by-state losses ranged widely.
By line of business, residential (
including mobile homes) and commercial (
including industrial assets) shared in the
losses almost equally, as seen in Figure 2.
Figure 3 shows the seasonal distribution of the flood events during the year.
Inland flood seasonality — which affects
the time it takes to dry a building — can
have a sizable effect on losses.
The second most costly event during
the modeled year is a February storm that
reached from Texas to Connecticut and
affected 19 states, as shown in Figure 4.
With ground-up losses of $22.4 billion,
this lengthy, seven-day event highlights
some of the many complex considerations in assessing inland flood loss potential. Progressing from northwest Texas
to Connecticut, flooding caused damage in more than 600 counties, covering
218,834 square miles. Impacts included
riverine flooding in unprotected areas,
failed levees (in Nashville, Tennessee and
Louisville, Kentucky), and off-floodplain
flooding from excessive precipitation.
Probing portfolio resilience
The scenario year detailed here is not
an extreme occurrence or tail event. Al-
though the industry ground-up loss for
this inland flood scenario has a modeled
annual EP of about one percent (which
equates to a 100-year return period), far
greater losses are possible.
Responsible risk management includes
preparing for a wide range of loss sce-
narios. Using model scenarios to probe a
portfolio’s strengths and weaknesses will
help insurers respond effectively when di-
saster does strike. Being attentive to best
practices for an inland flood model can
help ensure that companies achieve the
most realistic loss estimates:
• Address the potential for increased
losses due to demand surge.
Catastrophic flood events and the
property damage they cause take place
regularly in the U.S. Advanced catastrophe models — thoroughly validated with
data from a wide variety of sources —
help insurers and reinsurers gain a global
perspective on their overall risk from inland flood. By carefully analyzing model
results, risk managers can prepare for a
range of contingencies including megadisasters.
Boyko Dodov, Ph.D., is assistant vice
president and director of flood modeling at
catastrophe modeling firm AIR Worldwide.
Figure 3. Approximately one-third of the inland flood events in the modeled year occurred
in cooler months, which can mean slower drying times and higher losses.
Jan Feb Mar Apr May Jun Jul Aug Sept Oct Nov Dec
Figure 4. This February storm affected 19 states, with ground-up losses of $22.4 billion.
Figure 2. Ground-up loss (in USD billions)
by line of business for the modeled year.