FCHLPM 2009 Standards
Meeting to Determine Acceptability
RMS® North Atlantic Hurricane Model RiskLink 11.0.SP1
June 2, 2011
Tallahassee, FL
© 2011 Risk Management Solutions, Inc. 2
Agenda
Hurricane Model Component Overview
– Key Changes in model
– Changes in Output Ranges
Changes to Submission since original submission
Standards
© 2011 Risk Management Solutions, Inc.
FCHLPM Presentation Overview
3
-Michael Young
© 2011 Risk Management Solutions, Inc.
After redeveloping key components, the statewide zero
deductible AAL on the FHCF aggregate exposure changes
by approximately 6.5%.
Statewide Model Change
4
Time Period Produced by Model
Current Submission $3.47 billion
Previously Accepted
Submission$3.26 billion
Percentage Change Current
Submission/Previously
Accepted Submission6.44%
Form S-5: AAL Zero Deductible Loss Cost
© 2011 Risk Management Solutions, Inc.
Framework for Windstorm Catastrophe Modeling
Stochastic Track
Wind Field Model
FinancialLoss
9 0 %
Vulnerability
Basin-wide track and parameter simulation and calibration
Pressure history simulation and calibration
Importance sampling of simulated tracks
Time-stepping wind profile calculation
Directional factors for surface roughness upstream of over-land location
Variable Resolution Grid
Engineering model calibrated with historical claims
Hundreds of vulnerability classes based on material, height, occupancy, and year built
Mitigation measures
Allocates loss to policy holder, insurer, reinsurer
RED = Changes
© 2011 Risk Management Solutions, Inc.
Disclosure G-1.5.a change classifications
– SIGNIFICANT anything that affects model output
Highlight Two Key Changes
Inland Filling Model
New Vulnerability Regions
Other “Significant”
– NON-SIGNIFICANT changes with negligible effects
Change Categories
6
© 2011 Risk Management Solutions, Inc.
Inland Filling
7
© 2011 Risk Management Solutions, Inc.
“Inland filling” characterizes how the eye of the storm “fills” after landfall
and the pressure increases as hurricanes are removed from their
primary energy source
Previous model based on functional form of Kaplan and DeMaria (1995)
model
Development of a new statistical model is limited by historical data
8
Pressure time
series from
landfall
Charley
Irene
Challenges in Building an Inland Filling Model
© 2011 Risk Management Solutions, Inc.
Three year R&D project involving a team of six PhDs from
RMS
RMS worked with leading experts in Hurricane modeling
Dave Nolan - Associate Professor at University of Miami
10+ years experience in numerical simulations
Coauthor on inland filling model paper
Investment in Inland Filling Research
9
© 2011 Risk Management Solutions, Inc.
Bringing New Modeling Methods to Fill the Gaps
10
RMS conducted largest ever numerical modeling study
(WRF) of hurricane behavior during landfall
– Simulated over 1000 years of hurricane landfalls in realistic
mesoscale circulations
– Identified new relationships between predictors and filling rates
– New model improves fit to historical record
Peer reviewed methodology
“Using Mesoscale Simulations to Train
Statistical Models of Tropical Cyclone
Intensity over Land” ,
Colette, A., Leith N., Daniel, V., Bellone, E.,
Nolan D.S.
Monthly Weather Review Vol. 138, No. 6.(June 2010)
© 2011 Risk Management Solutions, Inc.
Consideration of
multiple
storm-specific
predictors
Improved ability to
produce full range
of filling rates
observed in nature
More Physically Realistic Inland Filling Model
11
Comparison of bounds of RMS filling model with key historical storms.
© 2011 Risk Management Solutions, Inc.
RMS also engaged in other external reviews to
validate that our methodology and models were
sound and state-of-the-art.
– Bob Hart (Associate Professor, Florida State University)
Reviewer for the inland filling model
10 years of experience in hurricane simulations
Quotes from Hart’s review included in Appendix A
Model Reviewed and Validated by Independent Expert
12
“Key state of the art science additions to the model include … incorporation of an improved inland decay model that models much more correctly the rate of decay inland.”
© 2011 Risk Management Solutions, Inc.
