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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

2018 Risk All Stars

Stop Mitigating Risk. Start Conquering It Like These 2018 Risk All Stars

The concept of risk mastery and ownership, as displayed by the 2018 Risk All Stars, includes not simply seeking to control outcomes but taking full responsibility for them.
By: | September 14, 2018 • 3 min read

People talk a lot about how risk managers can get a seat at the table. The discussion implies that the risk manager is an outsider, striving to get the ear or the attention of an insider, the CEO or CFO.

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But there are risk managers who go about things in a different way. And the 2018 Risk All Stars are prime examples of that.

These risk managers put in gear their passion, creativity and perseverance to become masters of a situation, pushing aside any notion that they are anything other than key players.

Goodyear’s Craig Melnick had only been with the global tire maker a few months when Hurricane Harvey dumped a record amount of rainfall on Houston.

Brilliant communication between Melnick and his new teammates gave him timely and valuable updates on the condition of manufacturing locations. Melnick remained in Akron, mastering the situation by moving inventory out of the storm’s path and making sure remediation crews were lined up ahead of time to give Goodyear its best leg up once the storm passed and the flood waters receded.

Goodyear’s resiliency in the face of the storm gave it credibility when it went to the insurance markets later that year for renewals. And here is where we hear a key phrase, produced by Kevin Garvey, one of Goodyear’s brokers at Aon.

“The markets always appreciate a risk manager who demonstrates ownership,” Garvey said, in what may be something of an understatement.

These risk managers put in gear their passion, creativity and perseverance to become masters of a situation, pushing aside any notion that they are anything other than key players.

Dianne Howard, a 2018 Risk All Star and the director of benefits and risk management for the Palm Beach County School District, achieved ownership of $50 million in property storm exposures for the district.

With FEMA saying it wouldn’t pay again for district storm losses it had already paid for, Howard went to the London markets and was successful in getting coverage. She also hammered out a deal in London that would partially reimburse the district if it suffered a mass shooting and needed to demolish a building, like what happened at Sandy Hook in Connecticut.

2018 Risk All Star Jim Cunningham was well-versed enough to know what traditional risk management theories would say when hospitality workers were suffering too many kitchen cuts. “Put a cut-prevention plan in place,” is the traditional wisdom.

But Cunningham, the vice president of risk management for the gaming company Pinnacle Entertainment, wasn’t satisfied with what looked to him like a Band-Aid approach.

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Instead, he used predictive analytics, depending on his own team to assemble company-specific data, to determine which safety measures should be used company wide. The result? Claims frequency at the company dropped 60 percent in the first year of his program.

Alumine Bellone, a 2018 Risk All Star and the vice president of risk management for Ardent Health Services, faced an overwhelming task: Create a uniform risk management program when her hospital group grew from 14 hospitals in three states to 31 hospitals in seven.

Bellone owned the situation by visiting each facility right before the acquisition and again right after, to make sure each caregiving population was ready to integrate into a standardized risk management system.

After consolidating insurance policies, Bellone achieved $893,000 in synergies.

In each of these cases, and in more on the following pages, we see examples of risk managers who weren’t just knocking on the door; they were owning the room. &

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Risk All Stars stand out from their peers by overcoming challenges through exceptional problem solving, creativity, clarity of vision and passion.

See the complete list of 2018 Risk All Stars.

Dan Reynolds is editor-in-chief of Risk & Insurance. He can be reached at [email protected]