session val5 – clifr part ii use of actuarial judgement cia annual meeting Ÿ assemblée annuelle...

Session VAL5 – CLIFR Part II Use of Actuarial Judgement

CIA Annual Meeting Ÿ Assemblée annuelle de l’ICA

June 29 & 30, 2006 Ÿ Les 29 et 30 juin 2006Ottawa, Ontario



• Sub-Committee of CLIFR formed late in 2004

• Members of Sub-Committee: – Jacques Boudreau, Ty Faulds, Carl Kruglak, Dale

Mathews, Christian-Marc Panneton, Michael Promislow, Anne Vincent

• Mandate – review current ways actuarial judgement is brought in to

the GAAP financial reporting process and determine what guidance can be provided to ensure compliance with standards and narrow the range of practice

• Status: Recommendation to PSC



Agenda• Background• Principles for setting assumptions and margins• Considerations for Non Scenario Tested

Assumptions• Modeling• Scenario Testing• Segregated Fund Reserves



Background• CALM is prospective by nature• In projecting future experience, understand past• Consider trends and changing circumstances • A crude application of past experience without

judgement is rarely appropriate however any application of judgement should be based on sound grounds



Background• Section 1750.01 of the General Standards states

– Unless the actuary reports the inconsistency, the assumptions for a calculation for a periodic report should in the aggregate be consistent with those of the prior calculation

• Volatility is a financial reporting reality

• In many circumstances, volatility of results is appropriate when the entity has unhedged or imperfectly hedged exposures to risk



Principles for setting assumptions and margins:

• Assumptions and margins are justified on a prospective basis.

• Maintaining an assumption/margin subject to same level of scrutiny.

• The change in policy liabilities does not reflect a change in past experience that the actuary has sufficient reason to believe is temporary.



Principles for setting assumptions and margins:

• The change in expected assumption is supported with data that indicate a need for change.

• The change in the margin for adverse deviation is supported by a change in the level of risk.

• The change in assumption is not manipulative.– methods to determine assumptions are predetermined

and are not subject to irregular or inconsistent application over time



Considerations for Non Scenario Tested Assumptions:

• The best estimate assumptions reflect the actuary’s best estimate of how future experience will emerge.– based on past experience, industry experience and

other factors such as correlations with other parameters in the valuation.



Considerations for Non Scenario Tested Assumptions:

• Reflect emerging trends in experience, but not random fluctuations in recent past experience. – This is sometimes accomplished by using the average

of the past three to five years’ of experience as the base from which to determine the best estimate assumption.



Considerations for Non Scenario Tested Assumptions: (cont’d)

• Difficult to determine whether changes in past experience are caused by underlying trends, random fluctuations, or cyclical influences.– reflect emerging trends when they have been clearly

established. For example, a 4% drop in actual unit expenses might result in a 2% drop in the choice of best estimate expense assumption, with the other 2% drop reflected a year later if the unit expenses stay low.




• Difficult to determine whether changes in past experience are caused by underlying trends, random fluctuations, or cyclical influences.– Where emerging trends in different assumptions are

offsetting then may delay action on both

– Where going in the same direction then more reason to proceed with a change




• Incorporates guidance from recent fall letters on setting cyclical assumptions

• Impact of policyholder pass through features – ensuring consistency of pass through features with

base assumptions– recognizing limitations on ability to pass through




• Correlation of other assumptions with scenario tested assumptions– interrelationships often difficult to measure– look for relevant experience to aid in reflecting

policyholder behavior, anti-selection…– sensitivity testing often useful in aiding understanding– may be appropriate to assume that policyholders may

not react quickly or fully even if to their advantage



Modeling• Modeling constraints may cause current interest

rate environment, mismatch position, asset quality and mix to have an unrealistic impact.– actual investment policy, and policy constraints often

difficult to model– when and how to recognize changes in investment

approach

• Model results tested to ensure they are reasonably consistent with observed experience.



Modeling• Incorporates guidance from recent fall letters on

reinvestment strategies• Reviews common approaches in modeling asset

investment strategy and things to watch out for• In all take care to not assume prior knowledge of

future projected rates.



Scenario Testing - Principles• Reflects control over mismatch position, asset mix and

asset quality• Recognizes the investment policy as a a model

constraint• Reflects investment practices

– i.e. if practice is to invest long to pick up yield, model should so recognize

• Recognizes current position at balance sheet date• Liabilities set to be sufficient without being excessive



Scenario Testing - Example• Illustrates concepts and not to be taken literally• Concepts discussed can be difficult to implement• Uses duration mismatch as the variable

