Tag Archives: Insurance

EXPOSURE Magazine: Taking Cloud Adoption to the Core

This is a taster of an article published in the latest edition of EXPOSURE magazine. For the full article click here or visit the EXPOSURE website.

With the main benefits of Cloud computing now well-established, EXPOSURE explored why insurance and reinsurance companies have demonstrated some reluctance in moving core services onto a Cloud-based infrastructure.

While a growing number of insurance and reinsurance companies are using Cloud services (such as those offered by Amazon Web Services, Microsoft Azure and Google Cloud) for nonessential office and support functions, most have been reluctant to consider Cloud for their mission-critical infrastructure. Simply moving a legacy offering and placing it on a new Cloud platform offers a potentially better user interface, but it’s not really transforming the process.

EXPOSURE also asked whether now is the time for market-leading (re)insurers to make that leap and really transform how they do business, embrace the new and different, and take comfort in what other industries have been able to do.

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Schrödinger’s Cat Model

Schrödinger’s cat inhabits a thought-experiment designed to reveal the paradox of quantum properties. A hypothetical cat is sealed in a windowless box, in which there is a device that will administer a lethal poison, according to whether a single atom undergoes radioactive decay. Should the atom decay the cat will be dead. If the atom survives so will the cat. Only the quantum state of the atom is completely unknowable. So, the cat — in principle at least, is half dead and half alive. The simultaneous state of being both alive and dead is called a “superposition”.

While quantum behavior is not an average insurance coverage, (at least until future quantum computer cyber cover emerges), there are situations in the world of risk modeling that come close to Schrödinger’s cat — or perhaps that should better be Schrödinger’s “Cat” (short for Catastrophe)?

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Exceedance 2017 – Coming in Just a Few Weeks!

It’s hard to believe but Exceedance 2017 will be here in just a few weeks, and the excitement is building!

Exceedance_6Feb2Many companies are sending their cross-functional teams to fast track their ability to put new capabilities to work. And with good reason. With the releases of Risk Modeler on the RMS(one)® platform and Version 17 in April, attendees will experience more tracks (22) and more sessions (105) than in previous years.

There will also be many opportunities for interaction with model experts, up close team training, networking opportunities, and so much more. Enabling your success is the driving force behind Exceedance!

Here are some highlights of the topics we are preparing for you and your team:

  • Risk Modeler powered by RMS(one): You will obtain a deep understanding of the modeling and analytics that provide the core of the Risk Modeler workflow, including setting up analyses, creating structures and positions, and accessing models from multiple RiskLink® versions for key use cases such as change management, modeling reinsurance programs, and analyzing insurance portfolios.
  • Version 17 North America Earthquake: The changes to the North America Earthquake Models represent the latest view of risk across the U.S., Canada, and Mexico. We will provide the full scope of the update by delving into the model components, including our unique implementation of the latest source models from the USGS, directional loss changes by region and line of business, and detailed loss change exhibits.
  • Event Response: How did your business respond to Hurricane Matthew? Learn what we are doing to enhance RMS Event Response, including future offerings, making it work for your business, addressing the main challenges faced during a real-time event like Hurricane Matthew, and more.
  • U.S. Flood Model: Flood risk management is becoming an increasingly important peril to manage for the insurance industry in the U.S. We’ll provide the latest details on all model components, including the simulation-based model methodology, the innovative vulnerability components of the upcoming RMS U.S. Flood HD Model, and how best to capture opportunities in the evolving U.S. flood market.

The Lab at Exceedance: Solutions, Model Releases, and In-Depth Training with RMS ExpertsExceedance_6Feb

The Lab will be packed with our latest modeling and software releases, in addition to special areas dedicated to research from Horizons (RMS scientific publication) and resilience initiatives across the globe. Over 50 RMS scientists and modelers will be in The Lab to offer technical insights, training, and support – and will be available for personalized discussions.

There’s a Lot to Be Excited About

This is an important year for all of us in the industry, and RMS is ready to meet our commitments to you as we remain on track for a full schedule of delivery throughout 2017. If you’re attending, be sure to let your colleagues know about all Exceedance has to offer.

