Actuarial versus Financial Engineering

Transcription

1 FINANCIAL RISK MANAGEMENT Actuarial versus Financial Engineering CAE Fall 2008 Meeting 17 November 2008 Frank Cuypers ADVISORY

2 Performance, Risk and Capital performance 1 Value creator 2 Value destroyer RoRAC Value destroyer 2 Value creator risk 1

3 Value Added of Insurance performance RoRAC risk 2

4 Value Added of Credit performance RoRAC capital enhanced capital risk 3

5 Plan Financial & actuarial engineering Insurance linked securities Financial vehicles for insurers 4

6 Financial & Actuarial Engineering Similar Challenges Financial Engineers Actuarial Engineers Data availability Time series analysis Timeframes 1 year Reliance on rating agencies Experience modelling Extreme events Risk measures short VaR expected shortfall Tail dependences Exposure modelling Innovation 5

7 Financial & Actuarial Engineering Extreme Events loss probability Tail losses, Extreme events loss severity 6

8 Financial & Actuarial Engineering Extreme Events 7

9 Financial & Actuarial Engineering Similar Challenges Financial Engineers Actuarial Engineers Data availability Time series analysis Timeframes 1 year Reliance on rating agencies Experience modelling Extreme events Risk measures short VaR expected shortfall Tail dependences Exposure modelling Innovation 8

10 Financial & Actuarial Engineering Risk Measures loss probability acceptable losses extreme losses VaR = highest loss with 99% confidence = 100 year event expected shortfall = average loss if VaR is exceeded loss severity 9

11 Financial & Actuarial Engineering Risk Measures normal distribution fat tail distribution VaR expected shortfall normal distribution expected shortfall fat tail distribution 10

12 Financial & Actuarial Engineering Similar Challenges Financial Engineers Actuarial Engineers Data availability Time series analysis Timeframes 1 year Reliance on rating agencies Experience modelling Extreme events Risk measures short VaR expected shortfall Tail dependences Exposure modelling Innovation 11

13 Financial & Actuarial Engineering Tail Dependencies Kobe EQ Property Burglary Barings Bank September 11 Property Aviation BI Life Markets Sub-prime? risk 2 90% confidence interval 70% confidence interval 50% confidence interval best estimate risk 1 12

14 Financial & Actuarial Engineering Tail Dependencies Use copulas with realistic tail dependence Clayton, t-copula, grouped t-copula, Not Gauss copula! almost independent dependent (Gauss) tail dependent (Clayton) 13

15 Financial & Actuarial Engineering Similar Challenges Financial Engineers Actuarial Engineers Data availability Time series analysis Timeframes 1 year Reliance on rating agencies Experience modelling Extreme events Risk measures short VaR expected shortfall Tail dependences Exposure modelling Innovation 14

16 Financial & Actuarial Engineering Exposure modelling Homeowners insurance requires simulating hurricanes Historic Probabilistic 15

17 Financial & Actuarial Engineering Similar Challenges Financial Engineers Actuarial Engineers Data availability Time series analysis Timeframes 1 year Reliance on rating agencies Experience modelling Extreme events Risk measures short VaR expected shortfall Tail dependences Exposure modelling Innovation 16

18 Plan Financial & actuarial engineering Insurance linked securities Financial vehicles for insurers 17

19 Plan Financial & actuarial engineering Insurance linked securities Financial vehicles for insurers 18

20 Insurance Linked Securities Structure RoI swap counterparty LIBOR costs sponsor (cedent) spread + costs issuer (SPV) LIBOR + spread principal investors contingent claim bond proceeds RoI AAA assets investment reinsurance uncorrelated investment 19

21 Insurance Linked Securities Investor Motivations Higher spreads than other fixed-income assets Low (no?) correlation to other fixed-income assets Low (no?) impact of adverse credit events 20

