blowing through the range 2014 clrs presentation · blowing through the range 2014 clrs...

Blowing through the range

2014 CLRS presentationSeptember 15, 2014

Christopher Andersen, FCAS, MAAARon Fowler, FCAS, MAAA

Agenda

► Actuarial ranges and their context► Communication of the actuarial range► When things go wrong – Case studies

► Financial guarantee► Catastrophes► Asbestos

What is in an actuarial range?

► Actuarial standards of practice No. 43► Property / Casualty Unpaid Claim Estimates

► Actuarial central estimate► An estimate that represents an expected value over the range of

reasonably possible outcomes (“range”).

► 3.3.1 …may not include all conceivable outcomes, as, for example, it would not include conceivable extreme events where the contribution of such events to an expected value is not reliably estimable.

What disclosures are proper for an actuary to communicate?

► 3.6.7 – External conditions► Claim obligations are influenced by … potential economic

changes, regulatory actions, judicial decisions, or political or social forces. …the actuary is not required to have detailed knowledge of or consider all possible external conditions…

► 3.6.7 – Changing conditions► The actuary should consider whether there have been significant

changes in conditions …Examples include reinsurance program changes, … claims personnel [changes], …

What disclosures are proper for an actuary to communicate? [cont.]

► 3.6.8 – Uncertainty► The actuary should consider the uncertainty … This standard does

not require or prohibit the actuary from measuring this uncertainty. … the actuary should consider the types and sources of uncertainty … [and] may include uncertainty due to model risk, parameter risk, and process risk.

► 4.2 – Additional disclosures (re: range of estimates)► In the case when the actuary specifies a range of estimates, the

actuary should disclose the basis of the range provided

When things go wrong – Case studies

► 2008 financial crises ► Financial guarantee insurance

► Unusual catastrophes► Hurricane Katrina► Thailand flooding► New Zealand earthquake

► Asbestos

The 2008 financial crises was more sudden than previous depressions in the financial markets

-40.0%

-30.0%

-20.0%

-10.0%

0.0%

10.0%

20.0%

30.0%DJIA – Year over year percentage change

Prepared by EY

Industry loss ratio spiked to 200% to 300% and have still not recovered to pre-financial crisis levels

0.0%100.0%200.0%300.0%400.0%500.0%600.0%700.0%800.0%900.0%

1000.0%

Loss ratios for Industry and Top Financial Guarantee and Mortgage-Back Securities writers

P&C Industry Company 1 Company 2 Company 3 Company 4

Based on SNL data; Prepared by EY

Unprecedented financial market performance underlined inadequate reserve amounts in financial guarantee and mortgage guarantee products

-50.0%-25.0%

0.0%25.0%50.0%75.0%

100.0%125.0%

1 year reserve development / Prior year reserves

Commercial Auto Workers CompensationMedical Professional Fidelity and suretyFinancial Guarantee and Mortgage Gaurantee

Based on SNL data; Prepared by EY

Financial guarantee insurance

► What went wrong?► Was the cause of the reserve development due to process risk or

parameter risk?

► The development was due to a “tail event” or process risk

► How did the actuarial models uphold?► New information needed to be reflected that was not traditional to

historical analysis and development► Economic projections► TARP program

► Scenario testing is critical in developing a range of expectations

2006 vintage curves indicated stability

0%

5%

10%

15%

20%

25%

30%

35%

40%

45%

50%2 8 14 20 26 32 38 44 50 56 62 68 74 80 86 92 98 104

110

116

122

128

Seve

rity

Loan Age

1998199920002001200220032004200520062007

Post 2008 financial crisis the historical development was no longer relevant

0%

5%

10%

15%

20%

25%

30%

35%

40%

45%

50%2 8 14 20 26 32 38 44 50 56 62 68 74 80 86 92 98 104

110

116

122

128

Seve

rity

Loan Age

1998199920002001200220032004200520062007

Financial guarantee insuranceCase study – Post-crisis estimates and range

► Scenario testing was employed as future state after shock was difficult to ascertain from historical data► What movement in transition probabilities is plausible?► How high can loss severities be?

