risk trading unit – natural catastrophes in the bond
TRANSCRIPT
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Risk Trading Unit – Trading risk into value
Risk Trading Unit
“Trading risk into value”Innsbruck, July 2007
Marcel Grandi
Natural Catastrophes in the Bond Market- A Trader‘s View
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Risk Trading Unit – Trading risk into value
Agenda
1. Market development and functional areas
2. Examining the needs of insurers and investors
3. Operating structures – assessing required elements
4. Case study
5. Risk trading at Munich Re
Agenda
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Risk Trading Unit – Trading risk into value
1. Market development and functional areas
Risk Trading Unit – Trading risk into value
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Risk Trading Unit – Trading risk into value
5,3
8,4
15,0
1,32,4
5,0
2,52,0 2,3 2,7
1,81,3
5,1
3,3
1,21,11,3 1,1 1,0
2,41,3
0123456789
1011121314151617
1997* 1998 1999 2000 2001 2002 2003 2004 2005 2006 May2007
OutstandingCat Bonds
Issued Cat Bonds in USD bn
Market development and functional areas
* and prior Source: Goldman Sachs
0
50
100
150
200
250
300
350
1999 2000 2001 2002 2003 2004 2005 2006 2007
Munich Re Group Issues
Market Development and functional areas
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Risk Trading Unit – Trading risk into value
Hurricane U.S. Nationwide15005/07Carillon Series 2
Hurricane in East and Golf coast areaEarthquake in New Madrid area and California
18212/99Gold Eagle**
Hurricane in New York & Miami area16512/00PRIME Hurricane
Earthquake in N and S CaliforniaWindstorm in selected European Countries
13512/00PRIME CalQuake & EuroWind
Hurricane in East and Golf coast areaEarthquake in New Madrid area
12004/01Gold Eagle 2001**
Windstorm in selected European Countries11011/05Aiolos
Hurricane U.S. Nationwide8506/06Carillon Series 1
Earthquake in California19012/06Lakeside Re
Typhoon Japan8006/98Pacific Re
Covered PerilsVol.*ClosingTransaction Name
* In USD mn; **Munich Re of America, formerly American Re
Market development and functional areas
Munich Re Track Record
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Risk Trading Unit – Trading risk into value
The cat bond market has further matured in 2005, 2006, 2007Record issuance in 2006 Large pipeline in 2007
New risks transferred to capital markets (industrial 3rd party liability, motor portfolio, trade credit, Mexico EQ, Mediterranian EQ, cat mortality) allow investors to diversify into new risk classes
Cat bond spreads widened substantially after Hurricane Katrina after tightening before Katrina
Storm resulted in first total loss, i.e. Kamp ReSpread widening in particular for critical exposure zones (e.g. US Hurricane)No detaching of capital markets from reinsurance cycleStrong differences in prices for risks with identical expected loss levelSpreads tightening again
Market development and functional areas
Market development and functional areas
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Risk Trading Unit – Trading risk into value
Diversified investor market (cat funds, hedge funds, traditional asset managers)
Higher risk/return layers placed
Competition through „Sidecars“ (private equity)
Munich Re reentered the cat bond market
European windstorm bond (Aiolos) over EUR 110mn (USD 128mn)
Hurricane cat bond shelf program in June 2006 (Carillon)
Second series in Mai 2007 (USD 150mn, B rating)
Cat bond transaction for Zurich in December 2006 (Lakeside)
Market development and functional areas
Market development and functional areas
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Risk Trading Unit – Trading risk into value
Concentration on Peak Exposures
Tight capacities
High premium level
Diversification still limited
Traditional reinsurance without competition for diversifying risks
Price
Capacity
Pacific NW EQAustralia WindAustralia EQUS HurricaneUS EQJapan WindMexico EQCA EQMidwest US EQEurope WindFrance WindJapan EQ
Market development and functional areas
Market development and functional areas
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Risk Trading Unit – Trading risk into value
Investors’ comfort with regard to owning insurance risk will increase due to
Proven track record of past transactions
Better model availability leading to reduced asymmetric information
Sponsors’ net benefit will rise due to
Lower transaction costs per annum because of increased volumes, multi-year transactions and prevailing best practice methods; use of unissued shelf registrations which allow several takedowns
Less risk discounts demanded by investors