To see the full agenda with information about the tracks and sessions, The Lab, speakers, networking events, and more, visit the conference website at: exceedance.rms.com. You can also register for Exceedance here. Look for our next blog with more exciting Exceedance updates in the coming days!

Billions in Liabilities: Man-Made Earthquakes at Europe’s Biggest Gas Field

The Groningen gas field, discovered in 1959, is the largest in Europe and produces up to 15 per cent of the natural gas consumed across the continent. With original reserves of more than 100 trillion cubic feet, over the decades the field has been an extraordinary cash cow for the Dutch government and the two global energy giants, Shell and ExxonMobil, which partner in managing the field. In 2014 alone, state proceeds from Groningen were approximately €9.4 billion ($9.8 billion).

But now, costs to the Dutch government are mounting as the courts have ordered that compensation is paid to nearby propery owners for damage caused by the earthquakes induced by extracting the gas. Insurers who were covering liabilities at the field now find that the claims have the potential to extend beyond the direct shaking damage to include the reduction in property values caused by this ongoing seismic crisis. And the potential for future earthquakes and their related damages has not disappeared – a situation which again illustrates the importance of modeling the risk costs of liability coverages, a new capability on which RMS is partnering with its sister company Praedicat.

The Groningen gas reservoir covers 700 square miles and, uniquely among giant gas fields worldwide, it is located beneath a well-populated and developed region. The buildings in this region, which half a million people live and work in, are not earthquake resistant: 90% of properties are made from unreinforced masonry (URM).

The ground above the gas field has been subsiding as the gas has vented out from the 10,000-feet deep porous sandstone reservoir and the formation has compacted. This compaction helps squeeze the gas out of reservoir, but has also led to movement on pre-existing faults that are present throughout the sandstone layer, a small number of which are more regional in extent. And these sudden fault movements radiate earthquake vibrations.

How A Shake Became a Seismic Crisis

The first earthquake recorded at the field was in December 1991 with a magnitude of 2.4. The largest to date was in August 2012 with a magnitude of 3.6. In most parts of the world, such an earthquake would not have significant consequences, but on account of the shallow depth of the quake, thick soils and poor quality building construction in the Groningen area, there were more than 30,000 claims for property damage, dwarfing the total number from the previous two decades.

Since the start of 2014 the government has limited gas production in an attempt to manage the earthquakes, with some success. But the ongoing seismicity has had a catastrophic effect on the property market, which has been compounded by a class-action lawsuit in 2015. It was filed on behalf of 900 homeowners and 12 housing co-operatives who had seen the value of their properties plummet. The judge ruled that owners of the real estate should be compensated for loss of their property’s market value, even when the property was not up for sale. The case is still rumbling on through the appeal courts but if the earlier ruling stands, then the estimates of the future liabilities for damage and loss of property value range from €6.5 billion to €30 billion.

Calculating the Risk

While earthquakes associated with gas and oil extraction are known from other fields worldwide, the massive financial risk at Groningen reflects the intersection of a moderate level of seismicity with a huge concentration of exposed value and very weak buildings. And although limiting production since 2014 has reduced the seismicity, there still remains the potential for further highly damaging earthquakes.

Calculating these risk costs requires a fully probabilistic assessment of the expected seismicity, across the full range of potential magnitudes and their annual probabilities. Each event in the simulation can be modeled using locally-calibrated ground motion data as well as expected property vulnerabilities, based on previous experience from the 2012 earthquake.

There is also the question of how far beyond actual physical damage the liabilities have the potential to extend and where future earthquakes can affect house values. The situation at Groningen, where it took almost thirty years of production before the earthquakes began, highlights the need for detailed risk analysis of all energy liability insurance covers for gas and oil extraction.

Extreme Wind Speeds Over the Ocean – an International Workshop of Experts

It’s one thing being invited to speak at an industry event in front of dozens of the leading scientists in your field. It’s another to find, with a certain astonishment, that virtually all of them use RMS HWind to validate their scientific work.