– could have used asset mix or asset quality

• Assumes you know– historical average duration mismatch,current

mismatch position,target mismatch position and maximum mismatch position

• Discusses 4 potential alternatives



Scenario Testing Example - Alternative 1• Do the testing and set the liability assuming you

remain at the current mismatch position. – may be consistent with investment practice– quite sensitive to actual mismatch position – could result in insufficient liabilities if current position

is lower than historical average and/or target position– could result in excessive liabilities if current position is

significantly higher than historical average and/or target position




move to the maximum mismatch allowed. – clearly sufficient– likely inconsistent with investment practice– implicitly applies a margin to the mismatch position– less sensitive to actual mismatch position at valuation

date




move to the maximum mismatch allowed. – likely results in excessive liabilities, particularly if

maximum is sufficiently higher than the average historical and thus generally unacceptable

– variation could be to restate starting position to maximum

• Not felt to be appropriate as you can’t adjust the past




move to the target mismatch position.– likely consistent with investment practice– less sensitive to actual mismatch position at valuation

date than alternative 1– if target is the same as or slightly higher than the

historical average than would seem appropriate




move to the target mismatch position.– if target is significantly higher than historical average

then may be excessive• unless there is a documented plan to take more mismatch

risk

– if target lower than historical average then may not be sufficient in the absence of a plan to move to the target




move to the average historical mismatch position– likely consistent with investment practice– less sensitive to actual mismatch position at valuation

date than alternative 1– if historical average is the same as or slightly higher

than the target than would seem appropriate




move to the average historical mismatch position– if historical average is significantly higher than the

target then may be excessive if there is a clear plan to take less mismatch risk

– if historical average lower than target then may not be sufficient if there is a clear plan to take more mismatch risk



Scenario Testing Examples - Conclusions

• Liability should be based on mismatch/asset mix/asset quality in existence at the valuation date

• Reinvestment strategies that assume return to historical average or target positions are generally acceptable– generally consistently applied period to period



Scenario Testing Examples - Conclusions

• The period over which these actions are assumed to occur should reflect past experience

• Reinvestment strategies that assume move to maximum allowed positions may result in excessive liabilities



Segregated Fund Reserves• Factors common in these products include:

– single premium nature makes future revenue dependent on future investment return

– inherent instability of revenue stream given mixes heavily weighted towards common stock

– death and surrender guarantees heavily dependent on market performance

– fixed ‘upfront’ nature of acquisition expenses recovered from unstable revenue stream

– inverse correlation of guarantees with revenue



Segregated Fund Reserves:• Incorporates guidance from recent fall letters on

the selection of the CTE and changes in CTE levels

• Level of Aggregation Applied– encouraged to review the Aggregation and Allocation

of Policy Liabilities education note– once level chosen it is normally kept consistent period

to period



Segregated Fund Reserves:• Selection of CTE Level

• Within the CTE60 and CTE80 corridor• Parameter uncertainty

– impact of parameter uncertainty on CTE level should take into account the risk profile of the business

– generally less for closer to expiry / in the money

• Model Risk– model risk would not normally change period to period



Segregated Fund Reserves: Changes in the CTE Level• where designed to simply achieve a measure of

stability this is not appropriate• where recognizing a change in level of risk it is

appropriate• Lowering the CTE level consistent with the risk

can not result in a decrease in the total liability– only can recognize there is more certainty around the

amount needed



Segregated Fund Reserves: Changes in the CTE Level - Example 1• Look at the Standard Error of CTE0 as a

representation of the parameter risk • Standard Error has a different shape then CTE• In the example setting a PfAD of 2.62 times the

standard error with a maximum of CTE80 and minimum of CTE 60

• quite complex to implement



Standard error of the maturity CTE for a 10-year maturity as a percentage of guaranteed value

0%5%

10%15%20%25%30%35%40%45%50%

0% 20% 40% 60% 80% 100% 120% 140%

MV/GV

as

% o

f G

V

s.e. CTE0

2.6 s.e. CTE0

PfAD at CTE60

PfAD at CTE70

PfAD at CTE80



Segregated Fund Reserves: Changes in the CTE Level - Example 2• More simplistic approach, but similar concept • In this example the PfAD is set as 14.2% of the

Guarantee value with a maximum of CTE80 and minimum of CTE 60

• not as theoretically based but consistent with concepts



Maturity PFADs for a 10-year maturity as a percentage of guaranteed value

0%5%

10%15%20%25%30%35%40%45%50%

0% 20% 40% 60% 80% 100% 120% 140%

MV/GV

as

% o

f G

V

Alternate

PfAD at CTE60

PfAD at CTE70

PfAD at CTE80



Segregated Fund Reserves: Investment Return Assumptions• Valuation can be very sensitive to movements in

the market– short term fluctuations of common stocks can be

considerably greater than fluctuations over longer holding periods

– product generally priced and designed for the longer term

– can lead to greater volatility than is theoretically expected



Segregated Fund Reserves: Investment Return Assumptions• Valuation can be very sensitive to movements in

the market– however period to period investment performance

does directly change the best estimate revenues and costs

• May be reasonable to dampen impact of short term fluctuations based on the expectation that much of this is transitory