Cumulative Changes to 100-Year Wind Speed
13
version8.0.1a
version 11.0.SP1
Change in wind speed
Decrease along coastline
Increase inland areas
© 2011 Risk Management Solutions, Inc.
Point of Reference - ASCE 7-10 100 Yr Hazard
14
150
110
130
120
140
100
ASCE 7-10 Wind speed Contours
RMS Model100 Yr Windspeeds
100-yr Wind Hazard 3-sec peak gusts using “open terrain”
New hazard map compares
favorably with 100 year return
period map used by design
community, released May
2010
© 2011 Risk Management Solutions, Inc.
Vulnerability Updates
15
© 2011 Risk Management Solutions, Inc.
New objective methodology
pioneered for creating
historical reconstructions
from available observations
Reconstruction at hourly
incremental time-steps
greatly expands amount of
data available for
reconstruction
New footprints better match
peak gust observations for a
large range of wind stations
(including coastal and inland
stations) across multiple
hurricanes
Improved Historical Reconstructions
16
Comparison between Modeled (red line) and Observed (black dots) 3-Second Gust Time Series at Two Stations
for Hurricane Wilma (2005)
© 2011 Risk Management Solutions, Inc.
Two New Vulnerability Regions in Florida
17
e.g., Region 1C
e.g., Region 2C
*Note: Regions 1C and 2C are
the Coastal Region within
Regions 1 and 2, respectively.
Additional claims data from
Wilma highlights
overestimate at coastline
Main driver of change in
vulnerability compared to
previous model version
Coastal vulnerability is lower
than the inland regions
Previous Claims Data $ 9.114 billion
Wilma 2005 (new) $ 1.023 billion
© 2011 Risk Management Solutions, Inc.
External Vulnerability Review
18
Tom Smith, TLSmith Consulting
– Internationally recognized expert on wind
performance of buildings
– Vast field experience examining hurricane
damage post landfall – 15 hurricanes
Quote from Appendix B Review
“Based on my experience and discussion with other
design professionals, the inclusion of the new coastal
region is appropriate because of the greater attention
that is generally given to design and construction near
the coast.”
© 2011 Risk Management Solutions, Inc.
Impact on Losses
19
© 2011 Risk Management Solutions, Inc.
Top five counties
still dominate the
total AAL for the
state in the new
model
Counties that are
mostly “coastal”
drop in rank
Counties “inland”
tend to rise
Coastal Counties Still Dominate
20
County RL801a Rank RL801a AAL RL11 Rank RL11 AALMIAMI-DADE 1 493,077,072 1 464,184,998BROWARD 3 432,043,103 2 432,321,434PALM BEACH 2 489,244,383 3 396,536,073PINELLAS 4 232,986,762 4 203,339,631LEE 5 170,512,425 5 202,861,756HILLSBOROUGH 8 119,529,043 6 165,412,538COLLIER 7 121,577,809 7 139,380,020ORANGE 20 40,985,006 8 130,337,124BREVARD 9 99,623,662 9 128,891,510SARASOTA 6 147,411,823 10 123,254,884POLK 21 37,106,257 11 86,381,677MARTIN 11 78,358,823 12 85,739,451MANATEE 12 77,507,675 13 73,582,779VOLUSIA 16 45,435,222 14 71,526,452PASCO 17 44,526,469 15 64,137,573ST. LUCIE 14 53,485,600 16 61,752,951SEMINOLE 25 19,718,164 17 55,130,018CHARLOTTE 19 42,628,100 18 54,383,397MONROE 10 96,481,373 19 47,842,618INDIAN RIVER 15 45,519,146 20 42,326,489DUVAL 22 32,257,217 21 42,319,564ESCAMBIA 13 69,152,731 22 40,509,986LAKE 28 14,578,532 23 40,456,589
Top 23 of 67 counties by RiskLink 11.0
FHCF Personal Lines 2007 exposure – zero deductible
© 2011 Risk Management Solutions, Inc.
Coastline still
dominates the
overall statewide
loss distribution.