Last month, at a U.K. Met Office-hosted workshop, I spoke about the RMS HWind hurricane modeling solutions to a group of high-wind remote-sensing scientists from academic and government agencies from around the world, including:

  • European Space Agency (ESA)
  • National Aeronautics and Space Administration (NASA)
  • French Research Institute for Exploitation of the Sea (IFREMER)
  • Royal Netherlands Meteorological Institute (KNMI)
  • Met Office (U.K.)
  • European Center for Medium-Range Weather Forecasts
  • National Space Science Center, Chinese Academy of Sciences
  • Institute of Applied Physics of the Russian Academy of Sciences
  • National Oceanic and Atmospheric Administration (U.S.)

All of the above agencies are researching how satellite-mounted remote wind sensors can be used, most effectively, to inform on hurricanes and typhoons developing over the ocean.

During the workshops I was delighted to learn that every major remote sensing agency had used the RMS HWind archive of historical storms to validate and calibrate their sensor programs for detecting high winds from space. RMS HWind also provides real-time analysis of hurricanes as they happen with observational data from instruments in the air, in the sea and on land – including aircraft reconnaissance, GPS dropsonde instruments, sea buoys and satellites.

By citing HWind products and research in their peer-reviewed publications, these agencies provide independent endorsements that enhance the scientific credibility of the HWind archives and services, while also giving us a chance to evaluate cutting-edge technology before it becomes operationally available.

There is tremendous value in scientific collaboration and, as such, RMS facilitates the science community’s understanding of hurricanes by providing our academic partners free access to HWind products for their scientific investigations.

Sensors in Space

None of the satellites we discussed at the Met Office workshop actually measure wind directly – rather, they measure a signal which is influenced by the wind. So, for example, the new NASA CYGNSS system measures the reflection of GPS signals off sea’s surface, which is like the reflection of the moon on the surface of a lake. Winds disturb the surface and this scatters the signal.

Another satellite, the Canadian RADARSAT-2, has already been up for a few years and can capture images of the fine scale roughness of the ocean surface. But to collect these images and convert them to a wind speed reading requires a lot of advance planning, followed by lengthy processing.

Which is where RMS HWind comes in. Our 1 km gridded HWind Snapshots make it easy for scientists to overlay their satellite instrument measurements (typically a microwave signal reflected from the sea surface) over our wind analyses. They can do this for several storms of various sizes and intensities to convert the measured signal to wind speed over a range of meteorological and oceanic conditions.

Due for release this winter, the HWind Enhanced Archive of wind hazard metrics will provide a high resolution library of tropical cyclone wind fields for the North Atlantic, the Caribbean, Gulf of Mexico, and the east and central Pacific. In the coming years we’d hope to see the expansion of tropical cyclone wind field monitoring globally.

This expansion could benefit areas of the world with insurance protection gaps hugely. Increased insurance penetration in the Asian and Australian markets, together with new risk transfer products using parametric triggers, could help improve financial resilience to catastrophic tropical cyclones in whole new regions of the world.

Understanding Risk Accumulations in Taiwan’s Science Parks

“The 6.4 magnitude Tainan earthquake in February 2016 resulted in a sizeable insured loss from the high-tech industrial risks and reminded the insurance industry of the potential threat from the risk accumulated in science parks.” (A.M. Best Special Report, Sept 2016)

Reading the sentence above you might be forgiven for wondering why science parks would give insurers and reinsurers any particular cause for concern. But consider this statistic: although Taiwan’s three major science and industrial parks occupy only 0.1% of the island’s total land mass, they represent 16% of Taiwan’s overall manufacturing – they are hugely significant, both economically and with regards to the insured exposure in Taiwan.

For example, the Hsinchu Science Park (HSP), known for semiconductor production, employs more than 150,000 people and contributes over $32 billion in revenues – approximately 6% of national GDP. By one estimate HSP represents over $319 billion in total insured values. In addition, some of the latest high tech areas within HSP, such as advanced “clean rooms,” present additional challenges due to their vulnerability to ground shaking or power interruption. The importance of this risk was observed in February’s Tainan earthquake where some significant losses to high-tech industrial risks were caused by damage to the equipment and the related business interruption due to power outage.