Decrease in basis risk as modeling capability is improved
Even without much interference from outside, the market for capital markets risk transfer solutions is likely to grow further with at least slowly increasing growth rates
Market development and functional areas
Market development and functional areas
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Risk Trading Unit – Trading risk into value
2. Examining the needs of insurers and investors
Risk Trading Unit – Trading risk into value
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Risk Trading Unit – Trading risk into value
Needs of insurers and investors – insurer’s view
Advantages
Capacity in tighter markets
Additional and alternative capacity
Diversification
Collateralization
Immediate liquidity
Transparency
Multi year cover
Disadvantages
Basis risk
Decreases with improvements of modelling capabilities
Transaction costs
Risk transfer costs
Tightening of prices between reinsurance and capital markets for Peak Exposures
Complexity
Dependence on investor preferences
Needs of insurers and investors – insurer’s view
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Risk Trading Unit – Trading risk into value
Needs of insurers and investors – investor’s view
Advantages
High yield
Compared to credit markets
Track Record
One default
Uncorrelated asset class
Investment in pure insurance risks
Not possible in insurance stocks
Traded Cat Bond Spreads
0 1000 2000 3000
B
B+
BB-
BB
BB+
BBB+
Rat
ing
Spread
max min
0,23
1,6
2,7
2,8
8,5
Expected Loss
3,6
Needs of insurers and investors – insurer’s view
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Risk Trading Unit – Trading risk into value
Needs of insurers and investors – investor’s view
Comparison of BB rated CMBS with a BB rated cat bond (Lakeside)
31.12.2003 31.12.2004 30.12.2005 29.12.20060
50100150200250300350400450500550600650
Vergleich Spread CMBS vs. ILS Produkt
Credit Spread CMBS BB Risk
Current ILS Bond Spread
Spr
ead
in B
P
Needs of insurers and investors – insurer’s view
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Risk Trading Unit – Trading risk into value
Needs of insurers and investors – issues for investors
Liquidity
High bid/offer spreads
Secondary market write downs (after issuance)
Risk assessment
Rating and pricing based on risk modelling
Different modelling approaches of the Modelling Agencies
Modelling arbitrage
Change in modelling approach
E.g. US Hurricane
Doubling of industry losses
Downgrade of outstanding Hurricane Bonds
Needs of insurers and investors – insurer’s view
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Risk Trading Unit – Trading risk into value
Needs of insurers and investors – conflict of interest
Investor market
Excess demand for hurricane protection first half 2006
Secondary market pricing
Write down of new issues
Change in investor appetite
Preference for one year deals
Regional covers instead of whole market
Exclusions (flood)
MR requirements
High volume
Fair price
Multi year cover
Whole market protection
No exclusions
Example US Hurricane – MR cat bond 2006 (Carillon I)
Needs of insurers and investors – insurer’s view
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Risk Trading Unit – Trading risk into value
3. Operating structures – assessing required elements
Risk Trading Unit – Trading risk into value
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Risk Trading Unit – Trading risk into value
Operating structures – assessing required elements
Efficient protection
Success of placement
CostsCompliance with
regulations
Operating structures – assessing required elements
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Risk Trading Unit – Trading risk into value
Operating structures – assessing required elements
Structural considerations
Determine risk to be securitized (peak exposure)
Determine expected loss (EL) probability of securitisation
Select the EL range offering the best economics (protection vs. price)
The lower the EL, the higher the multiple to be paid as spread
The higher the EL the lower the multiple
Increasing investor appetite for higher EL ranges
Fit in overall reinsurance program
Operating structures – assessing required elements
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Risk Trading Unit – Trading risk into value
Operating structures – assessing required elements
Selection of trigger type
Parametric (based on event generation)
Industry loss (based on damage caused)
Modelled loss (reference portfolio)
Indemnity (based on financial loss of sponsor)
Basis RiskSponsor
Modelling RiskInvestor
Parametric Modelled Loss Indemnity
Operating structures – assessing required elements