More than 60% of
the loss originates
from within five
miles of the coast
Distribution of Statewide AAL by Distance to Coast
21
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
0 5 10 15 20 25 30 35 40 45 50 55 60
Cu
mu
lati
ve
Pro
po
rtio
n o
f AA
L
Distance to Coast (miles)
Florida Statewide AAL: Residential
RiskLink 8.0.1a
RiskLink 11.0
© 2011 Risk Management Solutions, Inc.
Form S5 shows a 6.5% change in statewide AAL
Table 1, page 39
Statewide Changes by Model Component
22
Geocoding
Hazard
Module
Vulnerability
Module
Financial
Module Total
0.0% -1.5% 6.7% 1.2% 6.5%
© 2011 Risk Management Solutions, Inc.
GeocodingPercent Difference
-55% to -40%
-40% to -20%
-20% to -10%
-10% to 0.0%
0.0% to 10%
10% to 20%
20% to 40%
40% to 100%
100% to 220%
G-1.5.b Percent Change - Geocoding
23
Change in
loss costs is
+/- 5%
© 2011 Risk Management Solutions, Inc.
Financial ModulePercent Difference
-55% to -40%
-40% to -20%
-20% to -10%
-10% to 0.0%
0.0% to 10%
10% to 20%
20% to 40%
40% to 100%
100% to 220%
G-1.5.b Percent Change - Financial Module
24
Effect of
economic
demand
surge
change
results in
+/- 10%
changes in
general
© 2011 Risk Management Solutions, Inc.
Hazard ModulePercent Difference
-55% to -40%
-40% to -20%
-20% to -10%
-10% to 0.0%
0.0% to 10%
10% to 20%
20% to 40%
40% to 100%
100% to 220%
G-1.5.b Percent Change - Hazard
25
Increases
inland
primarily
related to
inland filling
model
change
© 2011 Risk Management Solutions, Inc.
Vulnerability ModulePercent Difference
-55% to -40%
-40% to -20%
-20% to -10%
-10% to 0.0%
0.0% to 10%
10% to 20%
20% to 40%
40% to 100%
100% to 220%
G-1.5.b Percent Change - Vulnerability
26
Reanalysis of
claims data and
creation of new
coastal zone
results in
Increase in
non-coastal
areas
Decrease in
coastal
© 2011 Risk Management Solutions, Inc.
All Changes CombinedPercent Difference
-55% to -40%
-40% to -20%
-20% to -10%
-10% to 0.0%
0.0% to 10%
10% to 20%
20% to 40%
40% to 100%
100% to 220%
G-1.5.b Percent Change - Overall
27
Cumulative
effect of all
modules
combined
© 2011 Risk Management Solutions, Inc.
Absolute Loss Cost Changes vs. Percent Differences
28
A large percent change may not reflect absolute financial
impact
Change in modeled hurricane loss does not directly relate to
change in total premium
County
RiskLink
8.0.1a
($/$1000)
RiskLink
11.0.SP1
($/$1000)
Absolute
Change
($/$1000)
% Change
Orange 0.28 0.95 0.67 237%
Palm Beach 2.71 2.15 -0.56 -21%
Santa Rosa 1.50 0.96 -0.54 -36%
Gross Loss Cost
© 2011 Risk Management Solutions, Inc.
$10 Billion high-res claims
10X more wind observations
Largest numerical wind
modeling project in history
External Peer Reviews
Back-testing against
historical events
Drivers of Model Evolution
29
Data
Computing Power
Validation
This model reflects the continual improvements and evolution of modeling sophistication
© 2011 Risk Management Solutions, Inc.
$-
$5
$10
$15
$20
$25
$30
$35
$40
$45
$50
Gro
ss In
du
str
y L
oss (
$)
in 2
011
Bil
lio
ns
FL-OIR Estimate (1)
PCS Estimate (2)
RMS Estimate (3)
Comparison in Standard S-5
Validation against Industry Losses
30
© 2011 Risk Management Solutions, Inc.
Comparison of modeled and actual losses for residential portfolios affected by
hurricanes that made landfall in Florida
The results are normalized such that the maximum actual loss = $1,000,000 to
protect client confidentiality
Comparison to Portfolio Losses—Florida Residential
31
Incurred Loss
V11 Model Loss
© 2011 Risk Management Solutions, Inc.
