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RMS LAUNCHES NEW PROBABILISTIC FLOOD MODELS TO SIMPLIFY FLOOD RISK MANAGEMENT
ACROSS SOUTHEAST ASIA



Daniel Bernet February 25, 2022

The floods that severely impacted Malaysia and Indonesia between mid-December
2021 and mid-January 2022 remind insurers of the need to better manage flood
risk in Southeast Asia, which also includes Singapore and Thailand. Thankfully,
these recent floods did not reach the losses of the landmark 2011 Thailand
Floods that still rank as second-highest insured flood loss ever recorded.

To give (re)insurers the confidence to move forward with flood risk across a
complex region, we are excited to announce the launch of the RMS® Southeast Asia
Inland Flood HD Models. The first fully probabilistic models for Southeast Asia
– covering Indonesia, Malaysia, Singapore, and Thailand – offer a unified and
fully correlated view of inland flood risk. The models give (re)insurers the
necessary tools to reduce portfolio blind spots occurring from intra- and
interseasonal flood events such as tropical storms and monsoons, which caused
the 2011 Thailand Floods as well as the recent flooding in Malaysia and
Indonesia.

Remove Blind Spots With the Most Comprehensive View of Flood Risk in the Region

Looking at the regional climate, it is predominantly tropical with distinct dry
and wet seasons, driven by monsoon winds. The southwest monsoon that typically
occurs between May and September brings the wet season to northern Thailand and
overlaps with peak typhoon activity between June and October – amplifying flood
risk in the region.

It was a heavy monsoon season from May to October 2011, and a trigger event –
Tropical Storm Nock-ten in July, that caused the 2011 Thailand Floods. But the
recent December 2021/January 2022 floods in Malaysia and Indonesia were
triggered by the northeast monsoon that draws Pacific air masses southwestward.
The northeast monsoon brings the rainy season between November and March to
Indonesia, Malaysia, Singapore, and southern parts of Thailand.

Both events highlight the complex interactions between monsoons, tropical
storms, and typhoons, all with the potential to cause widespread flooding across
multiple countries at the same time. There is a need to understand the spatial
and temporal correlation of risk from all sources of inland flooding, and as
flood events do not respect country borders, a need for a consistent view of
flood risk across the region.

To address this challenge, the Southeast Asia Inland Flood HD Models offer a
consistent set of correlated events across the insurance markets of Thailand,
Malaysia, Singapore, and Indonesia. Our models capture all sources of inland
flood risk: fluvial and pluvial flooding from all precipitation sources
including monsoon rains, heavy rainstorms, and tropical cyclones. A river
network of over 76,000 kilometers is explicitly modeled across the region
(Figure 1), including the upper reaches of rivers that rise in neighboring
countries, such as the Mekong River that flows from China through Thailand.

Figure 1: Geographic coverage of the RMS Southeast Asia Inland Flood HD Models
highlighting the river network that expands over the model domain’s extent, but
is fully modeled as it influences flood risk further downstream.

Get Location-level Insights With the RMS High-Definition (HD) Modeling Framework

Flood is a peril characterized by a particularly high hazard gradient. For
example, while one building may experience significant flooding, a neighboring
building may stay dry. This could be due to small differences in the terrain or
the presence of local flood defenses. It is therefore critical that flood models
can realistically reflect these small-scale variations.

To capture these characteristics at a high temporal and spatial resolution, the
Southeast Asia Inland Flood HD Models leverage the latest data, science, as well
as the latest RMS flood modeling technology. The models are based on
high-resolution digital terrain models (DTMs), up to 20-meter resolution in high
exposure areas, with the flood hazard stored on a uniform grid at approximately
38-meter resolution.

Other model features include enhanced modeling of aggregate and low-resolution
exposure, to allow for ground-up simulation of losses at location level even
with coarse input exposure data, and temporal simulation for applying time-based
policy terms such as hours clauses.

Flood losses are not only determined by highly variable hazard, but also the
different ways exposures experience flood damage. To capture exposure
characteristics and how they react to flooding, model users benefit from over
100 flood-specific damage curves for building and contents per country, in
addition to 12 secondary modifiers.

Whether you capture your own detailed exposure data or allow the detailed
building inventory in the models to fill in the gaps, the four-parameter
vulnerability uncertainty distribution ensures that the model output
realistically represents the loss and claims distribution of flood events in the
region.

Building a Realistic View of Risk in the Face of Rapid Urbanization

Apart from the complex natural processes driving flood risk in space and time,
factors such as rapid urbanization and flood protection measures can have
significant impact on the level of flood risk. This is especially evident in
major cities such as Bangkok in Thailand, Kuala Lumpur in Malaysia, and Jakarta
in Indonesia. Kuala Lumpur, for example, has grown from around a quarter of a
million population in 1950 to nearly 8.2 million in the metropolitan area today,
with about 30 percent of this growth occurring since 2010.

For cities that have experienced rapid urbanization, gaining a realistic view of
flood risk is a great challenge. Building the model on the latest data and
considering the effect of flood-generating mechanisms of these vast built-up
areas is crucial.

Therefore, the RMS flood model developers have spent a lot of effort to gather,
review, and augment the best-available data, including many local data
providers. Moreover, for the first time, they have explicitly accounted for the
impact of the drainage network to provide a more realistic estimate of surface
water runoff in these important urban areas.

The models also include the most robust event set capturing more than 800,000
flood events based on 50,000 years of continuous simulation. By coupling
high-resolution insights, with hundreds of thousands of events and decades of
validated loss data, (re)insurers have the insights needed to translate flood
risk in high-risk areas into policy terms.

Providing Model Coverage for How Risk Is Underwritten

The RMS Southeast Asia Inland Flood HD Models are the most sophisticated flood
models available on the market. They form part of our wider flood model
solutions across the Asia-Pacific region and around the globe. To help model
risk for how its written in the region, clients can pair the flood models with
our existing regional earthquake models, or leverage RMS Global Flood Hazard
Maps to manage flood risk in territories not covered by the probabilistic flood
models.

Overall, RMS flood model solutions greatly enhance the management of risk in the
region and enables you to outperform in these rapidly growing economies and
markets.

The four RMS Southeast Asia Inland Flood HD Models – same as all HD models, run
on the open and modular, cloud-based RMS Intelligent Risk Platform™. The models
can be licensed individually, all together, or accessed through RMS Analytical
Services. Click here to find out more.

Join RMS on March 01, 2022 3 p.m. SGT (Singapore), or at 3 p.m. CET (Europe) for
a webinar entitled "Southeast Asia Flood Risk is Complex, Managing it Shouldn’t
Be" - click here to find out more and register.

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DANIEL BERNET

Senior Product Manager, Global Climate Team

As a senior product manager, Daniel is responsible for the Europe and Southeast
Asia Inland Flood Models. He has been with RMS for more than 3 years, joining
RMS after conducting doctoral and postdoctoral research at the Mobiliar Lab for
Natural Risks, University of Bern, focusing on the occurrence and modeling of
surface water flooding.

Prior to academia, he was working for a small Swiss NGO managing different
water-related projects in Nepal, following the conclusion of a bachelor's and
master's degree in Environmental Engineering at the Swiss Federal Institute of
Technology ETH Zurich.

 * #Southeast Asia Flood
 * #Thailand
 * #Southeast Asia Inland Flood HD Models
 * #2011 Thailand Floods
 * #Malaysia Floods
 * #Malaysia
 * #Singapore Flood
 * #indonesia


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