Segregated Fund Reserves: Investment Return Assumptions - Examples• Looks at 4 different approaches under a given

simplified situation (ignores dividends)– 50 year historical return is 9.5%– current index 1000– previous year index was 900– second previous year was 850



Investment Return Assumptions - Examples• In setting best estimate assumption

– Company A uses the long term historical average– Company B uses a prudent historical long term

average (currently assumed set at 8.5%)– Company C also uses a prudent long term average

(8.5%) but assumes an initial market correction• next years projected level is the average of this years and

previous 2 years projected level (result is 7.67% for next year, 8.5% after)



Investment Return Assumptions - Examples• In setting best estimate assumption

– Company D also uses a prudent long term average (8.5%) but adjusts its rate for the the first 25 years

• the 25th year projected level is the average of this years and previous 2 years projected level (result is 8.47% for 25 years , 8.5% after)

– Resultant projections areT T+1 T+2 T+3 T+5 T+10 T+25 T+50

A 1,000 1,095 1,199 1,313 1,574 2,478 9,668 93,477B 1,000 1,085 1,177 1,277 1,504 2,261 7,687 59,086C 1,000 1,077 1,168 1,268 1,492 2,244 7,628 58,636D 1,000 1,085 1,177 1,276 1,501 2,254 7,628 58,636



Investment Return Assumptions - Examples• Following year (T + 1) market return is 15%

– For Company A revised historical average (51 year now) is 9.61%

– Company B continues to use 8.5%– Company C’s method results in an assumption of

3.61% in year 1, 8.5% thereafter– Company D’s method results in an assumption of

8.3% for 25 years 8.5% thereafter



Investment Return Assumptions - Examples• Resultant projections by Company

T T+1 T+2 T+3 T+5 T+10 T+25 T+50A 1,000 1,150 1,260 1,382 1,660 2,625 10,391 102,906B 1,000 1,150 1,248 1,354 1,594 2,396 8,147 62,626C 1,000 1,150 1,192 1,293 1,522 2,288 7,780 59,803D 1,000 1,150 1,245 1,349 1,582 2,357 7,794 59,803

T T+1 T+2 T+3 T+5 T+10 T+25 T+50A 5% 5% 5% 5% 6% 7% 10%B 6% 6% 6% 6% 6% 6% 6%C 7% 2% 2% 2% 2% 2% 2%D 6% 6% 6% 5% 5% 2% 2%

• Change from Previous Years projections



Investment Return Assumptions - Examples• Following year (T + 2) market return is a loss of

20%– For Company A revised historical average (52 year

now) is 8.94%– Company B continues to use 8.5%– Company C’s method results in an assumption of

31.5% in year 1, 8.5% thereafter– Company D’s method results in an assumption of

9.34% for 25 years 8.5% thereafter




T T+1 T+2 T+3 T+5 T+10 T+25 T+50A 1,000 1,150 920 1,002 1,190 1,826 6,598 56,166B 1,000 1,150 920 998 1,175 1,767 6,007 46,176C 1,000 1,150 920 1,210 1,424 2,141 7,280 55,963D 1,000 1,150 920 1,006 1,203 1,879 7,169 55,963

T T+1 T+2 T+3 T+5 T+10 T+25 T+50A -27% -27% -28% -30% -36% -45%B -26% -26% -26% -26% -26% -26%C -23% -6% -6% -6% -6% -6%D -26% -25% -24% -20% -8% -6%




Investment Return Assumptions - Examples• Upon review the Appointed Actuaries of

Companies C and D noticed their initial returns exceeded the long term historical average

• Adjusted their process to ensure the projected values were not larger – Company C’s revised method resulted in a revised

assumption of 8.94% for approximately 49 years, 8.5% thereafter

– Company D’s revised method also results in 8.94% for approximately 49 years, 8.5% thereafter




T T+1 T+2 T+3 T+5 T+10 T+25 T+50A 1,000 1,150 920 1,002 1,190 1,826 6,598 56,166B 1,000 1,150 920 998 1,175 1,767 6,007 46,176C 1,000 1,150 920 1,002 1,190 1,826 6,598 55,963D 1,000 1,150 920 1,002 1,190 1,826 6,598 55,963

T T+1 T+2 T+3 T+5 T+10 T+25 T+50A -27% -27% -28% -30% -36% -45%B -26% -26% -26% -26% -26% -26%C -23% -22% -22% -20% -15% -6%D -26% -26% -25% -23% -15% -6%




Segregated Fund Reserves: Criteria for Changes in CTE Levels and

Investment Returns• Non manipulative• Consistent application• Produces liabilities within the prescribed range• Method is actuarially sound• Resultant returns are still the best estimate

based on a forward looking assessment

session val5 – clifr part ii use of actuarial judgement cia annual meeting Ÿ assemblée annuelle...

Documents

session val5 clifr

application of judgement

lica principles

lica subcommittee of

lica considerations

risk slide

ontario slide

psc slide