Explanation of Changes to Submission
32
© 2011 Risk Management Solutions, Inc.
Deficiencies noted by the commission were addressed and
sent to the commission January 7, 2011.
– Standard G-1.5 – percent difference for stochastic and hazard
module not provided for practical reasons
– Standard G-1.5 – percent difference for geocoding change was
provided
– Reference to Willoughby (2006) updated
– Standard V-1 – changes to description of site inspections
– Form S-6 was included in body of document
– Files related to uncertainty analysis needed to be updated
Deficiencies Submitted
33
© 2011 Risk Management Solutions, Inc.
Notice of Model Change as described in March 14 letter.
– Professional Team verified that corrections were made.
Changes:
1. Financial model optimization to improve runtime resulted in small
output changes
2. Standardized Lloyds Realistic Disaster Scenario (RDS) events with
extremely small rates 10-10 removed from event set.
3. Form S-2 sample size reporting changed to 100,000 years.
Changes result in very small changes to Form A-7,
Form A-9, and Form S-2.
Model Changes (1)
34
© 2011 Risk Management Solutions, Inc.
RevisionForm
A-6
Form
A-7
Form
A-9
Form
S-2
Max Abs
Difference:
Loss Cost
Max Percent
Difference:
PML
Financial Model
optimizationX X X 1E-04 0.00007%
Removal of
standardized RDS
events
X X X X 1E-14 -0.0000002%
Sample size X N/A N/A
Impact of model changes reported March 14, 2011
35
© 2011 Risk Management Solutions, Inc.
Two issues discovered just prior to Professional Team visit were verified with Professional Team
1. Report in Appendix D was missing a field to track the Vulnerability Curve Set used in model runs.
No changes in results
2. Error discovered in internal files used to quantify the Geocoding change in Standard G-1.5.c
Quantification sent in January was based on two different treatments of roads and bridges; now treated the same
No change to model, nor total reported change in G-1.5.c
Minimal impact on the quantification of hazard module change
Resulted in new model version ID of 11.0.SP1
– Changes to various pages that contain version number
Appendix C, Appendix D, footers, model identification sheet, and several other locations where reference to 11.0 was changed to 11.0.SP1.
Model Changes (2)
36
© 2011 Risk Management Solutions, Inc.
Clarifications and Editorial changes during Professional
Team visit were verified onsite.
– Changed “Special position” to “Spatial position” in M-2.3
– Clarify reference to output report in A-5.2
– Changed “et al” punctuation for editorial consistency
– Updated details related to position and tenure of
Mr. Krishnamoorthy, our new Computer signatory following
John Reiter’s retirement
– Revised row format in Form V-2
– Updated screenshots in Appendix C
– Clarified use of new claims data in description of vulnerability
module changes in G-1.5.a
Editorial changes (1)
37
© 2011 Risk Management Solutions, Inc.
Clarifications and Editorial changes during Professional
Team visit were verified onsite.
– Clarified model versioning procedures in C-6.2
– Clarified additive percent different method used to create
Table 1 in G-1.5.c
– Clarified information regarding claims data in V-1.2
– Clarified change to toe nail option in V-2.1
– Form A-8 updated to include additional color bands
– Table 10 in Form M-2 revised variable “vt” to “TS”
– Revised legend in map in Form M-2
– Corresponding updates to signatures in Forms G-1 to G-7
Editorial Changes (2)
38
© 2011 Risk Management Solutions, Inc.
2009 General Standards
39
© 2011 Risk Management Solutions, Inc.
Model version number: RiskLink 11.0.SP1
– Updated from RiskLink 8.0.1a
Scope of the model includes personal and commercial residential risks.
Significant changes made to model as described in overview slides earlier and submission document in G-1.5
– Inland Filling Model change
– Coastal Vulnerability Region introduced
Standard Verified
Standard G-1: Scope of the Computer Model and its Implementation
40
© 2011 Risk Management Solutions, Inc.
Employee/client statistics and biographies updated
Professional credentials updated to reflect changes in the
model team and relevant employment status relating to
current or previous model development.
Forms G-1 to G-7 Expert Certifications updated with each
revision cycle
Standard Verified
Standard G-2: Qualifications of Modeler Personnel and Independent Experts
41
© 2011 Risk Management Solutions, Inc.