22 Insurance Linked Securities Players Sponsors: Issuers: Structurers: Risk consultants: Rating agencies: Sales: 2 ndary trading: Investors: Swiss Re, Hartford, Glacier Re, WinCAT, Parametric Re, Pioneer, Shenandoah, Swiss Re, Goldman Sachs, Aon, AIR, RMS, EQE, Milliman, Moody s, S&P, Fitch Swiss Re, Goldman Sachs, Aon, Swiss Re, Goldman Sachs, UBS, Nymex, CME, mainly capital market players bankers realm insurers realm bankers realm bankers realm 21

23 Insurance Linked Securities Investor Segmentation dedicated funds US money managers Europe hedge funds banks Bermuda (re)insurers Japan 0% 10% 20% 30% 40% 50% 0% 20% 40% 60% 80% 22

24 Insurance Linked Securities Market Capacity issue year cat bonds all ILS size / GUSD 23

25 Insurance Linked Securities Perils life cat peril motor other LoBs multiperil wind US accident EQ US wind RoW EQ RoW credit XXX EV mortality contingency size / GUSD 24

26 Insurance Linked Securities Market Potential Market [GUSD] ILS capacity [GUSD] ILS capacity [%] XXX % Cat % EV % motor % mortality % 25

27 Insurance Linked Securities Perspectives Short term Reduction of ceded capacity, because o soft phase of cycle makes traditional reinsurance more attractive o Swiss Re has less need, thanks to the Berkshire Hathaway QS o testing more alternative financial vehicles More XS layers & non-cat LoBs securitised Long term Solvency II will boost o the securitisation of working layers & non-cat LoBs o the transition from risk to capital & liquidity management Spreads will further decrease Liquidity will increase & 2 ndary trading dominate Alternative financial vehicles will grow & capital markets will increasingly assume the role of reinsurance 26

28 Plan Financial & actuarial engineering Insurance linked securities Financial vehicles for insurers 27

29 Plan Financial & actuarial engineering Insurance linked securities Financial vehicles for insurers 28

30 Financial Vehicles Sidecar Transaction with several parties (typically private equity, hedge funds) SPV retrocedes large quota share to investors Insurer can start up new business Investor has a predefined exit strategy Long due diligence 29

31 Financial Vehicles Ultimate Net Loss contract (UNL) Transaction with one party (typically hedge fund) Investor deposits cash on blocked account If certain conditions are fulfilled then insurer can withdraw ~ fully collateralised working XL w/o RI Long due diligence 30

32 Financial Vehicles Contingent Capital Transaction with one party (typically investment bank, hedge fund) If certain conditions are fulfilled (nat cat, GDP, ) then investor provides insurer capital at favourable conditions 31

33 Financial Vehicles Industry Loss Warranty (ILW) Transaction with one party (typically investment bank, hedge fund) If industry loss index exceeds threshold then seller pays buyer Very fast & standard Volume ~ 5 GUSD? 32

34 Financial Vehicles Motivations Transferred risk Capital enhancement Regulatory-Accounting-Tax benefit Ceded margins Residual risks Flexibility Effect RAT benefit Price Residual risk Time ILS risk transfer depends competitive basis 3 6 months ILS shelf program risk transfer depends very competitive reduced basis 2 3 weeks sidecar risk transfer good competitive credit 3 6 months UNL risk transfer good expensive tail 3 6 months contingent capital financing weak expensive credit 1 2 months ILW risk transfer depends volatile basis, credit hybrid capital financing good volatile none? 2 3 days 1 2 months 33

35 Plan Financial & actuarial engineering Insurance linked securities Financial vehicles for insurers 34

36 The information contained herein is of a general nature and is not intended to address the circumstances of any particular individual or entity. Although we endeavor to provide accurate and timely information, there can be no guarantee that such information is accurate as of the date it is received or that it will continue to be accurate in the future. No one should act on such information without appropriate professional advice after a thorough examination of the particular situation. Presenter s contact details Frank Cuypers fcuypers@kpmg.com 35