Lloyd`s realistic disaster scenarios
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Transcript Lloyd`s realistic disaster scenarios
Lloyd’s
Realistic Disaster Scenarios
14th October 2004
Background to Lloyd’s
In existence since 1688
World's leading insurance market
66 syndicates
Over 160 brokers
Capacity of approximately £15.0 billion
Profile of the Lloyd’s Market
Lloyd’s
Franchisor
CLIENTS
Reinsureds
Commercial
MEMBERS
168
Lloyd’s
Brokers
66 Syndicates
£15.0bn Capacity
AM Best: A
AS&P: A
Personal
BUSINESS FLOW
Source: Lloyd’s
53
Corporate
Groups
45 Managing Agents
Service
Companies
4
Members’
Agents
2,048
Individuals
Members
(Unlimited
liability)
637
Conversions
(Limited
liability)
CAPITAL PROVISION
Profile of Lloyd’s Capacity & Managing Agents
Ca pa c i t y M ov e me nt
Market Capacit y
£ Bn
16
14
12
10
8
6
4
2
0
No. of syndicat es
No. of Managing Agent
200
150
164
66
100
50
68
45
0
1997
1998
1999
2000
2001
2002
2003
2004
Lloyd’s Realistic Disaster Scenarios
(RDSs)
Lloyd’s RDSs were introduced in 1995
Requiring syndicates to carry out disaster planning
Based on a range of hypothetical scenarios
Scenarios mainly based on historical disasters
“Failure of North Sea Complex” – from Piper Alpha
“Marine Collision” – from Exxon Valdez
“Japanese Earthquake” – from 1923 Great Kanto Event
RDS Overhaul Project
Two year RDS Overhaul Project
Improve consistency of risk assessment
Raise Loss Modelling standards in the market
Collaborative Process
Market Experts Group
Lloyd’s Market Association – Marine RDS
AIR, EQECAT and RMS
Florida Windstorm
California Earthquake
Overhaul to be Completed in April 2005
Will take account of feedback received in 2004
Why Overhaul the RDSs?
To provide a more reliable and accurate measurement of risk,
based on a more comprehensive and consistent approach
To measure the market’s and syndicates’ exposures to a series of
major catastrophes
RDS assumptions and practices varied widely
Significant variations observed in “Aggregate” to “Gross Loss”
relationships
Wide variations in methodologies
To provide a better understanding of Lloyd’s aggregate risk profile
For catastrophes
As an input to capital setting and allocation decisions
As an input in managing Central Fund exposures
RDS Guidance and Instruction
Issued in April 2004
Replaces previous “Regulatory Bulletins”
with a comprehensive guide to the
assessment of catastrophe exposures
REALISTIC DISASTER SCENARIOS APRIL 2004
Key sections include
Definitions
Calculation Principles
Recommended Best Practice
“Event Subset” Submissions
Scenarios and Events
Available on Risk Management Website
www.lloyds.com/riskmanagement
Guidance and Instructions
Scenarios and Events
SINGLE RISK SCENARIOS
AGGREGATING SCENARIOS
1
USA Windstorm
11
Second Event
2
Marine Event
12
Florida Windstorm
3
North Sea – Loss of Major Complex
13
California Earthquake
4
Aviation Collision
14
New Madrid Earthquake
5
Major Risk Loss
15
European Windstorm
6
Satellite Risks
16
Japanese Earthquake
7
Liability Risks
17
Terrorism
8
Political Risks
9
Alternative RDS: A
10
Alternative RDS: B
Marine RDS
Syndicates must return two scenarios
Collision in Prince William sound
Major Cruise Vessel Incident
Increased guidance for both scenarios
Specification of losses to the International Group of P&I Associations
Reinsurance Programme.
