Monthly Archives: August 2016

PMFBY Crop Insurance in India: A Big Success?

With an in­crease in the up­take of crop in­sur­ance in In­dia – a ru­mored tripling of crop in­sur­ance pre­mi­ums in 12 months – fol­low­ing the Modi gov­ern­men­t’s launch of the PMFBY scheme, can the scheme be con­sid­ered a suc­cess?

Yield-based poli­cies, such as PMFBY, pro­vide at­trac­tive cov­er­age for farm­ers and pol­icy hold­ers, not least be­cause the In­dian cen­tral gov­ern­ment and state gov­ern­ments heav­ily sub­sidize pre­mi­ums by 98 percent. Old weather-based poli­cies, while easy to struc­ture and trig­ger (such as a short­fall in pre­cip­i­ta­tion or lower than av­er­age tem­per­a­ture), left farm­ers ex­posed to un­ac­cept­able ba­sis risk. In the­ory, yield-based poli­cies are sim­pler to ad­min­is­ter and pro­vide a bet­ter ser­vice for their in­sureds – the farm­ers.

Re­ports this year es­ti­mate that five percent of the mar­ket will use the older weather-in­dex poli­cies, whilst 95 percent of the pre­mium will be writ­ten un­der PMFBY. This rep­re­sents a dra­matic re­ver­sal compared to the pre­vi­ous year. Re­ports also es­ti­mate that the mar­ket has at least tripled, and some say quadru­pled, to Rs 18,000 crores (approximately USD $3 billion). It ap­pears that the new scheme has proved at­trac­tive. The participation of four Indian public service utilities will only add to that.

Nonethe­less, praise has not been uni­ver­sal and con­cerns re­main. Early sceptics warned that the scheme was not ad­dress­ing many ba­sic is­sues, in­clud­ing the risk that PMFBY is prac­ti­cally just an in­sur­ance scheme for the farmer’s cred­i­tors, with others con­tinuing that crit­i­cism late in to the sea­son. There are also reports that some state govern­ments won’t be able to pay the costs of the pre­mium sub­si­dies.

It seems that, whilst the In­dian gov­ern­ment has made strides to­wards a suc­cess­ful im­ple­men­ta­tion, there re­main some ques­tions to be an­swered. On balance, through a dou­bling of in­sur­ance pen­e­tra­tion (by some mea­sures) in just 12 months, this is surely a sign of success.

Launching a New Journal for Terrorism and Cyber Insurance

Natural hazard science is commonly studied at college, and to some level in the insurance industry’s further education and training courses. But this is not the case with terrorism risk. Even if insurance professionals learn about terrorism in the course of their daily business, as they move into other positions, their successors may begin with hardly any technical familiarity with terrorism risk. It is not surprising therefore that, even fifteen years after 9/11, knowledge and understanding of terrorism insurance risk modeling across the industry is still relatively low.

There is no shortage of literature on terrorism, but much has a qualitative geopolitical and international relations focus, and little is directly relevant to terrorism insurance underwriting or risk management.

As a step towards redressing the imbalance in available terrorism literature, a new online journal, The Journal of Terrorism and Cyber Insurance, has been established; its launch is to coincide with the fifteenth anniversary of 9/11. The journal has been welcomed and supported by global terrorism insurance pools, and its launch will be publicized at the annual terrorism pools congress in Canberra, Australia, on October 7, 2016.

Originally conceived as a journal of terrorism insurance, coverage has been extended to include cyber risk, recognizing the increasing insurance industry concerns over cyber terrorism and the burgeoning insurance market in cyber risk. The aim of the open access journal is to raise the industry’s level of knowledge and understanding of terrorism risk. By increasing information transparency for this subject the editorial board hopes to facilitate the growth of the terrorism insurance market, which serves the risk management requirements of the wider international community. The first issue is a solid step in this direction, and will include articles on the ISIS attacks in Paris in November 2015; terrorism insurance in France and Australia; parametric terrorism insurance triggers; non-conventional threats; the clean-up costs of anthrax, and the terrorist use of drones.