Improving data quality for advanced and detailed modeling is an important way to manage these risks, concludes the A.M. Best report quoted above. This is so as to accurately assess the potential loss impact on insurers’ books. RMS has already been analysing earthquake risk in Taiwan for 12 years – long before this year’s Mw 6.4 event – and in that time our view of seismic risk in Taiwan has not changed, since our model benefits from spectral response-based hazard and damage functions, that even include local liquefaction and landslide susceptibilities.

The 1999 Chi-Chi Earthquake (known in Taiwan as the 921 Earthquake) was the key event in building the RMS® Taiwan Earthquake Model in terms of the quake’s seismicity, ground motion, soil secondary effects and building response. Since then there have been no significant events to justify a re-calibration of the components of the model. In fact, the damages observed in this year’s event were broadly in line with RMS’ expectations and validated the robustness of the current model.

But although A.M. Best views the Taiwan insurance industry as prudently managed with relatively high catastrophe management capability, there are still lessons to be learnt from the 2016 event, and RMS has solutions which offer additional insight into understanding the risk posed by these business parks in Taiwan.

Concentration of Exposure into Science Parks

The RMS® Asia Industrial Clusters Catalogs were released in 2014 to identify hotspots of exposure, and profile their risk. The locations and geographic extent of the science parks within Taiwan are detailed to help understand risk accumulations for industrial lines and develop more robust risk management strategies.

taiwanblog1

Example of industrial cluster captured in the RMS Taiwan Industrial Clusters Catalog. The red outline illustrates the digitized boundaries of the Formosa Petrochemical Co. Plant in Yunlin Hsien.

High Fragility of the Semiconductor Industry

For coding of Industrial Plants, the RMS® Industrial Facilities Model (IFM) captures the unique nature of different industrial risks, as a high percentage of property value is often associated with machinery and equipment (M&E) and stock. This advanced vulnerability model supports the earthquake model to define the damageability of a comprehensive set of industrial facilities more accurately, and calculate the financial risk to these specific types of facilities, including building, contents, and business interruption (BI) loss estimates. The IFM differentiates the risks for different types of business within the science parks, and highlights the higher fragility of semiconductor plants compared to other industrial units, as shown below.

taiwanblog2

Lessons Learnt?

The huge damage from the 1999 Chi Chi earthquake has not halted the rapid development of Taiwan’s science parks in this seismically active area – indeed the island’s third biggest science park has since been built there. But this year’s comparatively small Mw 6.4 event further highlighted the substantial exposures concentrated within this sector, reminding the industry of the potential for significant losses without sound accumulation management practices, informed by the best modeling insights.

“Italy is Stronger than any Earthquake”

Those were the words of the then Italian Prime Minister, Matteo Renzi, in the aftermath of two earthquakes on the same day, October 26, 2016. As a statement of indomitable defiance at a scene of devastation it suited the political and public mood well. But the simple fact is there is work to do, because Italy is not as strong as it could be in its resilience to earthquakes.

There’s a long history of powerful seismic activity in the central Apennines: only recently we’ve seen L’Aquila (2009, Mw6.3), Amatrice (August 2016, Mw6.0), two earthquakes in the area near Visso (October 2016, Mw 5.4 and 5.9) and Norcia (October 2016, Mw6.5). These have resulted in hundreds of fatalities, mainly attributed to widespread collapse of old buildings, emphasizing that earthquakes don’t kill people – buildings do. Whilst Italy’s Civil Protection Department provides emergency management and support after earthquakes, there is too little insurance help for the financial resiliency of the communities most affected by all these events. While the oft-repeated call for earthquake insurance to be compulsory continues to be politically unobtainable, one way it could be spread more widely is through effective modeling. And RMS expertise can help with this, allowing the market to better understand the risk and so build resilience.

Examining High Building Fragility

The two most significant factors for earthquake risk in Italy are (i) construction materials and (ii) the age of the buildings. The majority of the damaged and destroyed buildings were made from unreinforced masonry, and built prior to the introduction of the most recent seismic design and building codes, making them particularly susceptible. With the RMS® Europe Earthquake model capturing both the variations in construction types and age, as well as other vulnerability factors, (re)insurers can accurately reflect the response of different structures to earthquakes.  This allows the models to be used to evaluate the cost benefits of retrofitting buildings.  RMS has worked with the Italian National Institute for Geophysics and Volcanology (INGV) to see how such analyses could be used to optimize the allocation of public funds for strengthening older buildings, thereby reducing future damage and costs.