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Risk Trading Unit – Trading risk into value
Operating structures – assessing required elements
Selection of trigger type
Indemnity trigger
Best for sponsor (no basis risk)
Availability of exposure data
Publication of exposure data
Challenging to sell to investors (moral hazard)
Synthetic trigger (parametric, modelled loss, market loss)
Wide market acceptance (clarity & transparency)
Assessment of basis risk essential
Availability of internal know how
Operating structures – assessing required elements
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Risk Trading Unit – Trading risk into value
Operating structures – assessing required elements
Clarity on accounting and taxation
Balance sheet consolidation to be avoided
Close coordination with auditors
No financial leverage
Use reinsurer as fronter and legal sponsor
Taxation regime
No unfavourable taxation of collateral trust assets and premium cash flows (excise tax)
SPV location decisive
Double tax treaties in place
Operating structures – assessing required elements
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Risk Trading Unit – Trading risk into value
Operating structures – assessing required elements
Selection of service providers
Modelling Agency (inc. loss verification)
Credibility of model crucial for rating and success of transaction
SPV administrator
Indenture trustee
Legal
Limited number of law firms active
Placement (one placement bank sufficient)
Beauty contest
Rating agency (one agency sufficient)
Operating structures – assessing required elements
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Risk Trading Unit – Trading risk into value
Form of issuance
144A private placement standard „Principal at Risk“
Tranching
Currency
SPV
Off Shore (Cayman or Bermuda, Ireland)
Minimal capitalization provided by Charitable Trust
Consolidation with sponsor unlikely
Operating structures – assessing required elements
Operating structures – assessing required elements
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Risk Trading Unit – Trading risk into value
Operating structures – assessing required elements
Project management (responsible for execution and success)
Conceptual design
Internal coordination
Internal submission
Engagement of service providers (organization of beauty contests)
Manage internal and external interfaces and service providers
Manage costs
Control time schedule
Controlling
Operating structures – assessing required elements
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Risk Trading Unit – Trading risk into value
4. Case Study
Risk Trading Unit – Trading risk into value
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Risk Trading Unit – Trading risk into value
Covered Territory: California Risk: EarthquakeModeling Agent: RMS
USD 190mn principal at risk bonds3-year EQ cover for Zurich AmericanDual Trigger based on PCS industry loss and Zurich ultimate net loss (UNL)Rating S&P: BB+Spread: 650bps above LIBOR
Executive summary
Case study I – Lakeside Re
Case study
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Risk Trading Unit – Trading risk into value
Issuer Lakeside Re Ltd., a Cayman Islands exempted company licensed as a Class B insurer
Reinsurer Münchener Rückversicherungs-Gesellschaft Aktiengesellschaft (“Munich Re”)
Ceding Insurer Zurich American Insurance Company (“Zurich”), for itself and its Pool Members (“ZAIC Pool”)
Ceding Insurer Affiliates Certain branches and affiliates of the Zurich Insurance Company other than the ZAIC Pool
Securities Offered US$ 190,000,000 Principal At-Risk Variable Rate Notes
Closing Date December 20, 2006
Risk Period December 21, 2006 to December 23, 2009
Scheduled Redemption Date December 31, 2009
Triggers (i) Industry Loss threshold based on PCS Reports
(ii) Ultimate Net Loss based on actual claims
Covered Territory The United States state of California
Named Peril Earthquake
S&P Rating On the Closing Date, the Notes are expected to be rated “[BB+]”
Distribution 144A Private Placement to Qualified Institutional Buyers in Permitted Jurisdictions who, for U.S. Persons, are also Qualified Purchasers and residents of and purchasing in a Permitted U.S. Jurisdiction or a Permitted Non-U.S. Jurisdiction
Case study I – Lakeside Re
Case study
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Risk Trading Unit – Trading risk into value
Collateral Account$ 190mn
$ 190mn Reinsurance Agreement
Outstanding Principal Amount at Redemption
$ 190mnPrincipal At-Risk Variable
Rate Noteholders
DepositBank
$ 190mn Retrocession Agreement
Premiums
$ 190,mn Bank Deposit
LIBOR - Eligible Bank Fee
$ 190mn Note Proceeds
LIBOR + 650bps
Lakeside Re Ltd.