The four founding editors of the journal have extensive knowledge of the field. The managing editor is Rachel Anne Carter, who has terrorism insurance administrative experience with both OECD and U.K. Pool Re. Dr. Raveem Ismail, specialty terrorism underwriter at Ariel Re, brings to the editorial board detailed direct terrorism and political risk underwriting knowledge. Padraig Belton is a writer with extensive political risk expertise, having served as a correspondent in the Middle East and Pakistan. As chief architect of the RMS terrorism model, I will bring terrorism risk modeling expertise to the team and have the responsibility and pleasure to review all article submissions. I look forward to sharing insights from the journal with subscribers to this blog.

No More Guessing Games for Marine Insurers

Huge ports mean huge amounts of cargo. Huge amounts of cargo mean huge accumulations of risk.

As a guiding principle about where marine insurers are exposed to the highest potential losses, it seems reasonable enough. But in fact, as RMS research has proven this week, this proposition may be a bit misleading. Surprisingly, a port’s size and its catastrophe loss potential are not strongly correlated.

Take the Port of Plaquemines, LA which is just south-east of New Orleans. It is neither well known nor big in comparison with others around the world. Yet it has the third highest risk in the world of insurance loss due to catastrophe: our analysis revealed its 500-year marine cargo loss from hurricane would be $1.5 billion.

Plaquemines is not an isolated case. There were other smaller ports in our ranking: Pascagoula, MS in the United States ranks 6 on our list with a potential $1 billion marine cargo loss due to storm surge and hurricane; Bremerhaven in Germany (ranked 4th at $1 billion) and Le Havre in France (ranked 10th at $0.7 billion).

Asia-Pacific ports featured less frequently, but worryingly one Asia port topped the list: Nagoya, Japan was number 1 ($2.3 billion potential losses) with Guangzhou, China a close second ($2 billion). Our analysis modeled risk posed by earthquake, wind, and storm surge perils in a 500-year return period across 150 ports – the top ten results are further down this blog.

Ports At Risk For Highest Lost
(500 year estimated catastrophe loss for earthquake, wind, and storm surge perils)

Estimated Marine Cargo Loss in Billions USD
1 Nagoya, Japan 2.3
2 Guangzhou, China 2.0
3 Plaquemines, LA, U.S. 1.5
4 Bremerhaven, Germany 1.0
5 New Orleans, LA, U.S. 1.0
6 Pascagoula, MS, U.S. 1.0
7 Beaumont, TX, U.S. 0.9
8 Baton Rouge, LA, U.S. 0.8
9 Houston, TX, U.S. 0.8
10 Le Havre, France 0.7

* Losses rounded to one decimal place.

Our analysis demonstrates what we at RMS have long suspected: outdated marine risk modeling tools and incomplete data obscure many high-risk locations, big and small. These ports are risky because of the natural perils they face and the cargos which transit through them, as well as the precise way those cargos are stored. But many in the marine sector don’t have these comprehensive insights. Instead they have to make do with a guessing game in determining catastrophe risk and port accumulations. And with the advanced analytics available in 2016 this is no longer good enough.

Big Port or Small – Risk Can Now Be Determined

Back to that seemingly simple proposition about the relationship between port size and insurance risk which I began this blog with. As the table above demonstrates, smaller ports can also present a huge risk.

But the bigger ships and bigger ports brought about by containerization have led, overall, to a bigger risk exposure for marine insurers. Not least because larger vessels have rendered many river ports inaccessible forcing shippers to rely on seaside ports, which are more vulnerable to hurricanes, typhoons, and storm surge.

The value of global catastrophe-exposed cargo is already huge and is likely to keep growing. But the right tools, which use the most precise data, can reveal where the risk of insurance loss is greatest. Leveraging these tools, (re)insurers can avoid dangerous cargo accumulations and underwrite with greater confidence.

Which means that, at last, the guessing game can stop.

