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Flood Modeling

Comparing Flood Maps

A presentation held in London drives home the point that flood modeling has a long way to go.
By: | December 18, 2017 • 6 min read

A greater validation of inland flooding data is required to improve the accuracy of U.S. flood models.

That was one of the key conclusions from presenters at the first comparison of U.S. inland flood risk modeling of its kind hosted by Ariel Re at Lloyd’s of London in November. The event, led by Dr. Federico Waisman, senior vice president, head of analytics, Ariel Re, showcased the U.S. flood models of four leading vendors: AIR, CoreLogic, KatRisk and Impact Forecasting.

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RMS pulled out of the presentation because their model was not ready on time.

Compared to their earthquake and hurricane counterparts, flood models for U.S. risks are still in their relative infancy, relying largely on limited National Flood Insurance Program (NFIP) data. But in the wake of the devastation of thousands of homes and businesses caused by the effects of Hurricanes Harvey, Irma and Maria, the need for better flood modeling has arguably never been greater.

“Having more validation data would always be helpful,” said KatRisk’s chief technology officer and co-founder, Stefan Eppert.

“While in the U.S. we have got very good hazard data and excellent organization of data, on the loss side it would be nice to have generally agreed standards.”

Cagdas Kafali, senior vice president, research and modeling, AIR Worldwide, said there also needs to be more focus on commercial data sets.

Federico Waisman, senior vice president, head of analytics, Ariel Re

“There is some residential data available, but it’s also going to be important to validate these models’ vulnerability when it comes to the commercial risks,” he said. “The problem is that there is a lot of engineering assumptions in the absence of actual claims data.

“It’s also very difficult to get to peril-specific and coverage-specific claims when it comes to multi-location policies with sublimits. Hopefully that data will be available in the future and that will help to enhance the models.”

Risk Variety

Aon Benfield Impact Forecasting’s head of research and development, Siamak Daneshvaran, said that a bigger problem is capturing the different types of flooding risk.

“Flood risk is spread all over the country,” he said.

“It’s not only in river bank areas; you can have flood in pluvial regions that might be outside of the flood plain maps that FEMA [Federal Emergency Management Agency] is producing.

“Therefore, the models need to laser in and generate more events to define the correct flood plain maps. Also, to capture events like Hurricane Harvey, where there was a large loss in downtown Houston, we really need to understand pluvial processes, drainage and all of those issues.”

In terms of available claims data, all four models draw on NFIP data to varying degrees, the panel surmised.

CoreLogic and KatRisk both use a combination of NFIP and company claims data, while Impact Forecasting supplements that with Aon’s own data to calibrate its model.

AIR’s Kafali, however, warned that when using NFIP data, its own limits shouldn’t be used as replacement values.

“Instead, in our model, we used actual replacement values from industry exposure data,” he said. “That gave us the actual cash value policies for contents so we could model them as an exposure.

“We have also been able to push the limits by looking at the data which has come from weather factors like storm surge. That has enabled us to make a lot of assumptions on the residential side, however, the commercial data is somewhat lacking.”

Flood models

Compared on a similar basis spread across 1.2m locations nationwide, AIR’s Inland Flood Model for the U.S. registered the highest number of flooding events per year, while CoreLogic’s U.S. Inland Flood Model: RQE v17.0 posted the lowest.

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AIR also pegged the largest average annual gross loss by region at $576.4 million — 3.1 times larger than the smallest, KatRisk’s SpatialKat U.S. Inland Flood Model, at $185.1 million.

In three out of four vendors (AIR, CoreLogic and KatRisk), California accounted for the biggest loss, followed by the Ohio and Texas-Gulf regions.

Then the models were compared based on three historical scenarios: Hurricane Harvey (a precipitation event), the 2016 Louisiana flood (hurricane) and the 1993 Great Midwest flood (riverine).

“The challenge for users of these models is to interpret and make a decision about the various sciences and assumptions made to form your own view of the risk. That challenge is much greater than in other models like earthquake and hurricane where many models have been developed over the years.” — Federico Waisman, senior vice president, head of analytics, Ariel Re

CoreLogic reported the highest gross loss for Harvey at $986.4 million, closely followed by Impact Forecasting’s U.S. Inland Flood Model v11 at $915.2 million.

KatRisk and AIR were at the lower end with $591.4 million and $497.1 million respectively.

The same is true of the average claim size, with CoreLogic coming in highest at $86,431, Impact Forecasting with $44,398, KatRisk $22,467 and AIR $11,338.

That correlated with the number of claims, with AIR reporting 43,845 claims, KatRisk 26,321, Impact Forecasting 20,613 and CoreLogic 11,413.

It was a similar story for the Great Midwest flood, with CoreLogic coming in highest for losses at $741.6 million and average claim size of $55,823, while it also identified the lowest number of claims at 13,284.