Seismic Risk Assessment

The high-risk zone of the central Apennines is described well by probabilistic seismic hazard assessment (PSHA) maps, which show the highest risks in that region resulting from the movement of tectonic blocks that produce the extensional, ‘normal’ faulting observed. The maps also show earthquake risk throughout the rest of Italy. RMS worked with researchers from INGV to develop our view of risk in 2007, based on the latest available databases at that time, including active faults and earthquake catalogs. The resulting hazard model produces a countrywide view of seismic hazard that has not been outdated by newer studies, such as the 2009 INGV Seismic Hazard Map and the 2013 European Seismic Hazard Map published by the SHARE consortium, as shown below:

blog_italy-eq

The Route to Increased Resiliency

Increasing earthquake resiliency in Italy should also involve further development of the private insurance market. The seismic risk in Italy is relatively high for western Europe, whilst the insurance penetration is low, even outside the central Apennines. For example, in 2012, there were two large earthquakes in the Emilia-Romagna region of the Po valley, where there are higher concentrations of industrial and commercial risks. Although the type of faults and risks vary by region, such as the potential impact of liquefaction, the RMS model captures such variations in risk and can be used for the development of risk-based pricing and products for the expansion of the insurance market throughout the country.

Whilst Italy’s seismic events in October caused casualties on a lesser scale than might have been, the extent of the damage highlights once again the prevalence of earthquake risk. It is only a matter of time before the next disaster strikes, either in the Central Apennines or elsewhere. When that happens, the same questions will be asked about how Italy could be made more resilient. But if, by then, the country’s building stock is being made less susceptible and the private insurance market is growing markedly, then Italy will be able to say, with justification, it is becoming stronger than any earthquake.

See How Quickly and Easily You Can Access the Exposure Metrics That Matter

Exposure Manager is a risk management solution that provides executives, underwriters, risk analysts, and other decision-makers with the exposure analytics needed to offer a comprehensive view of risk and understand loss potential.

As the first solution released on the RMS(one) platform, Exposure Manager was developed based on the understanding that organizations not only need quick and reliable assessments of exposure concentrations, but also the right tools to ensure they can access key metrics and insights.

The videos below illustrate two of the important capabilities that enhance users’ ability to build portfolio intuition faster and quickly access the metrics that are most important.

Build Portfolio Intuition Faster provides insights into how Exposure Manager enables customers to quickly and efficiently derive deeper portfolio insights using an intuitive and user-friendly interface.

With a customizable interface that conveys the information that’s most important to the user, Exposure Manager’s analytics, enabled by an intuitive best-in-class user experience, can be configured without knowledge of SQL or support from IT.

This enhances the ability for customers to create quick insights into their portfolio or perform a deep dive into their book to make quick assessments.

Access Metrics That Matter shows how Exposure Manager leverages the RMS financial model to provide an exposed limit metric. This offers a consistent view of loss potential to enable precise identification of loss drivers.

The flexible interface provides users with precise control to quickly make informed decisions about their book and help identify threats and opportunities in the portfolio.

All of these benefits allow customers to become more incisive about their portfolio.

Earthquake Hazard: What Has New Zealand’s Kaikoura Earthquake Taught Us So Far?

The northeastern end of the South Island is a tectonically complex region with the plate motion primarily accommodated through a series of crustal faults. On November 14, as the Kaikoura earthquake shaking began, multiple faults ruptured at the same time culminating in a Mw 7.8 event (as reported by GNS Science).

The last two weeks have been busy for earthquake modelers. The paradox of our trade is that while we exist to help avoid the damage this natural phenomenon causes, the only way we can fully understand this hazard is to see it in action so that we can refine our understanding and check that our science provides the best view of risk. Since November 14 we have been looking at what Kaikoura tells us about our latest, high-definition New Zealand Earthquake model, which was designed to handle such complex events.