In a box: Our ranking of high risk ports used the new RMS Marine Cargo Model™, with geospatial analysis of thousands of square kilometers of satellite imagery across ports in 43 countries. RMS’ exposure development team used a proprietary technique for allocating risk exposure across large, complex terminals to assess the ports’ exposure and highlight the risk of port aggregations. The model took into account:

  • Cargo type (e.g. autos, bulk grains, electronics, specie)
  • Precise storage location (e.g. coastal, estuarine, waterside or within dock complex)
  • Storage type (e.g. open air, warehouse, container — stacked or ground level)
  • Dwell time (which can vary due to port automation, labor relations and import/export ratios)

Insurance-Linked Securities in Asia – Looking Out for the Tipping Point

We were at a conference in Singapore, pushing to develop a market that doesn’t yet really exist. Grounds, you might think, for frustration.

And yet my RMS capital markets colleague, Jin Shah, and I were upbeat and, in truth, a little excited.

So often we end up at ILS conferences talking to the same audiences about the same topics. But this was different. The inaugural ILS Asia Conference organized by, the de facto bulletin-board for the ILS industry, had 170 industry experts and practitioners from the region gathered in the Raffles Hotel ballroom.

The aim of the event was to demonstrate the ILS industry’s commitment to building a global footprint and developing expertise in the asset class among Asia’s investors and reinsurers. This conference was exciting because we can see the Asia insurance industry will approach a tipping point in the next decade or so, resulting in increased appetite in Asian ILS instruments from both sides. Let me explain how.

An Insurance Market Which Has Not Yet Matured

Currently in many Asian countries, the insurance market is still developing and the concept of insurance as a social and economic “good” is still not culturally normalized. In addition, mandatory insurance outside of auto/motor is, in some places, almost non-existent, with individuals looking instinctively to family and other social networks to provide financial safety-net.

Because of these factors, combined with generally lower levels of disposable income, property insurance penetration, in particular, is comparatively low in Asia. Thus, the region only contributes a small amount to reinsurer’s portfolios and capital loads. So they don’t yet need to transfer some of that risk to the capital markets as is the case in core, concentrated regions such as the U.S., Japan, and Europe. The economics of ILS in Asia are challenging to say the least, and in some cases, make fully collateralized products “non-starters” from a competitive point of view.

Growing Populations and Changing Demographics

But that’s the current environment. The future growth of the middle classes, particularly in China and India, will fuel increasing demand for all forms of insurance as more people chose to protect their assets against damage and loss. Given the sheer size of the population and their rate of growth, it is not inconceivable that within ten years these markets could represent a similar level of risk concentration to (re)insurers as the U.S., Europe, or Japan.

And that’s the tipping point.

In certain Asian countries, the ILS sector is already developed. For a number of years, Australian insurers have been tapping the capital markets as a strategic element of their outwards protection. Japanese risk has been a core part of the risk available in both the cat bond and collateralized re markets. Outside of these more mature markets, last year China Re issued their Panda Re cat bond which, whilst only being a $50 million dip-of-a-toe in the water, showed that ILS funds were keen to accept China risk and pave the way for larger issuances in the future.

And with social, demographic and economic changes in the years ahead Asia will provide a natural hunting ground for ILS funds, keen to leverage their broad and diversified capital base to support the local insurance market’s continued growth.

Sensing this future tipping point too, the Artemis conference was attended by more than 25 industry stalwarts who’d travelled from London, Bermuda, New York, San Francisco, Japan, and Australia to bring the conversation to new audiences. ILS investors are clearly looking to this region to diversify their own portfolios, both as a risk management measure and with an eye to the rapid growth occurring in the region – and the opportunities it presents.

Searching for Clues After the Ecuador Earthquake

Reconnaissance work is built into the earthquake modeler’s job description – the backpack is always packed and ready. Large earthquakes are thankfully infrequent, but when they do occur, there is much to be learned from studying their impact, and this knowledge helps to improve risk models.

An RMS reconnaissance team recently visited Ecuador. Close to 7pm local time, on April 16, 2016, an Mw7.8 earthquake struck between the small towns of Muisne and Pedernales on the northwestern coast of Ecuador. Two smaller, more recent earthquakes have also impacted the area, on July 11, 2016 an Mw5.8 and Mw6.2, fortunately with no significant damage.

