ‚ata from •erils A–ˆ 2‡ Swiss Re sigma No 1/2016
Number o ictimsœamount o damage ate CountrŒ …ent šhere ‚ata available›… local currency an‚/or Ž‘’ 1‡ˆ„ˆ–21ˆ„ˆ China hun‚erstorms… hail… flash floo‚s 2 ‚ea‚ –uihou… ‘hanxi… ‘haanxi… Ž‘’ 250m total ‚amae –ansu 20ˆ„ˆ ”rail orna‚o ith in‚s up to 20 €m/h 2 ‚ea‚ Åanxere… ‘anta Catarina 120 in ure‚ 20ˆ„ˆ–2ˆ„ˆ Australia ¨inter storm šEast Coast ƒo›… usty in‚s… flash ‚ea‚ žunter… ‘y‚ney šNe floo‚s… storm sure… hail AŽ’ †50m šŽ‘’ 6†1m› insure‚ loss ‘outh ¨ales› ÂAŽ’ 1ˆ2bn šŽ‘’ ‡m› total ‚amae 21ˆ„ˆ “n‚ia hun‚erstorms… lare hail – 25 000 houses 100 ‚ea‚ •urnia… ”ihar ‚amae‚ Ž‘’ 150m total ‚amae 2„ˆ„ˆ–2‡ˆ„ˆ Žnite‚ ‘tates hun‚erstorms… lare hail… torna‚oes… flash floo‚s „ ‚ea‚ Å… ƒA… Ÿµ… Aƒ… –A… ˜ƒ… Š‘ Ž‘’ 600m–1bn insure‚ loss Ž‘’ †50m total ‚amae 26ˆ„ˆ–2ˆ„ˆ •a€istan hun‚erstorms… stron in‚s… flash floo‚s… „† ‚ea‚ Ÿhyber •a€htun€ha torna‚oes 26 in ure‚ •Ÿ 150m šŽ‘’ 1m› total ‚amae 2ˆ„ˆ “n‚ia… žaryana hun‚erstorms “N 6ˆ†2bn šŽ‘’ 105m› total ‚amae 0ˆ„ˆ–„ˆ5ˆ Australia ¨inter storm šEast Coast ƒo›… flash floo‚s „ ‚ea‚ ”risbane… –ol‚ Coast AŽ’ „†m šŽ‘’ 25„m› insure‚ loss š¿ueenslan‚›… Ne ‘outh AŽ’ „20m šŽ‘’ 06m› total ‚amae ¨ales ˆ5ˆ–„ˆ5ˆ Žnite‚ ‘tates hun‚erstorms… hail… torna‚oes… flash floo‚s 1 ‚ea‚ ŠN… NE… “A… ¨“… Ÿ‘ „0 in ure‚ Ž‘’ 100–00m insure‚ loss Ž‘’ 160m total ‚amae 5ˆ5ˆ–‡ˆ5ˆ China hun‚erstorms… hail „ ‚ea‚ –uanxi… –uan‚on Ž‘’ 00m total ‚amae 6ˆ5ˆ–1ˆ5ˆ Žnite‚ ‘tates orna‚o outbrea€ š122›… hail… stron in‚s… flash „ ‚ea‚ ™Ÿ… Å… C™… NE… ‘’… Ÿ‘ floo‚s – severe ‚amae in ™€lahoma an‚ exas… Ž‘’ 600m–1bn insure‚ loss – flash floo‚ in Nebras€a Ž‘’ 1ˆ„bn total ‚amae 11ˆ5ˆ ”anla‚esh hun‚erstorms… torna‚oes šNor’ester› 50 in ure‚ ˜ari‚pur… •abna 1ˆ5ˆ –ermany orna‚o outbrea€ šE˜› ith in‚s up to † in ure‚ Ÿonstan š”a‚en 250 €m/h EŽ 50m šŽ‘’ 5„m› insure‚ loss ‰¨ürttember›… Affin EŽ 55m šŽ‘’ 60m› total ‚amae š”avaria› 15ˆ5ˆ “taly hun‚erstorms š‘torm ˜erox›… lare hail… flash EŽ 10m šŽ‘’ 11m› insure‚ loss •iemonte… ƒombar‚ia floo‚s – ‚amae to ariculture… ‚amae to the EŽ 100m šŽ‘’ 10†m› total ‚amae Šilan Šalpensa airport 15ˆ5ˆ–1ˆ5ˆ Žnite‚ ‘tates hun‚erstorms… torna‚oes… hail… flash floo‚s 2 ‚ea‚ Å… ™Ÿ… Š™… C™… Ÿ‘… NE Ž‘’ 100–00m insure‚ loss Ž‘’ 160m total ‚amae 1†ˆ5ˆ “n‚ia hun‚erstorms 2 ‚ea‚ An‚hra •ra‚esh 2ˆ5ˆ ”anla‚esh hun‚erstorms – ‡ 000 houses ‚amae‚… trees 6 ‚ea‚ ’ina pur an‚ electric poles uproote‚ 50 in ure‚ Ž‘’ 1m total ‚amae 2ˆ5ˆ–2‡ˆ5ˆ Žnite‚ ‘tates hun‚erstorms… torna‚oes… hail – severe floo‚in 1 ‚ea‚ Å… ™Ÿ… Ÿ‘… ƒA… C™… A… in exas an‚ ™€lahoma Ž‘’ 1ˆ„6bn insure‚ loss –A… ™ž… ‘C Ž‘’ 2ˆ5bn total ‚amae 25ˆ5ˆ Šexico orna‚o E˜… ith in‚s up to 200 €m/h – 2„ 1 ‚ea‚ Acuña… Coahuila houses ‚estroye‚… „50 ‚amae‚ 22† in ure‚ 2‡ˆ5ˆ–0ˆ5ˆ Žnite‚ ‘tates hun‚erstorms… torna‚oes… lare hail… flash floo‚s Ž‘’ 100–00m insure‚ loss Å… ™Ÿ… C™… Ÿ‘ Ž‘’ 1‡0m total ‚amae 2†ˆ5ˆ–1ˆ6ˆ China hun‚erstorms… hail Ž‘’ 25m total ‚amae ‘hanxi… ‘haanxi… –ansu… ¤ilin… žeilon ian… Ninxia Swiss Re sigma No 1/2016 2†
Tables or reporting Œear 2015 Number o ictimsœamount o damage ate CountrŒ …ent šhere ‚ata available›… local currency an‚/or Ž‘’ 1ˆ6ˆ China Cruise ship hit by stron in‚s an‚ rains capsies „„2 ‚ea‚ ¤ianli… žubei on µante iver Ž‘’ 15m total ‚amae ˆ6ˆ–‡ˆ6ˆ Žnite‚ ‘tates hun‚erstorms… torna‚oes… lare hail… flash floo‚s Ž‘’ 00–600m insure‚ loss C™… “ƒ Ž‘’ 650m total ‚amae 10ˆ6ˆ–11ˆ6ˆ Žnite‚ ‘tates hun‚erstorms… lare hail… 1 torna‚o… flash floo‚s 1 ‚ea‚ “ƒ Ž‘’ 25–100m insure‚ loss Ž‘’ ‡0m total ‚amae 16ˆ6ˆ–1‡ˆ6ˆ Žnite‚ ‘tates emnants of ropical ‘torm ”ill cause localise‚ ‚ea‚ Å… ™Ÿ storm sure an‚ ma or river floo‚in in ™€lahoma… Ž‘’ 25–100m insure‚ loss exas an‚ ƒouisiana še‚ iver ˜loo‚› Ž‘’ 200m total ‚amae 21ˆ6ˆ–2ˆ6ˆ China hun‚erstorms… hail Ž‘’ 1„5m total ‚amae –ansu… žeilon ian… “nner Šonolia… Ninxia žui… ¿inhai… ‘haanxi 21ˆ6ˆ–25ˆ6ˆ Žnite‚ ‘tates hun‚erstorms… lare hail… torna‚oes… flash floo‚s 1 ‚ea‚ C™… “ƒ… N¤… Š’… “A… •A… ‘’… Ž‘’ 600m–1bn insure‚ loss Š“… ´A… ¨“… C… Nµ… ’E… N’ Ž‘’ 1ˆ„bn total ‚amae 2†ˆ6ˆ–0ˆ6ˆ Žnite‚ ‘tates hun‚erstorms… hail… flash floo‚s… torna‚oes Ž‘’ 100–00m insure‚ loss ŠN… •A Ž‘’ 00m total ‚amae ‡ˆˆ “taly E˜„ torna‚o ‚ea‚ ’olo… ´enice 50 in ure‚ EŽ 10m šŽ‘’ 11m› insure‚ loss EŽ 25m šŽ‘’ 2m› total ‚amae 10ˆˆ–21ˆˆ ”rail hun‚erstorms… torna‚o ith in‚s up to ‚ea‚ •araná… ‘anta Catarina… io 115 €m/h… flash floo‚s – †00 houses ‚amae‚ † in ure‚ –ran‚e ‚o ‘ul 11ˆˆ–1ˆˆ China š«houshan… yphoon Chan‰hom ith in‚s up to 1†0 €m/h 1 ‚ea‚ «he ian›… aian… ¤apan – in China severe ‚amae to ariculture 2„ in ure‚ Ž‘’ 156m insure‚ loss Ž‘’ 1ˆ„26bn total ‚amae 12ˆˆ–1„ˆˆ Žnite‚ ‘tates hun‚erstorms… lare hail… torna‚oes… lan‚sli‚es ‚ea‚… 1 missin “ƒ… ŠN… “N… Ÿµ… ™ž… N… ¨“ an‚ flash floo‚s Ž‘’ 00–600m insure‚ loss Ž‘’ 00m total ‚amae 16ˆˆ–1ˆˆ ¤apan… Šarshall “slan‚s yphoon Nan€a 2 ‚ea‚ ¤•µ 15ˆbn šŽ‘’ 12m› insure‚ loss Ž‘’ 20m total ‚amae 1ˆˆ–20ˆˆ Žnite‚ ‘tates hun‚erstorms… hail… torna‚oes… flash floo‚s Ž‘’ 25–100m insure‚ loss ŠN… “N Ž‘’ ‡0m total ‚amae 1‡ˆˆ–1†ˆˆ “ran hun‚erstorms… flash floo‚s 1 ‚ea‚… 6 missin Albor… ehran 0 in ure‚ 21ˆˆ–22ˆˆ Cana‚a hun‚erstorms… hail… torna‚oes… flash floo‚s Ž‘’ 100–00m insure‚ loss Alberta… ‘as€atchean CA’ „20m šŽ‘’ 02m› total ‚amae 2†ˆˆ–1ˆˆ ”anla‚esh Cyclone Ÿomen brins heavy rains an‚ floo‚in ‚ea‚… ‡ missin Cox’s ”aar… Chittaon… Ž‘’ „0m total ‚amae ”hola… •atua€hali… ”aruna 2ˆ‡ˆ–„ˆ‡ˆ Žnite‚ ‘tates hun‚erstorms… lare hail… flash floo‚s… torna‚oes Ž‘’ 600m–1bn insure‚ loss “ƒ… Š“… ŠA… ¨“… “… ŠE… Nµ Ž‘’ †50m total ‚amae 2ˆ‡ˆ–‡ˆ‡ˆ aian… China š˜u ian›… yphoon ‘ou‚elor ‚ea‚… 6 missin… „„0 in ure‚ Žnite‚ ‘tates… •hilippines Ž‘’ 100m insure‚ loss Northern Šariana “slan‚s Ž‘’ ˆ1bn total ‚amae „ˆ‡ˆ–5ˆ‡ˆ Cana‚a hun‚erstorms… lare hail Ž‘’ 25–100m insure‚ loss Alberta CA’ 150m šŽ‘’ 10‡m› total ‚amae 1‡ˆ‡ˆ–26ˆ‡ˆ •hilippines… ¤apan… yphoon –oni brins floo‚in an‚ lan‚sli‚es ‡2 ‚ea‚… missin… †„ in ure‚ North Ÿorea Ž‘’ 1ˆ15bn insure‚ loss Ž‘’ 1ˆ6bn total ‚amae 0 Swiss Re sigma No 1/2016