Multiple-Segment Ruptures

With the Kaikoura earthquake’s epicenter at the southern end of the faults identified, the rupture process moved from south to north along this series of interlinked faults (see graphic below). Multi-fault rupture is not unique to this event as the same process occurred during the 2010 Mw 7.2 Darfield Earthquake. Such ruptures are important to consider in risk modeling as they produce events of larger magnitude, and therefore affect a larger area, than individual faults would on their own.

Map showing the faults identified by GNS Sciences as experiencing surface fault rupture in the Kaikoura Earthquake.
Source: http://info.geonet.org.nz/display/quake/2016/11/16/Ruptured +land%3A+observations+from+the+air

In keeping with the latest scientific thinking, the New Zealand Earthquake HD Model provides an expanded suite of events that represent complex ruptures along multiple faults. For now, these are included only for areas of high slip fault segments in regions with exposure concentrations, but their addition increases the robustness of the tail of the Exceedance Probability curve, meaning clients get a better view of the risk of the most damaging, but lower probability events.

Landsliding and Liquefaction

While most property damage has been caused directly by shaking, infrastructure has been heavily impacted by landsliding and, to a lesser extent, liquefaction. Landslides and slumps have occurred across the region, most notably over Highway 1, an arterial route. The infrastructure impacts of the Kaikoura earthquake are a likely dress rehearsal for the expected event on the Alpine Fault. This major fault runs 600 km along the western coast of the South Island and is expected to produce an Mw 8+ event with a probability of 30% in the next 50 years, according to GNS Science.

As many as 80 – 100,000 landslides have been reported in the upper South Island, with some creating temporary dams over rivers and in some cases temporary lakes (see below). These dams can fail catastrophically, sending a sudden increase of water flow down the river.

 

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Examples of rivers blocked by landslides photographed by GNS Science researchers.

Source: http://info.geonet.org.nz/display/quake/2016/11/18/ Landslides+and+Landslide+dams+caused +by+the+Kaikoura+Earthquake

 

 

 

 

 

 

 

 

Liquefaction occurred in discrete areas across the region impacted by the Kaikoura earthquake. The Port of Wellington experienced both lateral and vertical deformation likely due to liquefaction processes in reclaimed land. There have been reports of liquefaction near the upper South Island towns (Blenheim, Seddon, Ward), but liquefaction will not be a driver of loss in the Kaikoura event to the extent it was in the Christchurch earthquake sequence.

RMS’ New Zealand Earthquake HD Model includes a new liquefaction component that was derived using the immense amount of new borehole data collected after the Canterbury Earthquake Sequence in 2010-2011. This new methodology considers additional parameters, such as depth to the groundwater table and soil-strength characteristics, that lead to better estimates of lateral and vertical displacement. The HD model is the first probabilistic model with a landslide susceptibility component for New Zealand.

Tsunami

The Kaikoura Earthquake generated tsunami waves that were observed in Kaikoura at 2.5m, Christchurch at 1m, and Wellington at 0.5m. The tsunami waves arrived in Kaikoura significantly earlier than in Christchurch and Wellington indicating that the tsunami was generated near Kaikoura. The waves were likely generated by offshore faulting, but also may be associated with submarine landsliding. Fortunately, the scale of the tsunami waves did not produce significant damage. RMS’ latest New Zealand Earthquake HD Model captures tsunami risk due to local ocean bottom deformation caused by fault rupture, and is the first model in the New Zealand market to do this, that is built from a fully hydrodynamic model.

Next Generation Earthquake Modeling at RMS

Thankfully the Kaikoura earthquake seems to have produced damage that is lower than we might have seen had it hit a more heavily populated area of New Zealand with greater exposures – for detail on damage please see my other blog on this event.

But what Kaikoura has told us is that our latest HD model offers an advanced view of risk. Released only in September 2016, it was designed to handle such a complex event as the Kaikoura earthquake, featuring multiple-segment ruptures, a new liquefaction model at very high resolution, and the first landslide susceptibility model for New Zealand.

New Zealand’s Kaikoura Earthquake: What Have We Learned So Far About Damage?

The Kaikoura Earthquake of November 14 occurred in a relatively low population region of New Zealand, situated between Christchurch and Wellington. The largest town close to the epicentral region is Blenheim, with a population near 30,000.