Marine collision in Prince William Sound
Cruise Vessel
Tanker Owner
Protection and Indemnity
Protection and Indemnity
US$ 2,050m
US$ 2,050m
Layer 4
Layer 4
US$ 1,550m
US$ 1,550m
Layer 3
Oil Pollution
US$ 1,050m
Oil Pollution
Layer 2
Layer 2
US$ 1,050m
Layer 2
Layer 2
POOL RETENTION
Owned Entries
Layer 1
US$ 187.5m
US$ 50m
Layer 1
POOL RETENTION
Owned Entries
Coinsurance 25%
Layer 1
Coinsurance 25%
Layer 1
Coinsurance 25%
US$ 437.5m
Coinsurance 25%
US$ 600m
US$ 550m
US$ 550m
US$ 50m
Layer 3
California Earthquake
EXPOSURE DISTRIBUTION
EVENT FOOTPRINTS
Catastrophe Loss Modelling Software –
Florida Windstorm & California Earthquake
Three agencies - AIR, EQECAT & RMS
Working with the three catastrophe modelling agencies has
enabled us to:
Specify new events tightly, by industry loss level
US$70bn and $54bn respectively
Specify 2 events of similar magnitude
Based on Commercial (including Industrial) and Residential losses
Better coverage of risk (e.g. LA and San Francisco)
Derive Average Damage Factors
Feasible events cannot destroy all properties
Florida Windstorm and
California Earthquake
County level “Footprints”
County level damage factors
Derived from discussions with AIR, EQECAT and RMS
Prompt for additional lines of business to include
“Aggregate” to be based on county exposures in “Footprint”
Marine, Specie/Fine Art, Personal Accident, Aviation, Liability
Exclusion of classes viewed as “impossible” to model
Contingent Business Interruption
Aviation Hull in Earthquake
RMS “Roll-up” exercise
Pilot study with five managing agents
Combining Event Loss Table output
To validate choice of new RDS events
To assess feasibility of combining syndicate results
Analysis split by broad business categories
Direct & Facultative
Treaty
Binder
RMS “Roll-up” exercise
– California EQ
D&F
Lloyd's Sample Loss
D&F Benchmark Events
RMS Industry Loss
RMS “Roll-up” exercise
TREATY
Lloyd's Sample Loss
Treaty Benchmark Events
RMS Industry Loss
RMS “Roll-up” exercise
BINDERS
Lloyd's Sample Loss
Binder Benchmark Events
RMS Industry Loss
Terrorism RDS
Terrorism RDS
2-tonne conventional bomb attack on Empire State Building
Damage zones and levels specified in scenario
TRIA and non-TRIA events
Specification of deaths, injuries and BI
Fire-following, Number of Events and CBRN Guidance
Focus on data resolution
Address-level best for urban accumulations
Guidance for proportions in 10001, 10016 and 10018
Terrorism RDS
Data Resolution
Source: Munich Re. Topics Geo 2003
RDS Results
Playback
Visits
Each Managing Agent visited by two or more Risk
Executives
General questions asked concerning:
Data capture and resolution of data
Identifying relevant policies
Loss calculation and expected values
The return process & quality assurance
Modelling methods
Review of one RDS scenario from start to finish
RDS Results
Playback
Packs
Every syndicate receives a pack prepared solely for their own use.
Contains syndicate specific analysis on:
Aggregate, Gross, Net and Final Net losses
Losses in relation to capacity and hence Franchise Performance
Guidelines
Ranking within the market
Includes analysis on modelling types at both market and syndicate
level for each scenario.
Graphical representation of Losses, Average Damage Factors
(ADFs) and Ranking.
RDS Results
Modelling Type Analysis
Modelling type - Market
Licensed Softw are(AIR/EQECAT/RMS)
Modelled Internally
Maximum Line
Market Share
Premium Derived
M arine Co llisio n in P rince William So und
Sunk/Damaged Cruise Liner
M ajo r Risk Lo ss
Seco nd Event
USA Windsto rm
A lternative RDS B
No rth Sea Co mplex
A lternative RDS A
Specific Euro pean Windsto rm
Lo s A ngeles
San Francisco
Specific New M adrid Earthquake
Specific Japanese Earthquake
M iami
Tampa B ay
Liability
No n-TRIA Event
TRIA Event
0%
10%
20%
30%
40%
50%
60%
70%
Percentage of Gross Loss by Modelling type
80%
90%
100%
Four-Stormed is Forearmed
14 October 2004
How Hurricanes are Formed
Thunderstorms drift over warm ocean
waters.