ZIP Code data vintage is April 2010–United States Postal
Service.
ZIP Code information is examined by RMS for consistency
and is subject to standardized quality control testing and
checking by experts employed by RMS for that purpose.
If a building location is entered as a ZIP Code, the RMS
model uses wind speeds that are exposure weighted
averages of wind speeds throughout the ZIP Code, based
on population data.
Standard Verified
Standard G-3: Risk Location
42
© 2011 Risk Management Solutions, Inc.
The vulnerability, meteorological, and actuarial model
components are theoretically sound and each has been
thoroughly and independently tested and calibrated.
They have also been tested in an integrated way to ensure
that the relationships between the components are
reasonable.
Standard Verified
Standard G-4: Independence of Model Components
43
© 2011 Risk Management Solutions, Inc.
All documents provided to the Commission throughout the
review process were reviewed and edited by a person or
persons with experience in reviewing technical documents.
Submission document is managed with the same source
control system used on the computer code and development
tools.
Form generation process is documented including flow
charts
Standard Verified
Standard G-5: Editorial Compliance
44
© 2011 Risk Management Solutions, Inc.
2009 Meteorological Standards
45
© 2011 Risk Management Solutions, Inc.
The frequency of the stochastic set used by RMS in both
calibration and validation is consistent with National
Hurricane Center HURDAT data as of June 2009 without
modification.
Standard Verified
Standard M-1: Base Hurricane Storm Set
46
© 2011 Risk Management Solutions, Inc.
Hurricane parameters and characteristics in the RMS model
are modeled and validated using information documented in
accepted literature.
The wind field model directly simulates surface winds as
1-minute mean winds over water.
Standard Verified
Standard M-2: Hurricane Parameters and Characteristics
47
© 2011 Risk Management Solutions, Inc.
Hurricane probability distributions of hurricane parameters
and characteristics are consistent with historical hurricanes
in the Atlantic basin.
Hurricane intensities in the Base Hurricane Storm Set and
model are defined using the maximum one-minute sustained
10-meter wind speed.
Standard Verified
Standard M-3: Hurricane Probabilities
48
© 2011 Risk Management Solutions, Inc.
Wind fields generated by the model are consistent with
observed historical storms which affected Florida.
Surface Roughness database is based on ASTER satellite
imagery data with vintages of 2001-2007.
Effects of vertical variation of winds are accounted for in the
vulnerability curves as different height bands.
Standard Verified
Standard M-4: Hurricane Wind Field Structure
49
© 2011 Risk Management Solutions, Inc.
Over-land weakening methodologies are consistent with
historical records and advances the current state-of-the-
science.
– RMS’ methodology has been published in Monthly Weather Review
Vol. 138, No. 6. (Colette et al. June 2010 )
Transition of winds from water to land is consistent with
state-of-the-science and validated against recent
measurements published in Masters (2004).
Standard Verified
Standard M-5: Landfall and Over-Land Weakening Methodologies
50
© 2011 Risk Management Solutions, Inc.
Wind field is physically consistent with accepted scientific
principles and historical hurricane characteristics
– Magnitude of asymmetry increases as translation speed increases all
other factors held constant
– Mean wind speed decreases with increasing roughness all other
factors held constant
Standard Verified
Standard M-6: Logical Relationships of Hurricane Characteristics
51
© 2011 Risk Management Solutions, Inc.
2009 Vulnerability Standards
5252
© 2011 Risk Management Solutions, Inc.
A. Vulnerability functions are based on well-supported
structural and wind engineering principles and detailed
analyses of historical claims data
– New data associated with Hurricane Wilma
– Updated historical wind field reconstructions
B. Methods used to derive vulnerability functions are
theoretically sound
– A detailed description of the vulnerability update was presented to the
Professional Team, including a review of the data utilized in the
update, and how the data was processed and used in the derivation of
the updated vulnerability curves
Standard V-1: Derivation of Vulnerability Functions (1 / 3)
5353
© 2011 Risk Management Solutions, Inc.