Number o ictimsœamount o damage ate CountrŒ …ent šhere ‚ata available›… local currency an‚/or Ž‘’ 2ˆ‡ˆ–1ˆ‡ˆ ’ominica… žaiti… ropical storm Eri€a 1† ‚ea‚… 16 missin Žnite‚ ‘tates Ž‘’ 15m insure‚ loss Ž‘’ „50m total ‚amae 6ˆ†ˆ “n‚ia… An‚hra •ra‚esh hun‚erstorms… lihtnin 2 ‚ea‚ ‡ˆ†ˆ–†ˆ†ˆ ƒebanon… ‘yrian Arab ‘evere san‚storm 6 ‚ea‚ epublic „ 0 in ure‚ 1„ˆ†ˆ–1†ˆ†ˆ ´ietnam… Cambo‚ia… ropical storm ´amco brins floo‚s 1 ‚ea‚ hailan‚ Ž‘’ 150m total ‚amae 25ˆ†ˆ–2‡ˆ†ˆ aian… China š˜u ian… yphoon ’u uan – 5 000 ha of croplan‚ floo‚e‚ ‚ea‚… 2 missin «he ian›… •hilippines 6 in ure‚ Ž‘’ ‡m insure‚ loss Ž‘’ 516m total ‚amae 1ˆ10ˆ–„ˆ10ˆ ”ahamas žurricane ¤oaŒuin – caro ship oes missin ‚ea‚ ƒon “slan‚… ae‚ “slan‚ Ž‘’ 61m insure‚ loss Ž‘’ †0m total ‚amae 1ˆ10ˆ–1ˆ10ˆ Žnite‚ ‘tates žeavy floo‚in in ‘outh Carolina ‚ue to žurricane 25 ‚ea‚ ‘C… NC ¤oaŒuin Ž‘’ 00m insure‚ loss Ž‘’ 1ˆ5bn total ‚amae 2ˆ10ˆ–„ˆ10ˆ China š–uan‚on… yphoon Šu iae – 562 00 ha of croplan‚ Ž‘’ „00m insure‚ loss –uanxi… žainan›… floo‚e‚ Ž‘’ „ˆ52bn total ‚amae •hilippines 2ˆ10ˆ–6ˆ10ˆ Žnite‚ ‘tates hun‚erstorms… flash floo‚s Ž‘’ 00–600m insure‚ loss ‘C… NC… ´A… N¤… Š’… ’E Ž‘’ 500m total ‚amae ˆ10ˆ–„ˆ10ˆ Žnite‚ ‘tates hun‚erstorms… hail Ž‘’ 25–100m insure‚ loss NŠ Ž‘’ 110m total ‚amae ˆ10ˆ–„ˆ10ˆ “n‚ia… Šaharashtra hun‚erstorms 2† ‚ea‚ 5ˆ10ˆ–ˆ10ˆ Žnite‚ ‘tates hun‚erstorms… lare hail… torrential rain Ž‘’ 25–100m insure‚ loss El •aso… Å Ž‘’ 100m total ‚amae 1‡ˆ10ˆ–1†ˆ10ˆ •hilippines yphhon Ÿoppu šCat „› ith in‚s up to „‡ ‚ea‚… „ missin ƒuon 2„0 €m/h… heavy floo‚in… lan‚sli‚es – 1‡ †5 ‡ in ure‚ houses ‚estroye‚… 11‡ ‡‡5 houses ‚amae‚… •ž• 1„bn šŽ‘’ 2†‡m› total ‚amae 0 000 ha of croplan‚ ‚estroye‚ 20ˆ10ˆ–2ˆ10ˆ Žnite‚ ‘tates hun‚erstorms… hail… flash floo‚s Ž‘’ 100–00m insure‚ loss Å… NŠ Ž‘’ 20m total ‚amae 22ˆ10ˆ–26ˆ10ˆ Šexico… šCuixmala… žurricane •atricia brins in‚ an‚ floo‚ ‚amae 1„ ‚ea‚ ¤alisco›… Žnite‚ ‘tates šÅ› to Šexico an‚ exas – freiht train ‚erails in Ž‘ Ž‘’ „m insure‚ loss Ž‘’ ‡2m total ‚amae 2„ˆ10ˆ–25ˆ10ˆ Eypt hun‚erstorms… hail… flash floo‚s – ‚amae to the 6 ‚ea‚ Alexan‚ria city’s seae system Ž‘’ 100m total ‚amae 2†ˆ10ˆ–1ˆ10ˆ Žnite‚ ‘tates hun‚erstorms… hail… flash floo‚s Ž‘’ 100–00m insure‚ loss Å… ƒA Ž‘’ 20m total ‚amae 1ˆ11ˆ–ˆ11ˆ µemen Cyclone Chapala ‡ ‚ea‚ Šu€alla… ‘ocotra 65 in ure‚ ˆ11ˆ–„ˆ11ˆ Eypt hun‚erstorms… flash floo‚s 25 ‚ea‚ ”eheira 5 in ure‚ ‡ˆ11ˆ–10ˆ11ˆ µemen Cyclone Šeh – ‡00 houses… 1 poer station 2„ ‚ea‚ ‘ocotra… A‚en ‚amae‚ 60 in ure‚ 16ˆ11ˆ–1‡ˆ11ˆ Žnite‚ ‘tates hun‚erstorms… flash floo‚s Ž‘’ 100–00m insure‚ loss ¨A… “’ Ž‘’ 10m total ‚amae 22ˆ11ˆ–2ˆ11ˆ China ¨inter storm „ ‚ea‚ ”ei in… ian in CNµ 1ˆbn šŽ‘’ 262m› total ‚amae 26ˆ11ˆ–0ˆ11ˆ Žnite‚ ‘tates ¨inter storm ith freein rains an‚ floo‚in 1‡ ‚ea‚ Å… ™Ÿ… Ÿ‘ Ž‘’ 25–100m insure‚ loss Ž‘’ 1„0m total ‚amae Swiss Re sigma No 1/2016 1
Tables or reporting Œear 2015 Number o ictimsœamount o damage ate CountrŒ …ent šhere ‚ata available›… local currency an‚/or Ž‘’ 1„ˆ12ˆ–16ˆ12ˆ •hilippines yphoon Šelor brins floo‚in an‚ lan‚sli‚es „2 ‚ea‚… „ missin Šin‚oro… omblon – †‡ 1 houses ‚estroye‚… 1‡1 116 houses 2„ in ure‚ ‚amae‚ 2‡ 22 homeless •ž• 10ˆ5„bn šŽ‘’ 225m› total ‚amae 16ˆ12ˆ Australia hun‚erstorms… E˜2 torna‚o ith in‚s up to 6 in ure‚ ‘y‚ney… Ÿurnell 200 €m/h… flash floo‚s – ‚esalination plant in AŽ’ 202m šŽ‘’ 1„m› insure‚ loss Ÿurnell ‚amae‚ AŽ’ 250m šŽ‘’ 1‡2m› total ‚amae 2ˆ12ˆ–2„ˆ12ˆ Žnite‚ ‘tates hun‚erstorms… torna‚oes… hail… flash floo‚s ‚ea‚ –A… N… “N… Aƒ… Š‘… “ƒ… A Ž‘’ 100–00m insure‚ loss Ž‘’ 1‡0m total ‚amae 26ˆ12ˆ–2‡ˆ12ˆ Žnite‚ ‘tates hun‚erstorms… torna‚oes šE˜„ an‚ E˜›… „ ‚ea‚ Å… Š™… “ƒ… ™Ÿ… –A… “N bliar‚s… flash floo‚s Ž‘’ 600m –1bn insure‚ loss Ž‘’ †00m total ‚amae …arthˆua‰es Number o ictimsœamount o damage ate CountrŒ …ent šhere ‚ata available›… local currency an‚/or Ž‘’ 1ˆˆ China EarthŒua€e šŠ 5ˆ2› – 220 houses ‚estroye‚… 2 in ure‚ Nansan… Canyuan… 15 ‡00 houses severely ‚amae‚ 2000 homeless –enma Ž‘’ 15m total ‚amae 15ˆ„ˆ China EarthŒua€e šŠ „ˆ5› 1 ‚ea‚… 1 in ure‚ µanhuan 5000 homeless 25ˆ„ˆ Nepal šƒam un… EarthŒua€e šŠ ˆ‡›… avalanche on Šount Everest… ‡†5 ‚ea‚… missin Ÿathman‚u›… “n‚ia… China… ma or aftershoc€s – in Nepal „†‡ ‡52 houses 2„ 000 in ure‚ ”anla‚esh ‚estroye‚… 256 6† houses ‚amae‚… severe Ž‘’ 160m insure‚ loss ‚amae to the country’s cultural heritae Ž‘’ 6bn total ‚amae 12ˆ5ˆ Nepal šŸo‚ari›… “n‚ia… EarthŒua€e šŠ ˆ› 11 ‚ea‚ ”anla‚esh 62‡ in ure‚ ˆˆ China EarthŒua€e šŠ 6ˆ„› ‚ea‚ µil€iŒi… Åin ian 1 in ure‚ 16ˆ†ˆ Chile EarthŒua€e šŠ ‡ˆ› triers tsunami – 2 05 15 ‚ea‚… 1 missin… 1„ in ure‚ “llapel houses ‚estroye‚… 2 „ houses severely 600 homeless ‚amae‚… 01 houses slihtly ‚amae‚… Ž‘’ 50m insure‚ loss 1†1 boats ‚estroye‚ Ž‘’ 1bn total ‚amae 2„ˆ†ˆ “n‚onesia… ‘oron EarthŒua€e šŠ 6ˆ6› – 200 houses ‚amae‚ 62 in ure‚ 26ˆ10ˆ Afhanistan… •a€istan… EarthŒua€e šŠ ˆ5› – 2 6‡1 houses ‚estroye‚… †† ‚ea‚ “n‚ia † 12 houses ‚amae‚ 2 1 in ure‚ ”a‚a€shan… žin‚u Ÿush „ˆ11ˆ “n‚onesia EarthŒua€e šŠ 6ˆ› – 1 6‡ houses ‚estroye‚ or in ure‚ ’ili… imor ‚amae‚ Šore than 2000 homeless “’ „†ˆ5bn šŽ‘’ „m› total ‚amae 16ˆ11ˆ–2ˆ11ˆ “n‚onesia remors – 2 houses heavily ‚amae‚… 1† 2000 homeless ¨est žalmahera ’istrict… me‚ium ‚amae‚… 50„ slihtly ‚amae‚ North Šalu€u •rovince 1ˆ11ˆ Ÿyrystan EarthŒua€e šŠ 5ˆ› – 222 houses ‚estroye‚… 2000 homeless ™sh ‡6 houses severely ‚amae‚… 1 „01 houses Ž‘’ 12m total ‚amae mo‚erately ‚amae‚ ˆ12ˆ a i€istan EarthŒua€e šŠ ˆ2› – more than 500 houses 2 ‚ea‚… 1 in ure‚ Šurhob… –orno ‚estroye‚… † houses ‚amae‚ Šore than 2000 homeless ‰”a‚a€hshan Ž‘’ 5m total ‚amae 25ˆ12ˆ Afhanistan… •a€istan EarthŒua€e šŠ 6ˆ› 2 ‚ea‚ Ash€asham † in ure‚ 2 Swiss Re sigma No 1/2016