However, with the Louisiana flood, the one outlier was AIR, which estimated the largest loss at $124.3 million but the smallest average claim at $4,704. It also captured the largest number of claims at 26,434.

“AIR has the lowest average claim size across all three of the historic scenarios and CoreLogic the highest,” said Waisman.

“AIR also has the largest number of claims and CoreLogic the lowest.”

Kafali said that the difference in event frequency between the models could be down to the definition of an event.

“Event definition may be one reason why we have different numbers, because we might be defining events differently,” he said.

“It’s not like with earthquake and hurricane where you have a defined scale of measurement.”

Eppert added, “By rights, the event definition should be driven by contract terms. However, this has the downside that you have got a different event set for each contract, so there’s a compromise between adequately representing the terms that you insure and being able to communicate the losses.”

Biggest Challenges

Waisman concluded that while there were many similarities between the models’ results, there were also a lot of material deviations.

“In fact, the norm tends to be more deviations than similarities,” he said.

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“The differences tend to be higher when we extend the model to its limits, like higher return periods, or under extreme circumstances, like high deductibles, where they depart the most.”

He added: “The challenge for users of these models is to interpret and make a decision about the various sciences and assumptions made to form your own view of the risk. That challenge is much greater than in other models, like earthquake and hurricane, where many models have been developed over the years.

“Flood as a peril, by contrast, is extremely complex to model. The U.S. has a variety of precipitous weather patterns and not enough claims data, but I have no doubt that all four of these vendor models will help play a part in tackling this problem.”

Head of Lloyd’s risk aggregation David Clouston concluded, “Widespread flooding as a result of windstorms Harvey and Irma has once again highlighted the costs of natural catastrophes — both in terms of human suffering and economic hardship. The need for a deeper understanding of inland flood modeling is therefore more important than ever.” &

Alex Wright is a U.K.-based business journalist, who previously was deputy business editor at The Royal Gazette in Bermuda. You can reach him at [email protected]

More from Risk & Insurance

More from Risk & Insurance

Insurtech

Kiss Your Annual Renewal Goodbye; On-Demand Insurance Challenges the Traditional Policy

Gig workers' unique insurance needs drive delivery of on-demand coverage.
By: | September 14, 2018 • 6 min read

The gig economy is growing. Nearly six million Americans, or 3.8 percent of the U.S. workforce, now have “contingent” work arrangements, with a further 10.6 million in categories such as independent contractors, on-call workers or temporary help agency staff and for-contract firms, often with well-known names such as Uber, Lyft and Airbnb.

Scott Walchek, founding chairman and CEO, Trōv

The number of Americans owning a drone is also increasing — one recent survey suggested as much as one in 12 of the population — sparking vigorous debate on how regulation should apply to where and when the devices operate.

Add to this other 21st century societal changes, such as consumers’ appetite for other electronic gadgets and the advent of autonomous vehicles. It’s clear that the cover offered by the annually renewable traditional insurance policy is often not fit for purpose. Helped by the sophistication of insurance technology, the response has been an expanding range of ‘on-demand’ covers.

The term ‘on-demand’ is open to various interpretations. For Scott Walchek, founding chairman and CEO of pioneering on-demand insurance platform Trōv, it’s about “giving people agency over the items they own and enabling them to turn on insurance cover whenever they want for whatever they want — often for just a single item.”

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“On-demand represents a whole new behavior and attitude towards insurance, which for years has very much been a case of ‘get it and forget it,’ ” said Walchek.

Trōv’s mobile app enables users to insure just a single item, such as a laptop, whenever they wish and to also select the period of cover required. When ready to buy insurance, they then snap a picture of the sales receipt or product code of the item they want covered.

Welcoming Trōv: A New On-Demand Arrival

While Walchek, who set up Trōv in 2012, stressed it’s a technology company and not an insurance company, it has attracted industry giants such as AXA and Munich Re as partners. Trōv began the U.S. roll-out of its on-demand personal property products this summer by launching in Arizona, having already established itself in Australia and the United Kingdom.

“Australia and the UK were great testing grounds, thanks to their single regulatory authorities,” said Walchek. “Trōv is already approved in 45 states, and we expect to complete the process in all by November.

“On-demand products have a particular appeal to millennials who love the idea of having control via their smart devices and have embraced the concept of an unbundling of experiences: 75 percent of our users are in the 18 to 35 age group.” – Scott Walchek, founding chairman and CEO, Trōv

“On-demand products have a particular appeal to millennials who love the idea of having control via their smart devices and have embraced the concept of an unbundling of experiences: 75 percent of our users are in the 18 to 35 age group,” he added.

“But a mass of tectonic societal shifts is also impacting older generations — on-demand cover fits the new ways in which they work, particularly the ‘untethered’ who aren’t always in the same workplace or using the same device. So we see on-demand going into societal lifestyle changes.”

