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How DFA Can Help the Property/Casualty Industry, Part 4
Hurricanes Katrina, Rita, Wilma...
Catastrophes: Models and Reserving
Risk Measures
Reinsurer Results:
Catastrophe and Strengthening
Hurricanes: 2003 and 2004 Results, Clustering and TransitioninG
Brushfire and Fire Following Exposures
Brushfire
Fire Following Earthquake
Observations for Risk Management
Tsunami Exposure Worldwide and U.S.
Wind and Hail: Relative Hazard Levels
Cat Modeling Class
Introduction to Reinsurance
Holborn Technical Seminar
Catastrophe, Injury, and Insurance
Review of Myers & Read ARIA Paper
A Perfectly Ordinary Tuesday Morning
This is Not Your Father’s Cat Model
Global Warming and Increased Catastrophes?
Reinsurer Risk Loads from Marginal Surplus Requirements, PCAS LXXVII
Reinsurance Markets
Risk Transfer Assessment
Introduction to Asset Returns and Risks
CAS Call Paper Panel
Ceded Reinsurance Issues in DFA
Catastrophe Reinsurance Simulation Game
Reinsurance by any other name
Clash Pricing
ALLOCATION OF SURPLUS FOR A MULTI-LINE INSURER
Optimization to Improve Business Performance

 

 
May 12-13, 2005
Dan Zitelli
2005 Client Technical Seminar

Observations for Risk Management

What Do We Need To Know To Model Fire?

Ignition Rate

Fire ignitions are typically caused by the overturning and breakage of building contents (i.e., ignitions due to open flame or chemical reactions), structural deflections resulting in damage and short-circuiting of electrical wiring, and ruptured gas lines. As such, there is a generally positive correlation between the number of ignitions and earthquake intensity.

The probability of an ignition per million square feet of commercial high rise is not the same as the probability of an ignition per million square feet of single family residential structures. Fire codes in commercial buildings are more stringent, sprinkler systems further reduce the risk, building materials are less flammable, etc.

Once the number of ignitions is generated, they are stochastically placed throughout the ZIP Code / Modeled area.

Fire spread

Once a fire has been ignited, the growth of this fire must be modeled.

The fire spread rate is a function of building density, building spacing, building plan area, the percentage of buildings that are fire resistant, and wind speed. Models yields a burn area as a function of time. Also depends on smallest geographic area model looks at. (i.e., Zip code vs. VRG)

Fire spread parameters are estimated for four different urban types: town/suburban, urban, commercial, dense commercial.

The spread rate is, in part a function of local wind speed, based on data of annual mean wind speed and variability.

This could lead to an underestimation of the tail of the Fire Following EP curve. Since in this one model, no direct Santa Ana input is present; peaks smoother over averages.

Fire Suppression

Finally, fire response and suppression is simulated. Most models incorporate distributions of fire discovery and report times that are based on historical data.

Report time generally increases as intensity increases, as a result of, among other things, interruptions in telephone service.

Each fire is probabilistically assigned a discovery and report time and an engine is assigned to the fire.

The time it takes for local authorities to respond is estimated as a function of the fire discovery and reporting time and fire engine speed. More intense earthquakes are more likely to render roads impassable, break water mains, or result in other events that affect suppression capability.

Fire Damage Estimation

Fire losses are computed for each fire by taking the burn area and multiplying by an estimate of construction cost per square foot of the affected construction class.

Total losses for each fire class in a ZIP Code are capped by the maximum exposure in that ZIP Code for that fire class.

RMS Industry Loss Curves
EQ Shake Only And EQ Shake and Fire Following Combined
California, All Lines of Business - No Demand Surge
Gross Occurrence Loss Figures

Critical Prob.
Return Period
Shake and Fire
Shake Only
% Difference
10.00%
10
$2,524,162,949
$2,422,136,107
4%
4.00%
25
8,393,428,721
7,336,396,008
14%
2.00%
50
14,552,105,524
12,228,107,476
19%
1.00%
100
21,659,239,895
17,760,814,489
22%
0.40%
250
32,387,467,829
25,886,614,205
25%
0.20%
500
41,141,109,523
32,277,032,623
27%
0.10%
1,000
49,941,440,520
38,327,605,263
30%
0.01%
10,000
77,925,226,910
56,960,351,104
37%
Average Annual Loss
$1,216,873,535
$1,054,679,430
15%
Standard Deviation
4,523,737,653
3,665,905,471
23%
Pure Premium Fire Differential
$162,194,105
   
As % of Shake Loss
15%
   

RMS Industry Loss Curves
EQ Shake Only And EQ Shake and Fire Following Combined
All US, All Lines of Business - No Demand Surge
Gross Occurrence Loss Figures

Critical Prob.
Return Period
Shake and Fire
Shake Only
% Difference
10.00%
10
$4,053,431,984
$3,747,739,088
8%
4.00%
25
11,046,523,287
9,466,958,935
17%
2.00%
50
18,164,251,611
15,171,797,581
20%
1.00%
100
27,484,510,919
22,323,228,645
23%
0.40%
250
43,535,975,556
35,064,605,755
24%
0.20%
500
59,197,064,588
48,073,044,639
23%
0.10%
1,000
79,011,932,016
67,813,207,519
17%
0.01%
10,000
138,325,250,820
121,727,085,426
14%
Pure Premium
$1,838,982,887
$1,608,939,863
14%
Standard Deviation
6,503,531,425
5,474,202,264
19%
Pure Premium Fire Differential
$230,043,024  
As % of Shake Loss
14%  

Conclusion

Fire Following is a real exposure, if difficult to quantify.

The 2003 Brushfires were not fire following losses, but the magnitude of that season's loss illustrated the potential for loss in an earthquake during a Santa Ana season.