ZurichAmerica
Munich Re
Premiums
Case study I – Lakeside Re
Case study
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Risk Trading Unit – Trading risk into value
Estimated InsuredIndustry Losses
($ in millions)
AnnualProbability
of Exceedance
Estimated Zurich Portfolio Losses
($ in millions)91.679 0,10%84.111 0,13%73.672 0,20%64.840 0,29%61.154 0,33%58.525 0,37% Exhaustion Amount56.908 0,40%51.889 0,50%51.708 0,50% Trigger Amount45.722 0,67%40.000 0,88%37.628 1,00%32.305 1,33%25.329 2,00%14.594 4,00%
3.972 10,00%
Industry Trigger Amount
For the indemnity layer, the expected loss is 0,43%
Case study I – Lakeside Re
Case study
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Risk Trading Unit – Trading risk into value
21 InvestorsInvestors
49%
28%
12%
11%
Volume Issue size of US$ 190mn
Deal over subscribed
Use of Balance Sheet
Expiring Redwood V and VI
Total “bridge financing” of US$ 42.5mn
Case study I – Lakeside Re
Spread 650bps above 3m-LIBOR
In line with reinsurance pricing
Cat FundReinsurerInstitutionalHedge Fund
Case study
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Risk Trading Unit – Trading risk into value
Covered Area
Covered Area: US East CoastRisk: HurricanesModeling Agent: AIR
USD 150mn cat bond for Munich ReHurricane cover over four wind seasonsTrigger based on PCS industry loss (Attachment USD 35 bn; Exhaustion USD 45 bn)Rating S&P: BSpread: 1525bps above LIBOR for 3 2/3 years; seasonalized: 1400bps above LIBORAttracted new cat bond investors
Non-Covered Area
Executive summary
Case Study II – Carillon 2
Case study
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Risk Trading Unit – Trading risk into value
Transaction structure
Carillon Ltd. Capital Markets Investors
Morgan Stanley Capital Services Inc.
Guaranteed by Morgan StanleyA+/Aa3 (2)
Cayman Island SPV Class E Principal At-Risk Variable Rate Notes
Investment Income on Permitted Investments +
any gain
3M LIBOR – Swap Spread and Return of par on
Permitted Investments
Return of Original Principal Amount at Maturity (if no
trigger event)
Interest: 3M LIBOR +Interest Spread
Proceeds (USD)
PCS Index-triggeredUS Hurricane
Financial Contract
Payment Equal to Sum of Interest Spread and Swap
Spread
Collateral Account Contingent Security Interest
Munich Re
AA-/Aa3/AA- (1)
Proceeds 3M LIBOR – Swap Spread + Principal at Maturity
The Bank of New York Trustee
Notes1. S&P (Financial Strength), Moody’s (Insurance Financial Strength) and Fitch (Insurer Financial Strength) ratings respectively2. S&P (Long Term Issuer Credit) and Moody’s (Senior Unsecured Debt) ratings respectively
Case Study II – Carillon 2
Case study
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Risk Trading Unit – Trading risk into value
Trigger mechanism
Principal Reduction Formula
Principal reduction affecting the Notes will be applied linearly between the applicable Event Attachment Amount and the applicable Event Exhaustion Amount using the formula below:
Any principal reduction is limited to the Outstanding Principal Amount for the Class
OriginalPrincipalAmount
X
Event Attachment
Amount (USD 35bn)
Event Amount –
Event Attachment
Amount (USD 35bn)
Event Exhaustion
Amount(USD 45bn)
–
Generalized Class Payout Functions
0
20
40
60
80
100
Principal Reduction(%)
EventAttachmentAmount
EventExhaustionAmount
PCS Index
Principal written down according to Property Claims Services’ (PCS) loss estimates