Warm air from the storm and ocean
surface combine and begin rising,
creating low pressure.
Trade winds blowing in opposing
directions cause the storm to start
spinning.
The rising warm air causes pressure to
decrease at higher altitudes.
Air rises faster and faster to fill this low
pressure, in turn drawing more warm
air off the sea and sucking cooler, drier
air downwards.
As the storm moves over the ocean it
picks up more warm, moist air. Wind
speeds start to increase as more air is
sucked into the low pressure centre.
It can take hours or several days for a
depression to grow into a fully-formed
hurricane.
Lloyd’s 2004 Realistic Disaster Scenarios
Distribution of Florida Property Values
Hurricane Charley – The facts
Hurricane Charley made landfall at Sanibel Island,
Florida, late on the afternoon of 13 August 2004.
Maximum sustained winds were near 145 mph after
upgrading to a Category 4 storm, causing severe
damage and flooding in coastal areas.
Hurricane Charley had been expected to make landfall
near Tampa, 120 miles to the north, but shifted course
at midday and brushed low-lying islands.
Charley was responsible for the death of 27 people in
Florida.
RDS 2004 Pinellas Hurricane Event Footprint
Estimation of track of
Hurricane Charley
Hurricane Frances – The facts
Hurricane Frances made landfall at Sewall’s Point in
Martin County, Florida, at 05:00 GMT on Sunday 5th
September.
Maximum sustained winds were near 105 mph and
Frances dropped more than 33cm of rain along
Florida’s east-central coast.
Insured losses will be limited because much of the
damage has been caused by flooding, which is
covered by the National Flood Insurance Program.
Frances was responsible for the death of 23 people in
Florida.
RDS 2004
Miami-Dade Hurricane Event Footprint
Estimation of track of
Hurricane Frances
Tracks of Hurricane Charley & Hurricane Frances
Source: Guy
Carp.com.
Cat-i Reports
Hurricane Frances
Update- Report 10,
September 7, 2004
Hurricane Ivan – The facts
Hurricane Ivan made landfall just west of Gulf Shores in
Baldwin County, Alabama at 07:00 GMT on Thursday 16th
September.
Maximum sustained winds were near 130 mph when it
came ashore and subsequently moved inland and
weakened.
Ivan was responsible for the death of at least 50 people in
the United States in addition to over 70 people in the
Caribbean.
Tracks of Hurricanes Charley, Frances & Ivan
Source: Guy
Carp.com.
Cat-i Reports
Hurricane Ivan
Update- Report 13,
September 17, 2004
Hurricane Jeanne – The facts
Hurricane Jeanne made landfall near Hutchinson Island
just east of Stuart in Martin County, Florida at 04:00 GMT
on Sunday 26th September.
Maximum sustained winds were near 120 mph (Cat 3) when
it came ashore and subsequently moved inland and
weakened.
Jeanne was responsible for the death of at least 3,000
people in Haiti mainly due to flooding and 8 people in
Florida.
Track of Hurricane Jeanne
Source: Guy
Carp.com.
Cat-i Reports
Hurricane Jeanne
Update- Report 7,
September 27, 2004
Tracks of the Four Hurricanes
Source: Guy
Carp.com.
Cat-i Reports
Hurricane Jeanne
Update- Report 7,
September 27, 2004
Industry Loss Estimates
RMS
EQECAT
AIR
Charley
USD 6-8bn
USD 5-10bn
USD 6-10bn
Frances
USD 3-6bn
USD 2-5bn
USD 5.6-8.7bn
Ivan
USD 3-6bn
USD 4-10bn
USD 3-6bn
Jeanne
USD 4-8bn
USD 6-14bn
USD 5-9bn