Wooing Baby Boomers

In addition to its backing for Trōv, across the Atlantic, AXA has partnered with Insurtech start-up By Miles, launching a pay-as-you-go car insurance policy in the UK. The product is promoted as low-cost car insurance for drivers who travel no more than 140 miles per week, or 7,000 miles annually.

“Due to the growing need for these products, companies such as Marmalade — cover for learner drivers — and Cuvva — cover for part-time drivers — have also increased in popularity, and we expect to see more enter the market in the near future,” said AXA UK’s head of telematics, Katy Simpson.

Simpson confirmed that the new products’ initial appeal is to younger motorists, who are more regular users of new technology, while older drivers are warier about sharing too much personal information. However, she expects this to change as on-demand products become more prevalent.

“Looking at mileage-based insurance, such as By Miles specifically, it’s actually older generations who are most likely to save money, as the use of their vehicles tends to decline. Our job is therefore to not only create more customer-centric products but also highlight their benefits to everyone.”

Another Insurtech ready to partner with long-established names is New York-based Slice Labs, which in the UK is working with Legal & General to enter the homeshare insurance market, recently announcing that XL Catlin will use its insurance cloud services platform to create the world’s first on-demand cyber insurance solution.

“For our cyber product, we were looking for a partner on the fintech side, which dovetailed perfectly with what Slice was trying to do,” said John Coletti, head of XL Catlin’s cyber insurance team.

“The premise of selling cyber insurance to small businesses needs a platform such as that provided by Slice — we can get to customers in a discrete, seamless manner, and the partnership offers potential to open up other products.”

Slice Labs’ CEO Tim Attia added: “You can roll up on-demand cover in many different areas, ranging from contract workers to vacation rentals.

“The next leap forward will be provided by the new economy, which will create a range of new risks for on-demand insurance to respond to. McKinsey forecasts that by 2025, ecosystems will account for 30 percent of global premium revenue.

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“When you’re a start-up, you can innovate and question long-held assumptions, but you don’t have the scale that an insurer can provide,” said Attia. “Our platform works well in getting new products out to the market and is scalable.”

Slice Labs is now reviewing the emerging markets, which aren’t hampered by “old, outdated infrastructures,” and plans to test the water via a hackathon in southeast Asia.

Collaboration Vs Competition

Insurtech-insurer collaborations suggest that the industry noted the banking sector’s experience, which names the tech disruptors before deciding partnerships, made greater sense commercially.

“It’s an interesting correlation,” said Slice’s managing director for marketing, Emily Kosick.

“I believe the trend worth calling out is that the window for insurers to innovate is much shorter, thanks to the banking sector’s efforts to offer omni-channel banking, incorporating mobile devices and, more recently, intelligent assistants like Alexa for personal banking.

“Banks have bought into the value of these technology partnerships but had the benefit of consumer expectations changing slowly with them. This compares to insurers who are in an ever-increasing on-demand world where the risk is high for laggards to be left behind.”

As with fintechs in banking, Insurtechs initially focused on the retail segment, with 75 percent of business in personal lines and the remainder in the commercial segment.

“Banks have bought into the value of these technology partnerships but had the benefit of consumer expectations changing slowly with them. This compares to insurers who are in an ever-increasing on-demand world where the risk is high for laggards to be left behind.” — Emily Kosick, managing director, marketing, Slice

Those proportions may be set to change, with innovations such as digital commercial insurance brokerage Embroker’s recent launch of the first digital D&O liability insurance policy, designed for venture capital-backed tech start-ups and reinsured by Munich Re.

Embroker said coverage that formerly took weeks to obtain is now available instantly.

“We focus on three main issues in developing new digital business — what is the customer’s pain point, what is the expense ratio and does it lend itself to algorithmic underwriting?” said CEO Matt Miller. “Workers’ compensation is another obvious class of insurance that can benefit from this approach.”

Jason Griswold, co-founder and chief operating officer of Insurtech REIN, highlighted further opportunities: “I’d add a third category to personal and business lines and that’s business-to-business-to-consumer. It’s there we see the biggest opportunities for partnering with major ecosystems generating large numbers of insureds and also big volumes of data.”

For now, insurers are accommodating Insurtech disruption. Will that change?

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“Insurtechs have focused on products that regulators can understand easily and for which there is clear existing legislation, with consumer protection and insurer solvency the two issues of paramount importance,” noted Shawn Hanson, litigation partner at law firm Akin Gump.

“In time, we could see the disruptors partner with reinsurers rather than primary carriers. Another possibility is the likes of Amazon, Alphabet, Facebook and Apple, with their massive balance sheets, deciding to link up with a reinsurer,” he said.

“You can imagine one of them finding a good Insurtech and buying it, much as Amazon’s purchase of Whole Foods gave it entry into the retail sector.” &

Graham Buck is a UK-based writer and has contributed to Risk & Insurance® since 1998. He can be reached at riskletters.com.