Cold˜ rost Number o ictimsœamount o damage ate CountrŒ …ent šhere ‚ata available›… local currency an‚/or Ž‘’ 6ˆˆ–5ˆ‡ˆ •eru ”liar‚s… col‚ spell ith temperatures ‚on to 21 ‚ea‚ •uno… Apurimac… ‰20°C… severe frost – 52† houses ‚amae‚… 100 homeless Ayacucho… AreŒuipa… 1‡†„ ha of aricultural lan‚ ‚amae‚… 1162 ha of Ž‘’ †„m total ‚amae Cusco… žuancavelica… ƒima… crops lost… †12 00 livestoc€ perishe‚ ŠoŒueua… •asco… acna rought˜ bush ires˜ heat waes Number o ictimsœamount o damage ate CountrŒœregion …ent šhere ‚ata available›… local currency an‚/or Ž‘’ 1ˆ1ˆ–1ˆ12ˆ Žnite‚ ‘tates ’rouht in estern states Ž‘’ 1ˆ‡bn total ‚amae CA… N´… ™… ¨A… “’… Š… Ž… A« 1ˆ1ˆ–1ˆ12ˆ –uatemala… žon‚uras… ‘evere ‚rouht in Central America an‚ the ÈŽ‘’ 600m total ‚amae žaiti… ’ominican epublic… Caribbean ¤amaica… ‘aint ƒucia… El ‘alva‚or 1ˆ1ˆ–1ˆ12ˆ ‘outh Africa… ”otsana… ‘evere ‚rouht in southern Africa ÂŽ‘’ 500m total ‚amae Namibia 2ˆ1ˆ–‡ˆ1ˆ Australia ”ushfires šA‚elai‚e žills› – 2 houses… she‚s an‚ 1„ in ure‚ Šount ƒofty anes… farms ‚estroye‚… 12 500 ha of bush ‚estroye‚… AŽ’ 62m šŽ‘’ „5m› insure‚ loss A‚elai‚e š‘outh Australia› †00 animals perishe‚ AŽ’ 0m šŽ‘’ 51m› total ‚amae 12ˆ„ˆ–15ˆ„ˆ ussia ¨il‚fires – 1000 houses ‚estroye‚ or ‚amae‚ „ ‚ea‚ Ÿha€assia Ž” †bn šŽ‘’ 12m› total ‚amae 16ˆ„ˆ–1‡ˆ12ˆ Europe ‘evere ‚rouht in Europe ÈEŽ 2ˆbn šŽ‘’ 2ˆ„††bn› total ‚amae 1ˆ5ˆ–1ˆ10ˆ China ‘evere ‚rouht in northeastern China CNµ 2ˆ‡‡bn šŽ‘’ „„„m› insure‚ loss “nner Šonolia… ƒiaonin… CNµ 16bn šŽ‘’ 2ˆ„6„bn› total ‚amae ¤ilin 11ˆ5ˆ–ˆ5ˆ ¤apan žeatave 2 ‚ea‚ „‡0 in ure‚ 21ˆ5ˆ–2‡ˆ5ˆ “n‚ia žeatave 22„‡ ‚ea‚ An‚hra •ra‚esh… elanana 1ˆ6ˆ–2„ˆ6ˆ •a€istan žeatave 120 ‚ea‚ Ÿarachi… ‘in‚h 1ˆ6ˆ–1ˆ12ˆ •apua Ne –uinea •rolone‚ hih temperatures… severe ‚rouht 2 ‚ea‚ žihlan‚s 12ˆˆ–15ˆˆ ¤apan žeatave 5 ‚ea‚ 200 in ure‚ 2†ˆˆ–†ˆ‡ˆ Europe žeatave 1200 ‚ea‚ ˆ‡ˆ–†ˆ‡ˆ ¤apan žeatave 2 ‚ea‚ ™sa€a 11 1‡ in ure‚ 5ˆ‡ˆ–2ˆ10ˆ “n‚ia ‘evere ‚rouht Ž‘’ 120m insure‚ loss ™‚isha Ž‘’ 1ˆ5bn total ‚amae 6ˆ‡ˆ–1‡ˆ‡ˆ Eypt žeatave 110 ‚ea‚ Cairo 66 in ure‚ 1ˆ†ˆ–11ˆ11ˆ “n‚onesia ¨il‚fires trier ‚ense smo hae 1† ‚ea‚ ¤ambi… iau… ‘outh 500 000 in ure‚ ‘umatera š‘umatra›… Ž‘’ 1bn total ‚amae Ÿalimantan š”orneo› Swiss Re sigma No 1/2016
Tables or reporting Œear 2015 Number o ictimsœamount o damage ate CountrŒ …ent šhere ‚ata available›… local currency an‚/or Ž‘’ †ˆ†ˆ–1„ˆ†ˆ Žnite‚ ‘tates ¨il‚lan‚ fire “”utte ˜ire” – „5 houses ‚estroye‚… 2 ‚ea‚… 1 in ure‚ Ama‚or… Calaveras šCA› „5 structures ‚amae‚… 2‡ 6† ha of forest Ž‘’ 00–600m insure‚ loss ‚estroye‚ Ž‘’ „00m total ‚amae 12ˆ†ˆ–1„ˆ†ˆ Žnite‚ ‘tates ¨il‚lan‚ fire “´alley ˜ire” – 12‡0 houses… „ ‚ea‚ ƒa€e… Napa… ‘onoma šCA› 2 multi‰family structures… 66 commercial „ in ure‚ properties… an‚ 5‡5 other minor structures Ž‘’ 600m–1bn insure‚ loss ‚estroye‚ˆ „1 houses… commercial buil‚ins Ž‘’ 1ˆ„bn total ‚amae ‚amae‚… 0 ‡ ha of forest ‚estroye‚ 1„ˆ†ˆ–1ˆ†ˆ Colombia ‘evere il‚fires C™• „6bn šŽ‘’ 150m› total ‚amae ”oyacá… Cun‚inamarca 15ˆ11ˆ–21ˆ11ˆ Australia ƒare bushfires ‚estroy 1„5 000 ha of lan‚ „ ‚ea‚ Esperance… ¨estern inclu‚in vast areas of croppin lan‚ AŽ’ 1m šŽ‘’ 12m› insure‚ loss Australia AŽ’ 150m šŽ‘’ 10†m› total ‚amae 25ˆ11ˆ–2‡ˆ11ˆ Australia •inerey ”ushfires – ‡5 000 ha of aricultural lan‚ 2 ‚ea‚… 1 in ure‚ ”ala€lava… oseorthy… burnt AŽ’ 10m šŽ‘’ 12„m› insure‚ loss ‘outh Australia AŽ’ 200m šŽ‘’ 1„6m› total ‚amae 25ˆ12ˆ–26ˆ12ˆ Australia –reat ™cean oa‚ bushfires – 116 houses AŽ’ ‡m šŽ‘’ 6m› insure‚ loss ´ictoria ‚estroye‚ AŽ’ 100m šŽ‘’ m› total ‚amae ‹ail Number o ictimsœamount o damage ate CountrŒ …ent šhere ‚ata available›… local currency an‚/or Ž‘’ ˆ„ˆ “n‚ia žailstorm “N ‡bn šŽ‘’ 121m› total ‚amae ”areilly… Žttar •ra‚esh 25ˆ„ˆ Australia Anac ’ay hailstorm – ‚amae to commercial AŽ’ „21m šŽ‘’ 06m› insure‚ loss ‘y‚ney facilities an‚ to ariculture AŽ’ 500m šŽ‘’ 6„m› total ‚amae 5ˆ†ˆ “taly ‘eries of hailstorms cause ‚amae to ariculture 2 in ure‚ •ouoli šCampania›… an‚ vehicles EŽ †0m šŽ‘’ †‡m› total ‚amae Emilia omana… ƒombar‚ia žther natural catastrophes Number o ictimsœamount o damage ate CountrŒ …ent šhere ‚ata available›… local currency an‚/or Ž‘’ 1ˆ10ˆ –uatemala ƒan‚sli‚e – houses severely ‚amae‚… 2‡0 ‚ea‚… 0 missin El Cambray ““… ‘anta 111 houses ‚amae‚ 2 in ure‚ Catarina •inula „0 homeless Ž‘’ 5m total ‚amae Note: able ‡ uses loss ranes for Ž‘ natural catastrophes as ‚efine‚ by •roperty Claim ‘ervicesˆ ‘ource: ‘iss e Economic esearch ¦ Consultin an‚ Cat •erilsˆ „ Swiss Re sigma No 1/2016
Table € Chronoloical list of all man‰ma‚e ‚isasters 2015 ™iation disasters Number o ictims ate CountrŒ …ent šhere ‚ata available› 1‡ˆ1ˆ ‘yrian Arab epublic ‘yrian Air ˜orce Antonov 26 plane crashes on 0 ‚ea‚ Abu a‚h ’huhur lan‚in approach „ˆ2ˆ aian ransAsia Airays A 2‰600 plane crashes „ ‚ea‚ aipei after ta€e off 2„ˆˆ ˜rance –ermanins Airbus A20‰211 crashes ‚ue to 150 ‚ea‚ ”arcelonnette pilot suici‚e 2ˆ„ˆ µemen µemenia ”oein „‘• ‚estroye‚ ‚urin a un A‚en battle at A‚en “nternational Airport 12ˆ„ˆ ‘pace ƒoss of contact ith Eypt‰‘at 2… a remote sensin satellite 1„ˆ„ˆ ¤apan Asiana Airlines Airbus A20‰22 plane ritten off 2 in ure‚ žiroshima after har‚ lan‚in 25ˆ„ˆ ur€ey A ur€ish Airlines Airbus A20‰22 catches fire “stanbul on lan‚in 2‡ˆ„ˆ ‘pace ussian “‘‘ resupply craft lost ‚ue to early separation from roc€et †ˆ5ˆ ‘pace Airbus A„00Š plane crashes ‚urin a test fliht „ ‚ea‚… 2 in ure‚ 16ˆ5ˆ ‘pace Šexsat satellite crashes ‚ue to faulty launch 2‡ˆ6ˆ ‘pace NA‘A “‘‘ resupply roc€et explo‚es shortly after Cape Canaveral launch 0ˆ6ˆ “n‚onesia N“‰AŽ ƒoc€hee‚ C‰10” žercules plane crashes 1† ‚ea‚ Še‚an shortly after ta€eoff 16ˆ‡ˆ “n‚onesia riana Air ‘ervice A „2‰00 crashes before 5„ ‚ea‚ ™€sibil lan‚in 1ˆ10ˆ Eypt Šetro et Airbus A21‰21 plane crashes shortly 22„ ‚ea‚ Al‰Arish… ‘inai after ta€eoff allee‚ly ‚ue to bomb onboar‚ „ˆ11ˆ ‘u‚an Allie‚ ‘ervices ƒt‚ Antonov 12”Ÿ caro plane „1 ‚ea‚ ¤uba crashes shortly after ta€eoff 21ˆ11ˆ ‘pace ƒoss of contact ith Amos 5… a commercial satellite “aŽor ires˜ e•plosions Number o ictims ate CountrŒ …ent šhere ‚ata available› 10ˆ1ˆ Žnite‚ ‘tates… ™hio Explosion an‚ fire at an oil refinery 10ˆ1ˆ ‘outh Ÿorea ˜ire at a multi‰storey apartment bloc€ 5 ‚ea‚ Ži eonbu 125 in ure‚ 11ˆ1ˆ ”anla‚esh ˜ire in a shanty ton 2 ‚ea‚ ’ha€a 2000 homeless 2†ˆ1ˆ Šexico –as lea€ causes an explosion at a chil‚ren’s 2 ‚ea‚ Šexico City hospital 2 in ure‚ 5ˆ2ˆ ŽŸ ˜ire at an electrical plant ‘taverton 16ˆ2ˆ –ermany ˜ire at an animal fee‚ factory echterfel‚ ˆˆ Žnite‚ ‘tates ˜ire at a lass‰ma€in facility ’uryea… •A 11ˆˆ ussia ˜ire at a shoppin centre 1 ‚ea‚ Ÿaan 55 in ure‚ 12ˆˆ ”anla‚esh Žn‚er‰construction roof at a cement factory 5 ‚ea‚ Šonla… ”aerhat collapses 50 in ure‚ Swiss Re sigma No 1/2016 5