April’s earthquake was the strongest recorded in the country since 1979 and, at the time of writing, the strongest earthquake experienced globally so far in 2016. The earthquake caused more than 650 fatalities, more than 17,600 injuries, and damage to more than 10,000 buildings.

Two weeks after the earthquake, an RMS reconnaissance team of engineers started their work, visiting five cities across the affected region, including Guayaquil, Manta, Bahía de Caráquez, Pedernales, and Portoviejo. Pedernales was the most affected, experiencing the highest damage levels due to its proximity to the epicenter, approximately 40km to the north of the city.

Sharing the Same Common Vulnerability

The majority of buildings in the affected region were constructed using the same structural system: reinforced concrete (RC) frames with unreinforced concrete masonry (URM) infill. This type of structural system relies on RC beams and columns to resist earthquake shaking, with the walls filled in with unreinforced masonry blocks. This system was common across residential, industrial, and commercial properties and across occupancies, from hospitals and office buildings to government buildings and high-rise condominiums.

URM infill is particularly susceptible to damage during earthquakes, and for this reason it is prohibited by many countries with high seismic hazard. But even though Ecuador’s building code was updated in 2015, URM infill walls are still permitted in construction, and are even used in high-end residential and commercial properties.

Without reinforcing steel or adequate connection to the surrounding frame, the URM often cracks and crumbles during strong earthquake shaking. In some cases, damaged URM on the exterior of buildings falls outward, posing safety risks to people below. And for URM that falls inward, besides posing a safety risk, it often causes damage to interior finishes, mechanical equipment, and contents.

Across the five cities, the observed damage ranged from Modified Mercalli Intensity (MMI) 7.0-9.0. For an MMI of 7.0, the damage equated to light to moderate damage of URM infill walls, and mostly minimal damage to RC frames with isolated instances of moderate-to-heavy damage or collapse. An MMI of 9.0, which based on RMS observations, occurred in limited areas, meant moderate to heavy damage of URM infill walls and slight to severe damage or collapse to RC frames.

While failure of URM infill was the most common damage pattern observed, there were instances of partial and even complete structural collapse. Collapse was often caused, at least in part by poor construction materials and building configurations, such as vertical irregularities, that concentrated damage in particular areas of buildings.

Disruption to Business and Public Services

The RMS team also examined disruption to business and public services caused by the earthquake. A school in Portoviejo will likely be out of service for more than six months, and a police station in Pedernales will likely require more than a year of repair work. The disruption observed by the RMS team was principally due to direct damage to buildings and contents. However, there was some disruption to lifeline utilities such as electricity and water in the affected region, and this undoubtedly impacted some businesses.

RMS engineers also visited four public hospitals and clinics, with damage ranging from light to complete collapse. The entire second floor of a clinic in Portoviejo collapsed. A staff doctor told RMS that the floor was empty at the time and all occupants, including patients, evacuated safely.

Tourism was disrupted, with a few hotels experiencing partial or complete collapse. In some cases, even lightly damaged and unaffected hotels were closed as they were within cordoned-off zones in Manta or Portoviejo.

Tuna is an important export product for Ecuador. Two plants visited sustained minor structural damage, with unanchored machinery requiring repositioning and recalibration. One tuna processing plant reached 100% capacity just 16 days after the earthquake. Another in Manta reached 85% capacity about 17 days after the earthquake, and full capacity was expected within one month.

The need for risk differentiation

Occupancy, construction class, year built, and other building characteristics influence the vulnerability of buildings and, consequently, the damage they sustain during earthquakes. Vulnerability is so important in calculating damage from earthquakes that RMS model developers go to great lengths to ensure that each country’s particular engineering and construction practices are accurately captured by the models. This approach enables the models to differentiate risk across thousands of different factors.

Residential insurance penetration in Ecuador is still relatively low for commercial buildings and privately owned or financed homes, but higher amongst government-backed mortgages, as these require insurance. The knowledge gained from reconnaissance work is fundamental to our understanding of earthquake risk and informs future updates to RMS models. Better models will improve the insurance industry’s understanding and management of earthquake risk as insurance penetration increases both here and around the world.