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exam 7 > Marshall > Flashcards

Marshall Flashcards

1
Q

what are risk margins intended to do?

Marshall et al.

A

provide an extra bit of cushion above the central estimate (i.e. mean)

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2
Q

what are less sophisticated approaches to determining CoVs?

Marshall et al.

A
  • ignore individual characteristics of valuation portfolio

- based on “model” portfolios

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3
Q

what are more sophisticated methods to determining CoVs?

Marshall et al.

A

-combine quantitative analysis (i.e. stochastic modeling) with qualitative analysis of sources of uncertainty not captured quantitatively

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4
Q

what is the most common approach to populating the correlation matrix?

(Marshall et al.)

A
  • relies heavily on actuarial judgment
  • key risks believed to cause correlation between valuation portfolios are categorized as high, medium, or low
  • each category is assigned a correlation coefficient value
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5
Q

why do quantitative approaches to populating the correlation matrix tend to be the exception?

(Marshall et al.)

A

-most techniques require a significant amount of data, time, and cost to produce credible and intuitive results

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6
Q

what two distributions are most commonly selected for risk margin analysis?

(Marshall et al.)

A
  • lognormal

- normal (especially at lower probabilities of adequacy where it can generate a higher risk margin than logN)

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7
Q

what does bolt-on approach refer to?

Marshall et al.

A
  • any approach that does not involve a single unified distribution of the entire distribution of possible future claim costs
  • ie: separate analyses to develop a central estimate of insurance liabilities and estimate risk margins
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8
Q

why is it impossible to develop a purely quantitative model for representing the range of possible future claim cost outcomes?

(Marshall et al.)

A
  • judgment is essential to assessing insurance liabilities and risk margins
  • well-fitting models only reflect past sources of uncertainty
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9
Q

what is a claims portfolio?

Marshall et al.

A
  • aggregate portfolio for which risk margins must be estimated
    ex: XYZ Insurance
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10
Q

what are valuation classes?

Marshall et al.

A
  • portfolios that are considered individually as part of the risk margin analysis
    ex: Property vs. Auto
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11
Q

what is a claim group?

Marshall et al.

A

a group of claims with common risk characteristics

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12
Q

at the highest level, what are two sources of uncertainty?

Marshall et al.

A

systemic risk

independent risk

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13
Q

what does systemic risk represent?

Marshall et al.

A

risks that are common across valuation classes or claim groups

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14
Q

what are the two sources of systemic risk?

Marshall et al.

A
  • internal systemic risk

- external systemic risk

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15
Q

what is internal systemic risk?

Marshall et al.

A

risks internal to the insurance liability valuation/modeling process

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16
Q

what are 3 examples of internal systemic risk?

Marshall et al.

A
  • model structure
  • model parameterization
  • data accuracy
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17
Q

what is internal systemic risk also referred to as?

Marshall et al.

A

model specification risk

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18
Q

what is external systemic risk?

Marshall et al.

A

risks external to the insurance liability valuation/modeling process

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19
Q

what is an example of external systemic risk?

Marshall et al.

A

-future trends in claim cost outcomes (material costs, labor costs) that may cause actual experience to differ from what is expected based on the current environment and trends

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20
Q

what does independent risk represent?

Marshall et al.

A

-risks that occur due to the randomness inherent in the insurance process

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21
Q

what are two sources of independent risk?

Marshall et al.

A
  • random component of parameter risk

- random component of process risk

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22
Q

what does the random component of parameter risk represent?

Marshall et al.

A

-extent to which the randomness associated with the insurance process affects the ability to select appropriate parameters in the valuation models

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23
Q

what does the random component of process risk represent?

Marshall et al.

A

pure effect of the randomness associated with the insurance process

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24
Q

what types of risk are traditional quantitative modeling techniques best suited for analyzing?

(Marshall et al.)

A
  • independent risk

- historical external systemic risk

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25
Q

what types of risk do traditional methods fail to fully capture?

(Marshall et al.)

A
  • internal systemic risk

- future external systemic risk

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26
Q

what considerations should go into splitting the claims portfolio into valuation classes?

(Marshall et al.)

A
  • need to balance practical benefits of higher level allocation with insights from granular allocation
  • retain as much consistency as possible between central estimate analysis and risk margin analysis
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27
Q

why might it be preferable to align valuation classes with the valuation portfolios analyzed for central estimate purposes?

(Marshall et al.)

A
  • allows risk margin analysis to be conducted in the context of the central estimate analysis
  • allows quantitative and qualitative analysis to be aligned with central estimate valuation
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28
Q

what are two reasons why it might not be possible to conduct quantitative analysis at the same granularity used for central estimate purposes?

(Marshall et al.)