Tables or reporting Œear 2015 Number o ictims ate CountrŒ …ent šhere ‚ata available› 1†ˆ„ˆ ”rail ˜ire at a pharmaceuticals company ‘ao •aulo 2†ˆ„ˆ ŽŸ ˜ire at a heritae palace –uil‚for‚… ‘urrey 1„ˆ5ˆ •hilippines ˜ire at a footear factory 2 ‚ea‚ ´alenuela… Šanila 1†ˆ5ˆ Aerbai an ˜ire at a resi‚ential buil‚in 15 ‚ea‚ ”a€u 6 in ure‚ 1†ˆ5ˆ Žnite‚ ‘tates ™il spill into channel an‚ on to beaches after ‘anta ”arbara onshore pipeline bursts 25ˆ5ˆ China ˜ire at a home for the el‚erly ‡ ‚ea‚ •in‚inshan… ženan 25ˆ5ˆ ‘outh Ÿorea ˜ire at a clothin arehouse 1 ‚ea‚ ‘eoul 1ˆ5ˆ ‘yrian Arab epublic –as explosion in a hospital „0 ‚ea‚ ¿amishli „ˆ6ˆ –hana Explosion at a as station 1†0 ‚ea‚ Accra 60 in ure‚ 10ˆ6ˆ “srael ˜ire at a chemical plant ’imona 2ˆ6ˆ aian Explosion at a recreational ater par€ † ‚ea‚ Ne aipei City „†0 in ure‚ 5ˆˆ ¿atar “•unch‰throuh” inci‚ent at Al ‘haheen oil ri Al ‘haheen 2‡ˆˆ Eypt Explosion an‚ fire at a furniture factory 25 ‚ea‚ ¿alioubiya 22 in ure‚ 12ˆ‡ˆ China Explosions at a arehouse storin haar‚ous 165 ‚ea‚… ‡ missin ian in chemicals at ian in •ort – 0„ buil‚ins… 12 „2‡ †‡ in ure‚ vehicles an‚ 5 containers ‚estroye‚ 1ˆ‡ˆ Cech epublic –as lea€ at a petrochemicals plant causes an 5 in ure‚ ƒitvínov explosion an‚ ensuin fire 25ˆ‡ˆ –ermany ˜ire at a hy‚raulics company Neueiler 2†ˆ‡ˆ Cana‚a ˜ire an‚ explosion at an oil san‚s facility Šil‚re‚ ƒa€e… Alberta 0ˆ‡ˆ ‘au‚i Arabia ˜ire at a multi‰storey resi‚ential complex 10 ‚ea‚ Ÿhobar 25† in ure‚ ‡ˆ†ˆ ”elium ˜ire at a foo‚ processin factory 11 in ure‚ Nieu€er€e 10ˆ†ˆ ŽŸ ˜ire at a foo‚ processin factory –laso 11ˆ†ˆ ‘au‚i Arabia Construction crane at a mosŒue collapses ‚urin 111 ‚ea‚ Šecca a storm †„ in ure‚ 1ˆ†ˆ “n‚ia Explosions at a arehouse storin elinite an‚ 10„ ‚ea‚ •etlaa‚… ¤habua šŠa‚hya at a restaurant locate‚ in the same buil‚in •ra‚esh› 16ˆ†ˆ China Ÿin‚erarten chil‚ren trappe‚ by a fire in their 10„ in ure‚ Nin‚e City… ˜u ian buil‚in 0ˆ†ˆ Netherlan‚s ˜ire at a chemical plant –eleen 1†ˆ10ˆ Ž€raine ˜ire an‚ explosion at an ammunition ‚epot „ ‚ea‚ ‘vatovo ‚estroy or ‚amae 10† houses 5„ in ure‚ 0‡2 homeless 2ˆ10ˆ Žnite‚ ‘tates ƒare as lea€ at a storae facility – state of 660 in ure‚ Aliso Canyon emerency ‚eclare‚ 2 months after inci‚ent… 5„ househol‚s temporarily relocate‚ 0ˆ10ˆ omania ˜ire at a nihtclub… triere‚ by fireor€s 56 ‚ea‚ ”ucharest 166 in ure‚ 6 Swiss Re sigma No 1/2016
Number o ictims ate CountrŒ …ent šhere ‚ata available› „ˆ11ˆ •a€istan ‘hoppin bas factory buil‚in collapses „5 ‚ea‚ ƒahore 10 in ure‚ 15ˆ11ˆ Šalta –lass banister in a nihtclub collapses 1 in ure‚ ´alletta 2„ˆ11ˆ Aleria ˜ire in a mirant camp 1‡ ‚ea‚ ™uarla 50 in ure‚ 25ˆ11ˆ •hilippines ˜ire in a shanty ton… ‚estroys ‡00 houses 2500 homeless Šanila 2†ˆ11ˆ ‘outh Africa ˜ire in a shanty ton ‚estroys 1000 homes 2 ‚ea‚ „000 homeless „ˆ12ˆ •hilippines ˜ire in a shanty ton 5000 homeless ‘taˆ Cru… Šanila 5ˆ12ˆ Aerbai an ˜ire at an oil platform ‚ea‚… 2 missin Caspian ‘ea ˆ12ˆ “n‚ia ˜ire an‚ as explosions in a shanty ton 2 ‚ea‚ Ÿan‚ivali… Šumbai 11 in ure‚ 000 homeless 1ˆ12ˆ ussia ˜ire at a psychiatric hospital 2 ‚ea‚ ´oroneh 2„ˆ12ˆ ‘au‚i Arabia ˜ire at a hospital 2„ ‚ea‚ ¤aan… ¤ian eion 12 in ure‚ 2„ˆ12ˆ Nieria Explosion at a as plant 100 ‚ea‚ Nnei 1ˆ12ˆ Žnite‚ Arab Emirates ˜ire at a hotel at time of Ne µear’s Eve 1„ in ure‚ ’ubai celebrations “aritime disasters Number o ictims ate CountrŒ …ent šhere ‚ata available› 2ˆ1ˆ North •acific ™cean ”ul€ carrier sin€s off the coast of ´ietnam 2 ‚ea‚… 16 missin ´un au 1 in ure‚ 1ˆ1ˆ Central African epublic ”oat catches fire an‚ capsies on iver ™ubanui 10‡ ‚ea‚… 1„ missin N‚imba… „2 €m from ”anui 16ˆ1ˆ China uboat sin€s ‚urin a trial voyae on the µante 22 ‚ea‚ «han iaan… ¤iansu iver ˆ2ˆ µemen ”oat carryin mirants capsies in rouh eather 5 missin ”ab el‰Šan‚eb ‡ˆ2ˆ “taly ”oat carryin mirants capsies 00 ‚ea‚ ƒampe‚usa 11ˆ2ˆ ”rail Explosion at a ‚rillin platform 6 ‚ea‚… missin Espirito ‘anto ”asin 10 in ure‚ 1„ˆ2ˆ ’emocratic epublic of ”oat capsies on ƒa€e ananyi€a 100 missin Cono ƒa€e ananyi€a 22ˆ2ˆ ”anla‚esh •assener ferry sin€s in the iver •a‚ma after 0 ‚ea‚ Šani€an ‚istrict bein hit by a caro vessel 1ˆˆ Šyanmar… “n‚ian ™cean •assener ferry capsies in rouh eather „ ‚ea‚… 12 missin Naun ’a –yi “slan‚ 2‡ˆˆ –reece ˜ire onboar‚ a hih‰spee‚ ferry hile ‚oc€e‚ at 1 ‚ea‚ ’rapetsona shipyar‚ 1ˆ„ˆ Šexico ˜ire an‚ explosion on a ‚rillin platform „ ‚ea‚ ”ay of Campeche 16 in ure‚ Swiss Re sigma No 1/2016
