RMS North Atlantic Hurricane Model RiskLink 11.0

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


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


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


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


Inland Filling

7


“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


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


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)


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.


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.”


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


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


Vulnerability Updates

15


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)


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


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.”


Impact on Losses

19


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


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


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%


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%


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


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


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


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


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


$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


$-

$5

$10

$15

$20

$25

$30

$35

$40

$45

$50

Gro

ss In

du

str

y L

oss (

$)

in 2

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Bil

lio

ns

FL-OIR Estimate (1)

PCS Estimate (2)

RMS Estimate (3)

Comparison in Standard S-5

Validation against Industry Losses

30


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


Explanation of Changes to Submission

32


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


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


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


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


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


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


2009 General Standards

39


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


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


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


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


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


2009 Meteorological Standards

45


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


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


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


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


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


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


2009 Vulnerability Standards

5252


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


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


5454


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


5555


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


2009 Actuarial Standards

57


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


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


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


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


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


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


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


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


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


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


2009 Statistical Standards

69


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


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


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


Standard Verified

Standard S-3: Uncertainty Analysis for Modeled

Output

72


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


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


Standard Verified

Standard S-5: Replication of Known Hurricane Losses

74


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.


Standard Verified

Standard S-6: Comparison of Projected Hurricane

Loss Costs

75


2009 Computer Standards

76


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

77

../../../../../../Professional Team and Commission Meetings/On-Site Audit/3 Standards/Computer/C-1 Documentation




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

78

../../../../../../Professional Team and Commission Meetings/On-Site Audit/3 Standards/Computer/C-2 Requirements




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

79

../../../../../../Professional Team and Commission Meetings/On-Site Audit/3 Standards/Computer/C-3 Model Architecture and Component Design




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

80

../../../../../../Professional Team and Commission Meetings/On-Site Audit/3 Standards/Computer/C-4 Implementation




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

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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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RMS North Atlantic Hurricane Model RiskLink 11.0

Documents

Transcript of RMS North Atlantic Hurricane Model RiskLink 11.0