Scenarios Transition probabilities Loss Severities Difference to Median

A No change Decrease by 5% -36%

B Used 1 month look back No change -28%

C Used 2004 probabilities Increased by 5% -4%

D Lag vintage 1 year Increased by 5% +4%

E Used 2005 probabilities for all older vintages Increased by 7.5% +57%

F Used 2007 probabilities for all vintages No change +118%

Developing a range using non-traditional information and scenario testing

► Scenario testing► Search for relevant information from non-traditional sources

► Economic data and trends► Understand reform and its impact

► Discuss with client reasonability of assumptions and apply professional skepticism to avoid biases► Develop a maximum probable loss scenario► Consider industry perspective on phenomenon


► 2008 financial crises ► Financial guarantee insurance


► Asbestos

Recent catastrophes have proven to have stipulations that make predicting ultimate losses more uncertain

► Hurricane Katrina► Wind versus water disputes► Extended recovery and rebuilding period

► Thailand flooding► Claim investigation was severely delayed to due standing water

and the inability to investigate claim sites► Largest claims were business interruption and have a time-

element

► New Zealand earthquake

The Thailand Flooding claims have been harder to identify and investigate due to the lingering water in warehouses

Prepared by EY; based on RAA data. 1 period is equal to 3 months

0.0%10.0%20.0%30.0%40.0%50.0%60.0%70.0%80.0%90.0%

100.0%

1 3 5 7 9 11 13 15 17 19

% C

ase

incu

rred

to u

ltim

ate

Periods

Thailand FloodsKatrinaRitaWilmaNZ2 EQJapan EQWTC

► Significantly lower after 6 periods► Time-element coverage is causing

uncertainty

Historical earthquake % of case incurred to ultimate development

Prepared by EY; based on RAA data. 1 period is equal to 3 months

0.0%

20.0%

40.0%

60.0%

80.0%

100.0%

120.0%

1 2 3 4 5 6 7 8 9 1011121314151617181920

% C

ase

incu

rred

to u

ltim

ate

Periods

NZ EQ2ChileJapanLoma PrietaNorthridgeNZ EQ1NZ EQ3

► The case incurred amounts continue to rise through 9 report periods

New Zealand earthquake has experience high “event creep” than other recent natural catastrophes

► Event creep (New Zealand)► New Zealand Earthquakes: Christchurch, NZ

► NZ I: October 2010► NZ II: February 2011► Many smaller aftershocks

► New Zealand Earthquake Commission pays up to 100,000 NZD property, 20,000 NZD contents

► Suncorp and IAG have majority of the market share for additional insurance

► Reinsurers then provide excess cover (they get the effects of the creep)

Reason for event creep for New Zealand earthquake

► Scope of event (largest natural CAT year in NZ)► Apportionment: losses were apportioned between the two

events, often with complicated models► Renewals: the two earthquakes are treated as two events

and renewals separate the contracts so there are new limits

► Liquefaction (some neighborhoods abandoned), this was not factored into many loss models

► Claim settlement time (government insurer handling claims, slower than private insurance to process)

► Cordoned off areas (Red Zone) causes BI losses

Liquefaction


► 2008 financial crises ► Financial guarantee insurance► Mortgage-back security insurance


► Asbestos

A history of predictions and re-predictions

► The poor track record of estimating asbestos

0100,000200,000300,000400,000500,000600,000700,000800,000900,000

1,000,000

1988 1993 1997 2005 2013

Manville Trust – Asbestos Claims filing

Filed claims Expected Ultimate filed claims

AM Best’s asbestos and environmental studies have a similar shape

0

10

20

30

40

50

60

70

80

90

1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

P/C Industry Net Asbestos Losses

Incurred Losses AM Best Ultimate

Based on annual statement data and AM Best

So what’s in an asbestos range estimate?

► Historical development may have been considered an (un)conceivable extreme scenario or event

► Ranges are based on the best available data at that time► Survival ratio analyses► Exposure analyses► Market share and industry estimates

► Wide range of estimates may result – what is the right range?

blowing through the range 2014 clrs presentation · blowing through the range 2014 clrs...

Documents