Case Study II – Carillon 2
Case study
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Risk Trading Unit – Trading risk into value
Notes1. Source: AIR Worldwide
4.00%3.39%Probability of Exhaustion
4.59%3.97%Expected Loss
5.26%4.61%Probability of Attachment
Sensitivity Case
Base CaseClass E
Case Study II – Carillon 2
Risk metrics
Case study
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Risk Trading Unit – Trading risk into value
17 InvestorsInvestors
Volume Issue size of USD 150mn
Largest single B rated cat bond ever placed
Use of Balance Sheet Munich Re bought USD 1.5mn to round up to USD 150mn
Spread 1525 bps above 3m-LIBOR (annualized)
1400 bps seasonalized
Transaction outcome
34%
20%
12%
7%3%
24%
Hedge FundCat FundI BankReinsurer
25%
13%
11%
11%
10%
7%2%
21%
SwitzerlandCaymanBermudaGermanyU.S.U.K.CanadaOthers
Pension FundInsurer
Case Study II – Carillon 2
Case study
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Risk Trading Unit – Trading risk into value
5. Risk trading at Munich Re
Risk Trading Unit – Trading risk into value
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Risk Trading Unit – Trading risk into value
0
5
10
15
1997* 1998 1999 2000 2001 2002 2003 2004 2005 2006**
Outstanding Cat Bond Issued Cat Bond
Optimal moment to increase our activity in this market segmentbenefiting from a well developed infrastructure and maturing markets
Opportunities for portfolio optimization, increase of capital efficiency and additional earnings with a minimum of launching costs for MR
Attractive market conditionsAttractive market conditions
Source: Lane Financial L.L.C. 2006
* and prior; ** to date
Source: Goldman Sachs
0
1
2
3
0
1
2
3
4
5
6
7
8in bn
2001 2002 2003 2004 2005 2006
Average expected loss*(left axis in %)
Pricing “multiples“* (right axis)
*For outstanding cat bonds only
Risk Trading – Key considerations for Munich Re
Risk Trading – Key considerations for Munich Re
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Risk Trading Unit – Trading risk into value
Retain risks
Be active player in primary and secondary market
Extension of “buy and hold” strategy
Combine and restructure risks
Sell at favourable terms and conditions
Consulting, structuring, project management and placement support
Risk fronting / transformation and (interim) capacity provider
Optimise portfolio
Use of additional capacity
Risk-based, investment and arbitrage income
Munich Re’s Risk Trading approach
Risk Trading – Active use of capital markets
Managing our own risks
Fee and arbitrage income
Improve our risk/return profile and save costs Fee and risk-based income
Managing our clients’ risks
Risk warehousing Restructuring and reselling
Risk Trading – Active use of capital markets
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Risk Trading Unit – Trading risk into value
Dynamic market development
Doubling of market volume until 2008
Securitization market 10% of reinsurance market
Retrocession predominantly via capital markets
New investors (high net worth individuals)
New risk classes
Risk Linked Securities integral part of risk management spectrum
Outlook
Outlook
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Risk Trading Unit – Trading risk into value
Contacts
Marcel Grandi
Senior Manager - Structuring
Phone: +49 (0)89 3891-4114
E-mail: [email protected]
Münchener Rückversicherungs-Gesellschaft
Königinstrasse 107
D-80802 München
Conatcts