C. Primary classification variables used in model account for height, construction type and construction characteristics– Over 600 unique functions per region of which 256 unique residential
building functions in FL described in Table 16
– For commercial residential, vulnerability functions vary with height
– The single family residential vulnerability curves feature
2 height bands (1 story versus 2+ stories)
5 different floor area bands
D. Changes in building codes/construction practices are modeled
through regional and age band differences
– Three year bands
– New claims data analysis resulted in introduction of coastal
vulnerability regions 0.5 miles from coast as described in overview
Standard V-1: Derivation of Vulnerability Functions (2 / 3)
5454
© 2011 Risk Management Solutions, Inc.
E. Separate vulnerability functions
– For structures and mobile homes,
– Appurtenant structures use same function as main structure, but can be input separately
– Separate functions for contents and time element losses
F. Minimum wind speed generates damage
– 50 mph peak gust = ~42 mph one minute sustained
G. Wind vulnerability functions include damage due to wind speed and pressure, water infiltration, and missile impact. Wind vulnerability functions exclude damage due to flooding, storm surge and wave action.
Standard Verified
Standard V-1: Derivation of Vulnerability Functions (3 / 3)
5555
© 2011 Risk Management Solutions, Inc.
A. RMS uses secondary modifier functions to reflect specific attribute information referenced in OIR “Informational Memorandum 02-0470M” and can be used to reflect mitigation measures
– RiskLink 11.0.SP1 reorganized the modifier options to improve the alignment of options with data collected using the Uniform Mitigation Inspection Form (OIR-B1-1802)
– Changes:
Retired two modifiers that were little used or minimal impact
Combined eight modifiers into four modifiers to simplify application
Added one new modifier: Flashing and Coping for flat roofs
B. The application of modifier options are reasonable when applied individually and in combination as shown in Form V-2
Standard Verified
Standard V-2: Mitigation Measures
5656
© 2011 Risk Management Solutions, Inc.
2009 Actuarial Standards
57
© 2011 Risk Management Solutions, Inc.
Modeled loss costs and probable maximum loss levels
reflect all damages from storms that reach hurricane
strength and produce minimum damaging wind speeds or
greater on land in Florida.
Model treats damage from wind and storm surge/flood
separately. This submission excludes surge losses
completely.
Standard Verified
Standard A-1: Modeled Loss Costs and Probable Maximum Loss Levels
58
© 2011 Risk Management Solutions, Inc.
Adjustments, edits, inclusions, or deletions to insurance
company input data used are based upon accepted
actuarial, underwriting, and statistical procedures and are
documented in writing.
For loss cost and probable maximum loss estimates derived
from or validated with historical insured hurricane losses, the
assumptions in the derivations concerning (1) construction
characteristics, (2) policy provisions, (3) claim payment
practices, and (4) relevant underwriting practices underlying
those losses, as well as any actuarial modifications, are
appropriate.
Standard Verified
Standard A-2: Underwriting Assumptions
59
© 2011 Risk Management Solutions, Inc.
Neither loss cost nor probable maximum loss level
projections produced by hurricane loss projection models
include expenses, risk load, investment income, premium
reserves, taxes, assessments, or profit margin.
Neither loss cost nor probable maximum loss level
projections make a prospective provision for economic
inflation.
RiskLink is capable of producing loss cost projections and
probable maximum loss levels at variety of spatial
resolutions down to geocode (latitude-longitude) resolution
Standard Verified
Standard A-3: Loss Cost Projections and Probable Maximum Loss Levels
60
© 2011 Risk Management Solutions, Inc.
The methods, data, and assumptions used in the estimation
of demand surge are actuarially sound.
Demand surge is included in the model’s calculation of loss
costs using relevant data.
Standard Verified
Standard A-4: Demand Surge
61
© 2011 Risk Management Solutions, Inc.
Input data to the RMS Hurricane model is explicitly provided
by the user for each particular analysis. The model
assumes that inputs provided by the user reflect actual
exposures and their associated characteristics.
The model output report in Appendix D captures all input
data and model settings.
Standard Verified
Standard A-5: User Inputs
62
© 2011 Risk Management Solutions, Inc.
Loss costs exhibit logical relations to risk.
Loss costs change with changes in risk in logical ways.
