Post on 23-Aug-2018
2011 CAS Spring Meeting
Systemic Risks for P&C Insurers
Dr. Shaun Wang, FCAS, MAAA Chair, Risk Lighthouse LLC
Professor, Georgia State University
Impacts of Systemic Risks
Benchmarks and Differences
A Perfect Storm in the Making?
Contents
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Defining Systemic Risks
• “Systemic risks” has become center of attention for financial regulators
• Geneva Association April 2011 Report ---“Considerations for Identifying Systemically Important Financial Institutions in Insurance”
• We focus on the U.S. P&C insurance, and its players (from large national/global insurers to small to mid-sized regional insurers)
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Identify Systemic Events
• 1983-87 Liability crisis created a multi-year bust-and-boom in the casualty insurance sector
• 1992 Hurricane Andrew changed the way companies manage catastrophe accumulation
• 9/11/2001 not only changed airport security check, but accelerated the hardening of the P&C insurance market cycle
• AIG and Bond Insurers were at the center of 2008-2009 crisis, but the P&C industry was not hugely impacted (thanks to the Fed)
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__________________________________________________________________________________________________________________
U.S. Property-Casualty: Underwriting Cycle Modeling and Risk
Benchmarks Shaun S. Wang, PhD, FCAS
John A. Major, ASA Charles H. Pan
Jessica W.K. Leong, FCAS, FIAA
Data Analysis of Systemic Risks • In 2010, Risk Lighthouse and Guy Carpenter
undertook a joint research project • Thousands of hours (5 months, 7+ persons) • Compiled and cleaned extensive insurance
company data filings • Cleaned data serve as basis for studying
systemic risks and benchmark parameters
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Data Cleaning • Data Sources: SNL, NAIC, and A.M. Best • Unit: insurance company group & sub-groups • AY 1980 to 2009 Gross and Net Premiums; Paid,
Case Incurred and INBR loss triangles • Diagnosis of Inconsistencies:
1) Restatement of historical data 2) Mergers and Acquisitions 3) Inter-company reinsurance
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Segments of Company Groups
Segment Number of Company Groups
Large National 23
Super Regional 30
Small Regional 474
Specialty Writer 55
Reinsurer 19
Other 113
Homeowner 16
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Total Written Premium to Private Sector GDP Ratio (1967-2009)
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40%
60%
80%
100%
120%
140%
160%
1973
1975
1977
1979
1981
1983
1985
1987
1989
1991
1993
1995
1997
1999
2001
2003
2005
2007
2009
Reported Loss Ratio for General Liability by Accident Year and Development Year
1st year
2nd year
3rd year
4th year
5th year
6th year
7th year
8th year
9th year
10th year
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0.000%
0.100%
0.200%
0.300%
0.400%
0.500%
0.600%
-30%
-20%
-10%
0%
10%
20%
30%
40%
50%
60%
70%
1977
19
78
1979
19
80
1981
19
82
1983
19
84
1985
19
86
1987
19
88
1989
19
90
1991
19
92
1993
19
94
1995
19
96
1997
19
98
1999
20
00
2001
20
02
2003
20
04
2005
20
06
2007
20
08
2009
General Liability (Other Liability + Product Liability): Loss Ratio Development versus NWP/PSGDP
LR Dev NPW/PSGDP
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Movements of Total Premium Share
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Regime-shifting model for the Total Premium Share
• Up-regime
.
• Down-regime
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Down-regime
modeled as
Hockey-stick
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Example Simulation Paths of Total Premium Share
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Impacts of Systemic Risks
Benchmarks and Differences
A Perfect Storm in the Making?
Contents
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CV of Net Loss Ratios (AY 1987-2004) by Segment and LOB
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“Stdev of Net Ultimate Loss Ratio ” vs. “Premium” for Other Liability
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• Unlike large & complex global (re)insurers, small- to mid-sized regional insurers do not pose much systemic risk to the insurance industry, neither to the financial system They deserve favorable treatment by
regulators and rating agencies All insurers (large and small) can be impacted
by systemic events (increased catastrophes and economic crisis)
Findings of Our Data Analyses
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Impacts of Systemic Risks
Benchmarks and Differences
A Perfect Storm in the Making?
Contents
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After a prolonged soft market (1987-2000), industry didn’t have cushion for major loss shocks
Catastrophe event (9/11/2001) 2001-2003 bear stock market caused investment
losses Waves of reserve increases prompted S&P report
19-Nov-2003 Insurance Actuaries – A Crisis of Credibility: “Actuaries are signing off on reserves that turn out to be wildly inaccurate”
The 2001-2003 Perfect Storm
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(100)
(80)
(60)
(40)
(20)
0
20
40
2001 Y
2002 Y
2003 Y
2004 Y
2005 Y
2006 Y
2007 Y
2008 Y
2009 Y
2010 Y
Billions
P&C Insurance Industry Investment Gains (Losses) Realized Capital Gains Unrealized Capital Gains
• The 2004 and 2005 major catastrophes did not turn the P&C market cycle
• The industry enjoyed strong hard market during 2003-2005 and had redundant reserves
• Investment income/gain on the rise
Katrina didn’t turn the P&C market
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• The recent market softening slide has lasted five years (2005-2010)
• The 2008-2009 Financial Crisis brought heavy investment losses for P&C insurers, but it did not turn the market. Or should it have?
• The 3/11/2011 Japan earthquake has not turned the market yet
• So what will? • A perfect storm seems to gather clouds
How stubborn can a soft market be?
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A Perfect Storm in the Making?
• A mega earthquake in the U.S. may trigger economic collapse and market meltdown
• Unlike the 2008-2009 crisis, this time federal bailout is no longer available
• Insurers may suffer asset losses due to defaults of municipal bond and corporate bonds
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Muni Bond Exposures As of 9/30/2010
SNL top-tier entity Total
municipal bonds* ($M)
Surplus ($M) Invested assets ($M)
Total municipal
bonds/ surplus (%)
Total municipal
bonds/ invested
assets (%)
American International Group 45,520 28,876 84,219 157.6 54.0
Travelers Cos (TRV) 40,253 20,347 63,521 197.8 63.4
Auto Club Exchange Group 3,293 3,997 5,896 82.4 55.8
Mercury General Corp. (MCY) 2,474 1,559 3,277 158.7 75.5
COUNTRY Financial 1,893 1,807 3,446 104.8 54.9
Texas Farm Bureau 809 731 1,079 110.6 74.9
P&C Industry 363,291 547,042 1,303,796 66.4 27.9
Source: SNL Financial
Other Economic Factors
• Rising oil prices may cause a double dip recession; on the other hand, an economic downturn may crash oil prices (Gail Tverberg)
• QE2 will end by end of June 2011 • Volatility in exchange rates will impact inflation in
some areas and deflation in other areas • Housing Price volatility (divergence of
replacement cost and housing market value)
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Contact :
Phone: 1-678-732-9112 shaun.wang@risklighthouse.com