Tables or reporting Œear 2015 Number o ictims ate CountrŒ …ent šhere ‚ata available› 1ˆ„ˆ ussia… North •acific ˜ishin vessel sin€s after hittin ice 5 ‚ea‚… 12 missin ™cean… Ÿamchat€a •eninsula… ‘ea of ™€hots€ 1ˆ„ˆ Še‚iterranean ‘ea ”oat carryin mirants capsies „00 missin “taly 16ˆ„ˆ Še‚iterranean ‘ea ”oat carryin mirants capsies „1 missin off ‘icily 1†ˆ„ˆ ƒibyan Arab ¤amahiriya ”oat carryin mirants capsies 2„ ‚ea‚… †‡ missin «uarah… ripoli 2‡ˆ„ˆ Še‚iterranean ‘ea ˜ire on boar‚ a passener ferry ‘pain… Ša orca 5ˆ5ˆ Šexico ™ffshore oil ri tilts ‚urin maintenance 2 ‚ea‚ ”ay of Campeche operations 10 in ure‚ 15ˆ5ˆ ˜al€lan‚ “slan‚s ”loout at an oil ri 11ˆ6ˆ “n‚ian ™cean •assener ferry sin€s in un€non circumstances 22 missin “n‚onesia… Ša€assar ‘trait 2ˆ6ˆ ur€ey •assener vessel colli‚es ith tan€er³ both ’ar‚anelles ‘trait ‚amae‚ 2ˆˆ •acific ™cean ˜erry capsies in rouh eather 61 ‚ea‚ •hilippines… ™rmoc City 0ˆˆ “n‚ian ™cean hree fishin boats capsie in rouh eather „ ‚ea‚… 2„ missin ”anla‚esh ‘a‚ar… ”hola ˆ†ˆ “n‚ian ™cean… Šalaysia ”oat carryin mirant or€ers capsies in rouh 61 ‚ea‚ ‘aba€ ”ernam… ‘elanor eather 1ˆ†ˆ Še‚iterranean ‘ea ”oat carryin mirants capsies „ ‚ea‚ –reece… ˜arma€onisi “slan‚ 15ˆ†ˆ Še‚iterranean ‘ea ”oat carryin mirants capsies 22 ‚ea‚ –reece… Ÿos 20ˆ†ˆ “n‚ian ™cean ˜ive fishin boats capsie in rouh eather „ missin ”anla‚esh… •atua€hali 20ˆ†ˆ “n‚ian ™cean ˜ive fishin boats capsie in rouh eather 20 missin ”anla‚esh… ”aruna 25ˆ10ˆ North •acific ™cean žih‰spee‚ ferry hits floatin ob ect 12„ in ure‚ žon Ÿon 0ˆ11ˆ ’emocratic epublic of ”oat capsies on ƒa€e Ÿivu 1 ‚ea‚… 22 missin Cono… ”u€avu „ˆ12ˆ –uneshli oil fiel‚… Caspian ˜ire on a ‚rillin platform ‚urin a storm – 10 ‚ea‚… 20 missin ‘ea… Aerbai an 0 people ‚ie in a lifeboat ‚urin rescue † in ure‚ operations… ‚amae to as pipeline 1†ˆ12ˆ “n‚ian ™cean… “n‚onesia… ˜erry capsies in rouh eather 66 ‚ea‚… 12 missin ”one ”ay… ‘ia… ‘ulaesi in ure‚ “ining accidents Number o ictims ate CountrŒ …ent šhere ‚ata available› „ˆˆ Ž€raine… ’onets€ ™blast –as explosion at a coal mine ‚ea‚ 1†ˆ„ˆ China… ’aton City… ‘hanxi ¨all failure at a coal mine traps miners 21 ‚ea‚ 12ˆ‡ˆ China… ‘hanyan… ‘haanxi ƒan‚sli‚e at a vana‚ium mine buries ‚ormitories † ‚ea‚… 56 missin an‚ three resi‚ential buil‚ins 10ˆ10ˆ China… ‘hanrao… ¤ianxi –as explosion at a coal mine 22 ‚ea‚ 5ˆ11ˆ ”rail o ‚ams at an iron ore mine collapse – triers 1 ‚ea‚… 11 missin ”ento o‚riues šŠariana› mu‚flo at a nearby ton an‚ contaminates 6 homeless aterays 20ˆ11ˆ China… ¤ixi… žeilon ian ˜ire at a coal mine 22 ‚ea‚ 21ˆ11ˆ Šyanmar ƒan‚sli‚e at a a‚e mine buries or€ers an‚ ‡0 115 ‚ea‚ žpa€ant… Ÿachin resi‚ential buil‚ins 25ˆ12ˆ Šyanmar… žpa€ant ƒan‚sli‚e at a ol‚ an‚ a‚e mine 50 missin ‡ Swiss Re sigma No 1/2016
Rail disasters˜ including cablewaŒs Number o ictims ate CountrŒ …ent šhere ‚ata available› 6ˆ1ˆ ”rail rain at a station hit from behin‚ by another train 15‡ in ure‚ ŠesŒuita… io ‚e ¤aneiro 12ˆ1ˆ Žnite‚ ‘tates ‘mo€e an‚ electrical arcin acci‚ent at three 1 ‚ea‚ ¨ashinton metro stations ‡„ in ure‚ 1ˆ2ˆ “n‚ia •assener train ‚erails ‚ue to faulty trac€s ‚ea‚ Ane€al… Ÿarnata€a 60 in ure‚ 20ˆˆ “n‚ia •assener train ‚erails † ‚ea‚ aebareli… Žttar •ra‚esh ‡ in ure‚ 25ˆˆ hailan‚ o passener trains colli‚e 52 in ure‚ •hachi ’istrict 2‡ˆ„ˆ ‘outh Africa o passener trains colli‚e 1 ‚ea‚ ¤ohannesbur 2„1 in ure‚ 12ˆ5ˆ Žnite‚ ‘tates •assener train ‚erails ‡ ‚ea‚ •hila‚elphia 200 in ure‚ 25ˆ5ˆ “n‚ia •assener train ‚erails 2 ‚ea‚ Ÿaushambhi… Žttar •ra‚esh 100 in ure‚ 16ˆ6ˆ unisia •assener train hits lorry at an unmar€e‚ crossin 1‡ ‚ea‚ unis †‡ in ure‚ 2ˆˆ •a€istan… ¤am€ey Chattha… Army train plunes into canal after bri‚e 1† ‚ea‚ –u ranala collapses 100 in ure‚ 1ˆˆ ‘outh Africa o trains colli‚e 00 in ure‚ ¤ohannesbur 5ˆ‡ˆ “n‚ia o passener trains ‚erail ‚ue to floo‚e‚ trac€s 0 ‚ea‚ žar‚a… Ša‚hya •ra‚esh 60 in ure‚ 1ˆ11ˆ •a€istan •assener train ‚erails after bra€es fail 20 ‚ea‚ ”olan †6 in ure‚ “iscellaneous Number o ictims ate CountrŒ …ent šhere ‚ata available› 0ˆ1ˆ •a€istan ”omb explosion in a mosŒue 60 ‚ea‚ ‘hi€arpur ‡ˆ2ˆ Eypt Clashes at a football sta‚ium 22 ‚ea‚ Cairo 1ˆ2ˆ •a€istan –unmen attac€ an‚ explosions at a mosŒue 22 ‚ea‚ •eshaar 60 in ure‚ 1ˆ2ˆ žaiti žih‰voltae ire hits a carnival‰para‚e float an‚ 1‡ ‚ea‚ •ort‰au‰•rince electrocutes ‚ancers ‡ in ure‚ 26ˆ2ˆ Nieria… ”iu ‘uici‚e bombin in a local mar€et 22 ‚ea‚ ˆˆ Nieria ‘uici‚e bombins at a local mar€et 5‡ ‚ea‚ Šai‚uuri 15ˆˆ •a€istan ‘uici‚e bombin at a church 1„ ‚ea‚ ƒahore 0 in ure‚ 1‡ˆˆ unisia –unmen attac€s at ”ar‚o National Šuseum 22 ‚ea‚ unis „0 in ure‚ 26ˆˆ ‘omalia –unmen attac€s at a hotel 2„ ‚ea‚ Šoa‚ishu 1ˆ„ˆ Ÿenya –unmen attac€s at Žniversity 1„‡ ‚ea‚ –arissa 6ˆ„ˆ Nieria Šass shootin at a mosŒue 2„ ‚ea‚ Ÿa affa 11ˆ„ˆ •a€istan Šass shootin at a construction site 20 ‚ea‚ ”aluchistan Swiss Re sigma No 1/2016 †
Tables or reporting Œear 2015 Number o ictims ate CountrŒ …ent šhere ‚ata available› 12ˆ„ˆ Ÿenya ‘tampe‚e folloin an electrical explosion at a 1 ‚ea‚ Nairobi university buil‚in 1„1 in ure‚ 1‡ˆ„ˆ Afhanistan ‘uici‚e bombin outsi‚e a ban€ branch ‚ea‚ ¤alalaba‚ 115 in ure‚ 2ˆ„ˆ–2‡ˆ„ˆ Žnite‚ ‘tates •rotests… riots 10 in ure‚ ”altimore… Šarylan‚ ˆ5ˆ “srael Clashes beteen ethnic roups an‚ the police 5 in ure‚ el Aviv 1ˆ5ˆ •a€istan ‘hootin attac€ on a bus carryin pilrims „5 ‚ea‚ Ÿarachi 22ˆ5ˆ ‘au‚i Arabia ‘uici‚e bombin at a mosŒue 21 ‚ea‚ Al‰¿a‚eeh 50 in ure‚ 1„ˆ6ˆ “n‚ia –as lea€ from a tan€er carryin liŒuefie‚ ammonia 6 ‚ea‚ ƒu‚hiana 21 in ure‚ 15ˆ6ˆ Cha‚ ‘uici‚e bombin at the police hea‚Œuarters 2 ‚ea‚ N’’ amena 100 in ure‚ 2ˆ6ˆ Nieria ‘uici‚e bombins at a mosŒue 0 ‚ea‚ Šai‚uuri 26ˆ6ˆ unisia Šass shootin at a holi‚ay resort ‡ ‚ea‚ ‘ousse 26ˆ6ˆ Ÿuait ‘uici‚e bombin at a mosŒue 2„ ‚ea‚ Ÿuait City 202 in ure‚ ˆˆ Nieria ‘uici‚e bombin outsi‚e a overnment buil‚in 25 ‚ea‚ «aria 2 in ure‚ 1„ˆˆ “n‚ia ‘tampe‚e at a reliious festival 2 ‚ea‚ a ahmun‚ry šAn‚hra „ in ure‚ •ra‚esh› 20ˆˆ ur€ey ‘uici‚e bombin at a ‚emonstration ‚ea‚ ‘uruç 10„ in ure‚ 10ˆ‡ˆ “n‚ia ‘tampe‚e at a temple 11 ‚ea‚ ¤har€han‚ 50 in ure‚ 1ˆ‡ˆ hailan‚ ”omb explosion at a reliious shrine 20 ‚ea‚ ”an€o€ 120 in ure‚ 16ˆ†ˆ ‘u‚an ™il tan€er overturns an‚ explo‚es³ local resi‚ents 1† ‚ea‚ Šari‚i ha‚ athere‚ to siphon fuel 2ˆ†ˆ ‘au‚i Arabia ‘tampe‚e an‚ crush at the annual ža pilrimae 6† ‚ea‚ Šina… Šecca †„ in ure‚ 10ˆ10ˆ ur€ey ”omb explosions at peace ‚emonstrations outsi‚e 102 ‚ea‚ An€ara main train station „00 in