– Quality of construction type, materials and workmanship
– Fixtures or construction techniques designed for hazard (damage) mitigation
– Building codes and enforcement
– Deductibles
– Coverages
Standard Verified
Standard A-6: Logical Relationship to Risk
63
© 2011 Risk Management Solutions, Inc.
The methods and distributions used to develop deductible
and limit effects are actuarially sound and in compliance with
Florida Statute.
Relationships among loss costs with different deductibles
are reasonable.
Standard Verified
Standard A-7: Deductibles and Policy Limits
64
© 2011 Risk Management Solutions, Inc.
The methods used in the development of contents damage
are actuarially sound.
Modeled structure and contents damage relationships are
reasonable, based on the historical damage.
Standard Verified
Standard A-8: Contents
65
© 2011 Risk Management Solutions, Inc.
Standard A-9: Additional Living Expense (ALE)
The methods used in the development of ALE loss costs are actuarially sound.
ALE loss cost derivations consider the estimated time required to repair or replace the property and consider damage to the infrastructure.
The relationship between the modeled structure and ALE loss costs is reasonable and is based on the relationship between historical structure and ALE losses.
Standard Verified
66
© 2011 Risk Management Solutions, Inc.
Standard A-10: Output Ranges
Output ranges show logical relationships
As reported in G1.5c, statewide change in AAL are approximately
6.5%
All other factors held equal, output ranges reflect
– Lower loss costs for masonry than wood frame
– Lower loss costs for personal residential than mobile home
– Lower loss costs for inland counties than coastal counties
– Lower loss costs for Northern counties than southern counties
Form A6, Form A7, Form A8 submitted
Sample Com Res output range reports provided.
Standard Verified
67
© 2011 Risk Management Solutions, Inc. 68
Standard A-11: Probable Maximum Loss
The methods, data, and assumptions used in the estimation
of probable maximum loss levels are actuarially sound.
Form A-9 shows specified Probable Maximum Loss Levels
and associated uncertainty measures.
Standard Verified
© 2011 Risk Management Solutions, Inc.
2009 Statistical Standards
69
© 2011 Risk Management Solutions, Inc.
RMS uses empirical methods in model development and
implementation to match stochastic storm generation to
historical data. These methods are supported by those
described in currently accepted scientific literature
The chosen distributions have been shown to have
reasonable agreement with the historical data
Wind speeds have been extensively validated against
available data
Uncertainty analysis provided
All required forms provided
Standard Verified
Standard S-1: Modeled Results and Goodness-of-Fit
70
© 2011 Risk Management Solutions, Inc.
RMS has assessed the sensitivity of temporal and spatial
outputs with respect to the simultaneous variation of input
variables using currently accepted scientific and statistical
methods
The most sensitive aspects of the model are the intensity
and size of the hurricane at landfall
Form S-6 has been provided
Standard Verified
Standard S-2: Sensitivity Analysis for Modeled Output
71
© 2011 Risk Management Solutions, Inc.
RMS has performed an uncertainty analysis on the temporal
and spatial outputs with respect to the simultaneous
variation of input variables using currently accepted
scientific and statistical methods
The major contributors to the uncertainty in model outputs
are the intensity and size of the hurricane at landfall
Form S-6 has been provided
Standard Verified
Standard S-3: Uncertainty Analysis for Modeled
Output
72
© 2011 Risk Management Solutions, Inc.
The standard error of each output range at the county level
of aggregation is less than 2.5% of the loss cost estimate
Standard Verified
Standard S-4: County Level Aggregation
73
© 2011 Risk Management Solutions, Inc.
The RMS model is able to reliably and without significant
bias reproduce incurred losses on a large body of past
hurricanes, both for personal residential and mobile homes
Form S-4 has been provided
Standard Verified
Standard S-5: Replication of Known Hurricane Losses
74
© 2011 Risk Management Solutions, Inc.
The difference between historical and modeled annual
average statewide loss costs is statistically reasonable,
given the body of data, by established statistical
expectations and norms.
Form S-5 has been provided
Standard Verified
Standard S-6: Comparison of Projected Hurricane
Loss Costs
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© 2011 Risk Management Solutions, Inc.