Early damage reports indicate there has been structural damage in the northern part of the South Island as well as to numerous buildings in Wellington. While most of this has been caused directly by shaking, infrastructure and ports across the affected region have been heavily impacted by landsliding and, to a lesser extent, liquefaction. Landslides and slumps have occurred across the northeastern area of the South Island, most notably over Highway 1, severing land routes to Kaikoura – a popular tourist destination.

The picture of damage is still unfolding as access to badly affected areas improves. At RMS we have been comparing what we have learned from this earthquake to the view of risk provided by our new, high-definition New Zealand Earthquake model, which is designed to improve damage assessment and loss quantification at location-level resolution.

No Damage to Full Damage

The earthquake shook a relatively low population area of the South Island and, while it was felt keenly in Christchurch, there have been no reports of significant damage in the city. The earthquake ruptured approximately 150 km along the coast, propagating north towards Wellington. The capital experienced ground shaking intensities at the threshold for damage, producing façade and internal, non-structural damage in the central business district. Although the shaking intensities were close to those experienced during the Cook Strait sequence in 2013, which mostly affected short and mid-rise structures, the longer duration and frequency content of the larger magnitude Kaikoura event has caused more damage to taller structures which have longer natural periods.

From: Wellington City Council

Within Wellington, cordons are currently in place around a few buildings in the CBD (see above) as engineers carry out more detailed inspections. Some are being demolished or are set to be, including a nine-story structure on Molesworth Street and three city council buildings. It should be noted that most of the damage has been to buildings on reclaimed land close to the harbor where ground motions were likely amplified by the underlying sediments.

From: http://www.stuff.co.nz/national/86505695/quakehit-wellington-building-at-risk-of-collapse-holds-up-overnight; The building on Molesworth street before the earthquake (L) and on Tuesday (R).

From: http://www.stuff.co.nz/national/86505695/quakehit-wellington-building-at-risk-of-collapse-holds-up-overnight; The building on Molesworth street before the earthquake (L) and after on November 16 (R).

Isolated incidences of total damage in an area of otherwise minor damage demonstrate why RMS is moving to the new HD financial modeling framework. The RMS RiskLink approach applies a low mean damage ratio across the area, whereas RMS HD damage functions allow for zero or total loss – as well as a distribution in between which is sampled for each event for each location. The HD financial modeling framework is able to capture a more realistic pattern of gross losses.

Business Interruption

The Kaikoura Earthquake will produce business interruption losses from a variety of causes such as direct property or content damages, relocation costs, or loss of access to essential services (i.e. power and water utilities, information technology) that cripple operations in otherwise structurally sound buildings. How quickly businesses are able to recover depends on how quickly these utilities are restored. Extensive landslide damage to roads means access to Kaikoura itself will be restricted for months. The New Zealand government has announced financial assistance packages for small business to help them through the critical period immediately after the earthquake. Similar assistance was provided to businesses in Christchurch after the Canterbury Earthquake Sequence in 2010-2011.

That earthquake sequence and others around the world have provided valuable insights on business interruption, allowing our New Zealand Earthquake HD model to better capture these impacts. For example, during the Canterbury events, lifelines were found to be repaired much more quickly in urban areas than in rural areas, and areas susceptible to liquefaction were associated with longer down times due to greater damage to underground services. The new business interruption model provides a more accurate assessment of these risks by accounting for the influence of both property and contents damage as well as lifeline downtime.

It remains to be seen how significant any supply chain or contingent business interruption losses will be. Landslide damage to the main road and rail route from Christchurch to the inter-island ferry terminal at Picton has disrupted supply routes across the South Island. Alternative, longer routes with less capacity are available.

Next Generation Earthquake Modeling at RMS

RMS designed the update to its New Zealand Earthquake High Definition (HD) model, released in September 2016, to enhance location-level damage assessment and improve the gross loss quantification with a more realistic HD financial methodology. The model update was validated with billions of dollars of claims data from the 2010-11 Canterbury Earthquake Sequence.

Scientific and industry lessons learned following damaging earthquakes such as last month’s in Kaikoura and the earlier event in Christchurch increase the sophistication and realism of our understanding of earthquake risk, allowing communities and businesses to shift and adapt – so becoming more resilient to future catastrophic events.