ure‚ 12ˆ11ˆ ƒebanon ’ouble suici‚e bombin… outsi‚e a mosŒue an‚ a „ ‚ea‚ ”eirut ba€ery… in cro‚e‚ area of ”eirut 250 in ure‚ 1ˆ11ˆ ˜rance ‘imultaneous terrorist attac€s at various locations 10 ‚ea‚ •aris in •aris: mass shootins… suici‚e bombins an‚ 51 in ure‚ hostae siee 1ˆ11ˆ Nieria ”omb explosion at a farmer’s mar€et 2 ‚ea‚ µola ‡0 in ure‚ 1†ˆ11ˆ Žnite‚ Arab Emirates –as lea€ at an in‚ustrial one – or€ers ‡„ in ure‚ ‘har ah hospitalise‚ sufferin from asphyxia 20ˆ11ˆ Šali… ”ama€o ‘hootin an‚ hostae siee at a hotel 22 ‚ea‚ 1ˆ12ˆ •a€istan ”omb explosion at a baaar 2 ‚ea‚ •arachinar 0 in ure‚ 20ˆ12ˆ China ƒan‚sli‚e from a construction aste ‚ump at an ‚ea‚… „ missin ‘henhen… –uan‚on in‚ustrial par€ buries buil‚ins an‚ causes explosion at as pipeline 2†ˆ12ˆ •a€istan ‘uici‚e bombin outsi‚e a overnment office 2„ ‚ea‚ Šar‚an ‘ource: ‘iss e Economic esearch ¦ Consultin an‚ Cat •erilsˆ „0 Swiss Re sigma No 1/2016
Table 10 he „0 most costly insurance losses š1†0–2015› „ „nsured loss šin Ž‘’ m… in‚exe‚ to 2015› †ictims„„ Start date …ent CountrŒœregion † 66 1‡6 25ˆ0‡ˆ2005 žurricane Ÿatrina… storm sure… ‚amae to oil ris Ž‘… –ulf of Šexico 6 ‡65 1‡ 520 11ˆ0ˆ2011 EarthŒua€e šŠ †ˆ0› triers tsunami ¤apan 6 115 2 2„ˆ10ˆ2012 žurricane ‘an‚y… storm sure Ž‘… Caribbean… Cana‚a 2 01 65 2ˆ0‡ˆ1††2 žurricane An‚re… floo‚s Ž‘… ”ahamas 25 12† 2†‡2 11ˆ0†ˆ2001 error attac€ on ¨C… •entaon… other buil‚ins Ž‘ 2„ „55 61 1ˆ01ˆ1††„ Northri‚e earthŒua€e šŠ 6ˆ› Ž‘ 22 „ 1† 06ˆ0†ˆ200‡ žurricane “€e… floo‚s… ‚amae to oil ris Ž‘… Caribbean… –ulf of Šexico 16 ‡5 1‡5 22ˆ02ˆ2011 EarthŒua€e šŠ 6ˆ1›… aftershoc€s Ne «ealan‚ 16 1‡0 11† 02ˆ0†ˆ200„ žurricane “van³ ‚amae to oil ris Ž‘… Caribbean… ´eneuela 15 †† ‡15 2ˆ0ˆ2011 žeavy monsoon rains… extreme floo‚in hailan‚ 15 2„‡ 5 1†ˆ10ˆ2005 žurricane ¨ilma… torrential rains… floo‚in Ž‘… Šexico… Caribbean 12 252 „ 20ˆ0†ˆ2005 žurricane ita… floo‚s… ‚amae to oil ris Ž‘… –ulf of Šexico 11 51 12 15ˆ0ˆ2012 ’rouht in the Corn ”elt Ž‘ 10 0† 6 11ˆ0‡ˆ200„ žurricane Charley Ž‘… Caribbean… –ulf of Šexico †‡2 51 2ˆ0†ˆ1††1 yphoon Šireille/Noˆ 1† ¤apan ‡‡ 1 15ˆ0†ˆ1†‡† žurricane žuo Ž‘… Caribbean ‡6†1 562 2ˆ02ˆ2010 EarthŒua€e šŠ ‡ˆ‡› triers tsunami Chile… the ‘outh •acific ocean ‡„6 †5 25ˆ01ˆ1††0 ¨inter storm ’aria ˜rance… ŽŸ… ”elium… Nƒ etˆ alˆ ‡2„† 110 25ˆ12ˆ1††† ¨inter storm ƒothar ‘iterlan‚… ŽŸ… ˜rance… etˆ alˆ 6‡† 21 22ˆ0„ˆ2011 Ša or torna‚o outbrea€³ „† torna‚oes… hail Ž‘ „26 1 20ˆ05ˆ2011 orna‚o outbrea€… in‚s up to „05 €m/h… hail Ž‘ 6†66 5„ 1‡ˆ01ˆ200 ¨inter storm Ÿyrill… floo‚s –ermany… ŽŸ… Nƒ… ”elium etˆ alˆ 6„62 22 15ˆ10ˆ1†‡ ‘torm an‚ floo‚s in Europe ˜rance… ŽŸ… Nƒ… etˆ alˆ 605 50 26ˆ0‡ˆ200„ žurricane ˜rances Ž‘… ”ahamas 611‡ 5 22ˆ0‡ˆ2011 žurricane “rene… floo‚s Ž‘… Cana‚a… Caribbean 5†5 600 20ˆ0†ˆ1††‡ žurricane –eores… floo‚s Ž‘… Caribbean 5‡5 6„ 25ˆ02ˆ1††0 ¨inter storm ´ivian ‘iterlan‚… –ermany 5„6 26 22ˆ0†ˆ1††† yphoon ”art/Noˆ 1‡ ¤apan 5„2 – 0„ˆ0†ˆ2010 EarthŒua€e šŠ ˆ0›… over 00 aftershoc€s Ne «ealan‚ „‡2 0„ 1ˆ0†ˆ200„ žurricane ¤eanne³ floo‚s… lan‚sli‚es Ž‘… Caribbean „‡2 „ 05ˆ06ˆ2001 ropical storm Allison³ heavy rain… floo‚s Ž‘ „„† „5 06ˆ0†ˆ200„ yphoon ‘on‚a/Noˆ 1‡ ¤apan… ‘outh Ÿorea „205 25 2ˆ05ˆ201 ˜loo‚s –ermany… Cech epublic… etˆ alˆ „12 51 02ˆ05ˆ200 hun‚erstorms… torna‚oes… hail… flash floo‚s Ž‘ „01„ ‡ 10ˆ0†ˆ1††† žurricane ˜loy‚… heavy rain… floo‚s Ž‘… ”ahamas †0 – 2ˆ0ˆ201 žailstorms –ermany… ˜rance ‡†5 01ˆ10ˆ1††5 žurricane ™pal… floo‚s Ž‘… Šexico… –uatemala ‡„ 6„25 1ˆ01ˆ1††5 –reat žanshin earthŒua€e in Ÿobe šŠ 6ˆ†› ¤apan 505 25 2„ˆ01ˆ200† ¨inter storm Ÿlaus ˜rance… ‘pain „1 „5 2ˆ12ˆ1††† ¨inter storm Šartin ‘pain… ˜rance… ‘iterlan‚… “taly Note: Š ¬ moment manitu‚e scaleˆ ‘ource: ‘iss e Economic esearch ¦ Consultin an‚ Cat •erilsˆ 43 •roperty an‚ business interruption… exclu‚in liability an‚ life insurance losses³ Ž‘ natural catastrophe fiures base‚ on •roperty Claim ‘ervices š•C‘›/inclˆ N˜“• losses šsee “erms an‚ selection criteria” on pae „ˆ 44 ’ea‚ an‚ missinˆ Swiss Re sigma No 1/2016 „1
Tables or reporting Œear 2015 Table 11 he „0 orst catastrophes in terms of victims š1†0–2015› „6 „nsured loss šŽ‘’ m… „5 †ictims in‚exe‚ to 2015› Start date …ent CountrŒœregion 00 000 – 11ˆ11ˆ1†0 ‘torm an‚ floo‚ catastrophe ”anla‚esh 255 000 – 2‡ˆ0ˆ1†6 EarthŒua€e šŠ ˆ6› China 222 50 10† 12ˆ01ˆ2010 EarthŒua€e šŠ ˆ0›… aftershoc€s žaiti 220 000 250‡ 26ˆ12ˆ200„ EarthŒua€e šŠ †› triers tsunami in “n‚ian ™cean “n‚onesia… hailan‚… etˆ alˆ 1‡ 00 – 02ˆ05ˆ200‡ ropical cyclone Naris… “rraa‚‚y ’elta floo‚e‚ Šyanmar… ”ay of ”enal 1‡ 000 „ 2†ˆ0„ˆ1††1 ropical cyclone –or€y ”anla‚esh ‡ „„† „0 12ˆ05ˆ200‡ EarthŒua€e šŠ ˆ†› in ‘ichuan… aftershoc€s China „ 10 – 0‡ˆ10ˆ2005 EarthŒua€e šŠ ˆ6›³ aftershoc€s… lan‚sli‚es •a€istan… “n‚ia… Afhanistan 66 000 – 1ˆ05ˆ1†0 EarthŒua€e šŠ ˆ†› triers roc€ sli‚e an‚ floo‚s •eru 55 60 – 15ˆ06ˆ2010 žeatave… temperatures of up to „0°C ussia… Cech epublic „0 000 20† 20ˆ06ˆ1††0 EarthŒua€e šŠ ˆ„›… lan‚sli‚es “ran 5 000 162„ 01ˆ06ˆ200 žeatave an‚ ‚rouht in Europe ˜rance… “taly… –ermany… etˆ alˆ 26 21 – 26ˆ12ˆ200 EarthŒua€e šŠ 6ˆ5› ‚estroys ‡5§ of ”am “ran 25 000 – 0ˆ12ˆ1†‡‡ EarthŒua€e šŠ 6ˆ‡› Armenia 25 000 – 16ˆ0†ˆ1†‡ EarthŒua€e šŠ ˆ› in abas “ran 2 0‡6 – 1ˆ11ˆ1†‡5 ´olcanic eruption on Neva‚o ‚el ui triers lahars Colombia 22 00 1 0„ˆ02ˆ1†6 EarthŒua€e šŠ ˆ5› –uatemala 1† 1„ 26ˆ01ˆ2001 EarthŒua€e šŠ ˆ6› in –u arat “n‚ia… •a€istan 1† 11‡ 1 „22 1ˆ0‡ˆ1††† EarthŒua€e šŠ ˆ6› in “mit ur€ey 1‡ 520 6 ‡65 11ˆ0ˆ2011 EarthŒua€e šŠ †ˆ0› triers tsunami ¤apan 15 000 1„2 2†ˆ10ˆ1††† ropical cyclone 05” in ™rissa “n‚ia 1„ 20„ – 20ˆ11ˆ1† ropical cyclone in An‚hra •ra‚esh “n‚ia 11 6‡ 5‡1 22ˆ10ˆ1††‡ žurricane Šitch in Central America žon‚uras… Nicaraua… etˆ alˆ 1106† – 25ˆ05ˆ1†‡5 ropical cyclone in ”ay of ”enal ”anla‚esh 10 ‡00 – 26ˆ10ˆ1†1 ™‚isha cyclone… floo‚in in ”ay of ”enal “n‚ia 10 000 1 12ˆ12ˆ1††† ˜loo‚s… mu‚flos an‚ lan‚sli‚es ´eneuela †500 10„ 1†ˆ0†ˆ1†‡5 EarthŒua€e šŠ ‡ˆ0› Šexico †„5 0ˆ„ 0ˆ0†ˆ1†† EarthŒua€e šŠ 6ˆ„› “n‚ia ‡†60 160 25ˆ0„ˆ2015 EarthŒua€e šŠ ˆ‡› Nepal… “n‚ia… China… ”anla‚esh ‡15 51† 0‡ˆ11ˆ201 yphoon žaiyan… storm sure •hilippines… ´ietnam… China… •alau 0† – 1ˆ0‡ˆ1†6 EarthŒua€e šŠ ˆ1› triers tsunami in Šoro –ulf •hilippines 6„25 ‡„ 1ˆ01ˆ1††5 –reat žanshin earthŒua€e šŠ 6ˆ†› in Ÿobe ¤apan 60„ – 05ˆ11ˆ1††1 yphoon helma šŽrin› •hilippines 6000 – 02ˆ12ˆ1†‡„ Acci‚ent in chemical plant ‰ methyl isocyanates “n‚ia release‚ 6000 – 01ˆ06ˆ1†6 žeatave… ‚rouht ˜rance 5„† „ 2ˆ05ˆ2006 EarthŒua€e šŠ 6ˆ„›³ ”antul almost completely “n‚onesia ‚estroye‚ 5„‡ 50† 1„ˆ06ˆ201 ˜loo‚s cause‚ by heavy monsoon rains “n‚ia 5„22 – 25ˆ06ˆ1†6 EarthŒua€e šŠ ˆ1› “n‚onesia 5„ – 10ˆ0„ˆ1†2 EarthŒua€e šŠ 6ˆ6› in ˜ars “ran 500 – 2‡ˆ12ˆ1†„ EarthŒua€e šŠ 6ˆ0› •a€istan Note: Š ¬ moment manitu‚e scaleˆ ‘ource: ‘iss e Economic esearch ¦ Consultin an‚ Cat •erilsˆ 45 ’ea‚ an‚ missinˆ 46 •roperty an‚ business interruption… exclu‚in liability an‚ life insurance lossesˆ „2 Swiss Re sigma No 1/2016
erms an‚ selection criteria Natural catastrophes A natural catastrophe is cause‚ by he term “natural catastrophe” refers to an event cause‚ by natural forcesˆ ‘uch an natural forcesˆ event enerally results in a lare number of in‚ivi‚ual losses involvin many insurance policiesˆ he scale of the losses resultin from a catastrophe ‚epen‚s not only on the severity of the natural forces concerne‚… but also on man‰ma‚e factors… such as buil‚in ‚esin or the efficiency of ‚isaster control in the afflicte‚ reionˆ “n this sigma stu‚y… natural catastrophes are sub‚ivi‚e‚ into the folloin cateories: floo‚s… storms… earthŒua€es… ‚rouhts/forest fires/heat aves… col‚ aves/frost… hail… tsunamis… an‚ other natural catastrophesˆ “an-made disasters A man‰ma‚e or technical ‚isaster is his stu‚y cateorises ma or events associate‚ ith human activities as “man‰ma‚e” triere‚ by human activitiesˆ or “technical” ‚isastersˆ –enerally… a lare ob ect in a very limite‚ space is affecte‚… hich is covere‚ by a small number of insurance policiesˆ ¨ar… civil ar… an‚ ar‰li€e events are exclu‚e‚ˆ sigma sub‚ivi‚es man‰ma‚e ‚isasters into the folloin cateories: ma or fires an‚ explosions… aviation an‚ space ‚isasters… shippin ‚isasters… rail ‚isasters… minin acci‚ents… collapse of buil‚ins/bri‚es… an‚ miscellaneous šinclu‚in terrorism›ˆ “n ables ‡ an‚ † špaes „1–„2›… all ma or natural catastrophes an‚ man‰ma‚e ‚isasters an‚ the associate‚ losses are liste‚ chronoloicallyˆ Total losses ƒosses ‚ue to property ‚amae an‚ ˜or the purposes of the present sigma stu‚y… total losses are all the financial losses business interruption that are ‚irectly ‚irectly attributable to a ma or event… ie ‚amae to buil‚ins… infrastructure… vehicles attributable to ma or events are inclu‚e‚ etcˆ he term also inclu‚es losses ‚ue to business interruption as a ‚irect in this stu‚yˆ conseŒuence of the property ‚amaeˆ “nsure‚ losses are ross of any reinsurance… be it provi‚e‚ by commercial or overnment schemesˆ A fiure i‚entifie‚ as “total ‚amae” or “economic loss” inclu‚es all ‚amae… insure‚ an‚ uninsure‚ˆ otal loss fiures ‚o not inclu‚e in‚irect financial losses – ie loss of earnins by suppliers ‚ue to ‚isable‚ businesses… estimate‚ shortfalls in –’• an‚ non‰economic losses… such as loss of reputation or impaire‚ Œuality of lifeˆ he amount of the total losses is a –enerally… total šor economic› losses are estimate‚ an‚ communicate‚ in very eneral in‚ication onlyˆ ‚ifferent aysˆ As a result… they are not ‚irectly comparable an‚ shoul‚ be seen only as an in‚ication of the eneral or‚er of manitu‚eˆ „nsured losses he term “losses” refer to insure‚ losses… “ƒosses” refer to all insure‚ losses except liabilityˆ ƒeavin asi‚e liability losses… on but ‚o not inclu‚e liabilityˆ one han‚… allos a relatively sift assessment of the insurance year³ on the other han‚… hoever… it ten‚s to un‚erstate the cost of man‰ma‚e ‚isastersˆ ƒife insurance losses are also not inclu‚e‚ˆ “”I flood damage in t€e Œ… N˜“• floo‚ ‚amae in the Ž‘ is inclu‚e‚ˆ he sigma catastrophe ‚atabase also inclu‚es floo‚ ‚amae covere‚ by the National ˜loo‚ “nsurance •roram šN˜“•› in the Ž‘… provi‚e‚ that it fulfils the sigma selection criteriaˆ Swiss Re sigma No 1/2016 „
Terms and selection criteria Selection criteria sigma has been publishin tables listin ma or losses since 1†0ˆ hreshol‚s ith respect to casualties – the number of ‚ea‚… missin… severely in ure‚… an‚ homeless – also ma€e it possible to tabulate events in reions here the insurance penetration is belo averaeˆ hreshol‚s for insure‚ losses an‚ ˜or the 2015 reportin year… the loer loss threshol‚s ere set as follos: casualties in 2015 “nsure‚ losses šclaims›: Šaritime ‚isasters Ž‘’ 1†ˆ million Aviation Ž‘’ †ˆ million ™ther losses Ž‘’ „‡ˆ‡ million or otal losses: Ž‘’ †ˆ million or Casualties: ’ea‚ or missin 20 “n ure‚ 50 žomeless 2 000 ™dŽustment or inlation˜ changes to published data˜ inormation ƒosses are ‚etermine‚ usin year‰en‚ sigma converts all losses for the occurrence year not iven in Ž‘’ into Ž‘’ usin exchane rates an‚ are then a‚ uste‚ for the en‚‰of‰year exchane rateˆ o a‚ ust for inflation… these Ž‘’ values are inflationˆ extrapolate‚ usin the Ž‘ consumer price in‚ex to ive current š2015› valuesˆ his can be illustrate‚ by examinin the insure‚ property losses arisin from the floo‚s hich occurre‚ in the ŽŸ beteen 2† ™ctober an‚ 10 November 2000: “nsure‚ loss at 2000 prices: Ž‘’ 1 0„5ˆmillion “nsure‚ loss at 2015 prices: Ž‘’ 1 „‡ˆ‡ million Alternatively… ere one to a‚ ust the losses in the oriinal currency š–”•› for inflation an‚ then convert them to Ž‘’ usin the current exchane rate… one oul‚ en‚ up ith an insure‚ loss at 2015 prices of Ž‘’ 1 „2 million… 1§ less than ith the stan‚ar‚ sigma metho‚ˆ he reason for the ‚ifference is that the value of the –”• ‚ecline‚ by almost 1§ aainst the Ž‘’ in the perio‚ 2000–2015ˆ he ‚ifference in inflation beteen the Ž‘ šˆ6§› an‚ the ŽŸ šˆ6§› over the same perio‚ as neliibleˆ Figure — Floods Ÿ …•change rate S inlation Alternative metho‚s of a‚ ustin for 2† ™ctober–10 November 2000 –”•m Ž‘’/–”• Ž‘’m Ž‘’m inflation… by comparison ™riinal loss 00ˆ0 1ˆ„†„ 10„5ˆ 10„5ˆ ƒevel of consumer price in‚ex 2000 †ˆ1 100ˆ0 ƒevel of consumer price in‚ex 2015 12‡ˆ0 1ˆ6 “nflation factor 1ˆ6 1ˆ6 A‚ uste‚ for inflation to 2015 †6ˆ2 1ˆ„‡2 1„2ˆ„ 1„‡ˆ‡ Comparison ††§ 100§ ‘ource: ‘iss e Economic esearch ¦ Consultinˆ „„ Swiss Re sigma No 1/2016