2009 Computer Standards
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© 2011 Risk Management Solutions, Inc.
Computer Standards document binder
– On-line, in central location
– Folder hierarchy indexes material by standard
– Covers all software relevant to submission
– Includes documentation external to source code
Binder created for RiskLink 11.0.SP1 to reflect:
– Model updates (Standard G-1, Disclosure 5)
Vulnerability, Hazard, Post Loss Amplification model.
Platform changes (Performance, 64 bit support)
– Upgrades in documentation for version RiskLink 11.0.SP1
Standard Verified
Standard C-1: Documentation
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Requirements covered in various documents
– RiskLink System Administration and User Guide
– Coding standards
– Market requirements documents
– Functional specifications / Technical specifications
– Project management documents
– Team foundation documents/ Sharepoint documents
– Information Technology Security documents
– Quality Assurance test plans
– Training program documents
Model updates for RiskLink 11.0.SP1 reflected in requirements documents where appropriate
Standard Verified
Standard C-2: Requirements
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Control flow diagrams– Illustrate key processes, branches, and loops within software
Data flow diagrams– Illustrate data-dependency relationships between software
components
Interface specifications– Document software module inputs and outputs
Data schema documentation– Describes all data files / databases
Model updates for RiskLink 11.0.SP1 reflected in these
documents where appropriate; primarily control flow and
data flow
Standard Verified
Standard C-3: Model Architecture and Component Design
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© 2011 Risk Management Solutions, Inc.
Coding guidelines contain standards for software and data
development
Data procedures documented
Flow diagrams can be traced to code level
Count of lines of code and comment lines maintained for all components
Comments within code allow components to be comprehensible
Equations, formulas, and source code terms for G-1.5 changes
Hardware, software, languages
Model updates for RiskLink 11.0.SP1 reflected in these
documents where appropriate
Standard Verified
Standard C-4: Implementation
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© 2011 Risk Management Solutions, Inc.
Procedures for general testing– Design and prototype of model modifications/additions
– Written specifications describe purpose, algorithm, and testing plans; reviewed by modelers, software engineers, Product managers, Client Development and QA
– Independent execution of test plans by RMS Software and Engineering Quality Assurance departments
– Code inspections, reviews, and walkthroughs to verify code correctness
– Run time errors caught by logical assertions, exception handling mechanisms, and trace statements in code
Procedures for component testing– IBM/Rational Enterprise/Automation tools used for analyzing and testing all
components
– Software debuggers used to verify execution paths and calculation results
– Custom unit tests used to check components using range of input values
– Aggregation tests performed by running the product as complete package to check all the components and data files accessed by model
– Performance tests check for execution time and memory use problems
Standard C-5: Verification (1/2)
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Procedures for data testing
– Software tools used
Database packages
Mapping software
Rational Robot regression tests
Custom tools (e.g., in Excel, Access, C++, SQL)
– Aggregation tests check use of data files, and to check repeatability of results with same input
Model verification updates for RiskLink 11.0.SP1 reflected in these documents where appropriate
Standard Verified
Standard C-5: Verification (2/2)
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Comprehensive procedures for full life cycle
– Summarized by High-Level Description of Model-Revision Policy
– Elaborated upon in Detailed Description of Model-Revision Policy
– RMS Development Process documents all key life cycle steps along
several dimensions:
Description
Ownership
Inputs
Deliverables
Process flow
Tools and templates
Best practices
Standard C-6: Model Maintenance and Revision (1/2)
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Software and processes used to track errors, revisions
Unique model version used for each release of model
– Internal Component convention
[MajorRevision].[MinorRevision].[BuildNumber].[PatchRevision]
– External naming convention
RiskLink [MajorRevision].[MinorRevision].SP[PatchRevision]
Standard Verified
Standard C-6: Model Maintenance and Revision (2/2)
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© 2011 Risk Management Solutions, Inc.
RMS has documented and implemented security
procedures for access to code, data, and documentation
– Security requirements documented and enforced by RMS Legal
and Information Technology Departments
– Company personnel are trained in security requirements and
procedures as part of the company’s significantly revised and
expanded training process
Standard Verified
Standard C-7: Security
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