Chanes to loss amounts of previously “f chanes to the loss amounts of previously publishe‚ events become €non… sigma publishe‚ events are up‚ate‚ in the ta€es these into account in its ‚atabaseˆ žoever… these chanes only become sigma ‚atabaseˆ evi‚ent hen an event appears in the table of the „0 most costly insure‚ losses or the „0 ‚isasters ith the most fatalities since 1†0 š‘ee ables 10 an‚ 11 on paes „1‰„2›ˆ ™nly public information use‚ for “n the chronoloical lists of all man‰ma‚e ‚isasters… the insure‚ losses are not shon man‰ma‚e ‚isasters for ‚ata protection reasonsˆ žoever… the total of these insure‚ losses is inclu‚e‚ in the list of ma or losses in 2015 accor‚in to loss cateoryˆ sigma ‚oes not provi‚e further information on in‚ivi‚ual insure‚ losses or about up‚ates ma‚e to publishe‚ ‚ataˆ Sources Nespapers… ‚irect insurance an‚ “nformation is collecte‚ from nespapers… ‚irect insurance an‚ reinsurance reinsurance perio‚icals… specialist perio‚icals… specialist publications šin printe‚ or electronic form› an‚ reports from publications an‚ other reports are use‚ insurers an‚ reinsurersˆ “n no event shall ‘iss e be liable for any loss or ‚amae to compile this stu‚yˆ arisin in connection ith the use of this information šsee the copyriht information „ on the bac€ pae›ˆ Table 12 CountrŒ CurrencŒ …•change rate˜ end 2015 „‡ Exchane rate use‚ … national currency Australia AŽ’ 1ˆ„5 per Ž‘’ Cana‚a CA’ 1ˆ‡†2 China CNµ 6ˆ„† Europe EŽ 0ˆ†20 Žnite‚ Ÿin‚om –”• 0ˆ6‡„ –eoria –Eƒ 2ˆ†„† “n‚onesia “’ 1 †5ˆ0000 “n‚ia “N 66ˆ2200 “ran “ 2† ‡55ˆ0000 ¤apan ¤•µ 120ˆ250 Šyanmar ŠŠŸ 102ˆ5000 Šalai ЍŸ 65‡ˆ500 Ne «ealan‚ N«’ 1ˆ„60 •hilippines •ž• „6ˆ†200 •a€istan •Ÿ 10„ˆ‡00 ussia Ž” ˆ0‡21 ‘au‚i Arabia ‘A ˆ5 hailan‚ ž” 6ˆ050 aian ¨’ 2ˆ†50 Ž‘ Ž‘’ 1ˆ0000 47 he losses for 2015 ere converte‚ to Ž‘’ usin these exchane ratesˆ No losses in any other currencies ere reporte‚ˆ 48 Natural catastrophes in the Ž‘: those sigma fiures hich are base‚ on estimates of •roperty Claim ‘ervices š•C‘›… a unit of the “nsurance ‘ervices ™ffice… “nc š“‘™›… are iven for each in‚ivi‚ual event in ranes ‚efine‚ by •C‘ˆ he estimates are the property of “‘™ an‚ may not be printe‚ or use‚ for any purpose… inclu‚in use as a component in any financial instruments… ithout the express consent of “‘™ˆ Swiss Re sigma No 1/2016 „5
•ublishe‚ by: ‘iss e ƒt‚ Explore an‚ visualie sigma ‚ata on natural catastrophes an‚ Economic esearch ¦ Consultin the orl‚ insurance mar€ets at ˆsigma‰explorerˆcom •ˆ™ˆ ”ox ‡022 «urich © 2016 ‘iss eˆ All rihts reserve‚ˆ ‘iterlan‚ he e‚itorial ‚ea‚line for this stu‚y as 26 ˜ebruary 2016ˆ elephone ®„1 „ 2‡5 2551 ˜ax ®„1 „ 2‡2 005 sigma is available in Enlish šoriinal lanuae›… –erman… ˜rench… E‰Šail: simaÊsissreˆcom ‘panish… Chinese an‚ ¤apaneseˆ sigma is available on ‘iss e’s ebsite: ˆsissreˆcom/sima Armon€ ™ffice: 15 Ÿin ‘treet he internet version may contain slihtly up‚ate‚ informationˆ Armon€… Nµ 1050„ ranslations: elephone ®1 †1„ ‡2‡ ‡000 –erman: ’iction A– ˜rench: ithaxa Communications ‘Aƒ ‘panish: ra‚uctores Asocia‚os ´alencia ‘ˆƒˆ žon Ÿon ™ffice: 1‡ žarbour oa‚… ¨anchai –raphic ‚esin an‚ pro‚uction: Central •laa… 61st ˜loor Corporate eal Estate ¦ ƒoistics / Še‚ia •ro‚uction… «urich žon Ÿon… ‘A •rintin: Šulticolor •rint A–… ”aar elephone ® ‡52 25 ‡2 56„„ Authors: ƒucia ”evere elephone ®„1 „ 2‡5 †2† his report is printe‚ on sustainably pro‚uce‚ paperˆ he oo‚ a eev ‘haran use‚ comes from forest certifie‚ to 100§ by the ˜orest ‘tear‚ship elephone ®†1 ‡0 „†00 212 Council š˜‘C›ˆ ´ipin Ÿ ‘ © 2016 elephone ®†1 ‡0 „†00 2„02 ‘iss e All rihts reserve‚ˆ sigma e‚itor: he entire content of this sigma e‚ition is sub ect to copyriht ith all •aul on€e rihts reserve‚ˆ he information may be use‚ for private or internal elephone ®„1 „ 2‡5 2660 purposes… provi‚e‚ that any copyriht or other proprietary notices are not remove‚ˆ Electronic reuse of the ‚ata publishe‚ in sigma is E‚itor in chief prohibite‚ˆ Ÿurt Ÿarl… žea‚ of Economic esearch ¦ Consultin… epro‚uction in hole or in part or use for any public purpose is is responsible for the sigma seriesˆ permitte‚ only ith the prior ritten approval of ‘iss e Economic esearch ¦ Consultin an‚ if the source reference “‘iss e… sigma No 1/2016” is in‚icate‚ˆ Courtesy copies are appreciate‚ˆ Althouh all the information use‚ in this stu‚y as ta€en from reliable sources… ‘iss e ‚oes not accept any responsibility for the accuracy or comprehensiveness of the information iven or forar‚ loo€in statements ma‚eˆ he information provi‚e‚ an‚ forar‚‰loo€in statements ma‚e are for informational purposes only an‚ in no ay constitute or shoul‚ be ta€en to reflect ‘iss e’s position… in particular in relation to any onoin or future ‚isputeˆ “n no event shall ‘iss e be liable for any loss or ‚amae arisin in connection ith the use of this information an‚ rea‚ers are cautione‚ not to place un‚ue reliance on forar‚‰loo€in statementsˆ ‘iss e un‚erta€es no obliation to publicly revise or up‚ate any forar‚‰loo€in statements… hether as a result of ne information… future events or otheriseˆ ™r‚er no: 20½0116½EN Swiss Re sigma No 1/2016 „
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