A
  • credibility concerns

- implementation costs

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29
Q

when it’s not possible to conduct quantitative analysis at the same granularity as central estimate purposes, what can we do?

(Marshall et al.)

A

-conduct quantitative analysis on aggregated valuation classes and allocate down to more granular classes

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30
Q

what is an example of a valuation class that typically requires further allocation into claim groups, and why?

(Marshall et al.)

A

home portfolio:

  • dev patterns differ between cat and non-cat claims
  • liability claims tend to behave differently from other home claims
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31
Q

what are three reasons why stochastic modeling techniques do NOT capture all sources of uncertainty?

(Marshall et al.)

A
  • good models fit past data well -> tends to remove past episodes of external risk, leaving only random sources of uncertainty behind
  • if past external risk is not removed completely - must consider if we expect these to continue into the future
  • models normally don’t catch uncertainty arising from internal systemic risk
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32
Q

what are five modeling techniques?

Marshall et al.

A
  • Mack
  • Bootstrapping
  • Stochastic CL
  • GLM
  • Bayesian
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33
Q

what is a useful supplement for any analysis of independent risk?

(Marshall et al.)

A

internal and external benchmarking

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34
Q

what are three sources of internal systemic risk?

Marshall et al.

A
  • specification error
  • parameter selection error
  • data error
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35
Q

what is specification error?

Marshall et al.

A

error that arises because the model cannot perfectly model the insurance process

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36
Q

what is parameter selection error?

Marshall et al.

A

model cannot adequately measure all predictors of future claim costs or trends in these predictors

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37
Q

what is the difference between the parameter risk component of independent risk and the parameter selection error component of internal systemic risk?

(Marshall et al.)

A
  • parameter selection error relates to actual selection of model parameters
  • parameter risk relates to the proper parameterization of the selected predictors
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38
Q

what is data error?

Marshall et al.

A
  • error that arises due to lack of credible data
  • can also refer to an inadequate knowledge of the portfolio being analyzed, including pricing, underwriting, and claims management processes
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39
Q

describe an approach to analyzing internal systemic risk

Marshall et al.

A
  • balanced scorecard is developed to objectively assess the model specification against a set of criteria
  • for each source of internal systemic risk, risk indicators are developed and scored against the criteria
  • scores are aggregated for each valuation class and mapped to a quantitative measure (CoV) of the variation arising from internal systemic risk
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40
Q

what subjective decisions must be made within the balanced scorecard approach to analyzing internal systemic risk?

(Marshall et al.)

A
  • risk indicators
  • measurement and scoring criteria
  • weight given to each risk indicator
  • CoVs that map to each score
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41
Q

what are risk categories within external systemic risk? (7)

Marshall et al.

A
  • economic and social risks
  • legislative, political, and claim inflation risks
  • claim management process change risk
  • expense risk
  • event risk
  • latent claim risk
  • recovery risk
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42
Q

what are economic and social risks?

Marshall et al.

A

uncertainty associated with inflation, social trends, etc.

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43
Q

what are legislative, political, and claim inflation risks?

Marshall et al.

A

uncertainty associated with changes in the political landscape, shifts/trends in the level of claim settlements, etc.

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44
Q

what is claim management process change risk?

Marshall et al.

A

uncertainty associated with changes in claim reporting, payment, estimation, etc.

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45
Q

what is expense risk?

Marshall et al.

A

uncertainty associated with the cost of managing the run-off of the insurance liabilities or the cost of maintaining the unexpired risk until the date of loss

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46
Q

what is event risk?

Marshall et al.

A

uncertainty associated with claim costs arising from events (e.g. cats), either natural or man-made

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47
Q

what is latent claim risk?

Marshall et al.

A

uncertainty associated with claims that arise from sources that are not currently covered (e.g. asbestos)

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48
Q

what is recovery risk?

Marshall et al.

A

uncertainty associated with recoveries, either reinsurance or non-reinsurance

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49
Q

how do the valuation actuary and business unit management interact in the risk margin analysis?

(Marshall et al.)

A
  • normally used to discuss all aspects of the portfolio management process
  • discuss potential external systemic risks that may impact portfolio to inform both central estimate valuation AND identification and quantification of external systemic risk
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50
Q

what risk category accounts for most of the uncertainty in property classes?

(Marshall et al.)

A

event risk dominates volatility of premium liabilities

51
Q

what risk category accounts for most of the uncertainty in long-tailed classes?

(Marshall et al.)

A

legislative, political and claim inflation dominate the volatility of both outstanding claim liabilities and premium liabilities

52
Q

what are disadvantages of quantitative methods used to assess correlation effects?

(Marshall et al.)

A
  • very complex
  • require large amounts of data
  • heavily influenced by past correlations (problem for external risk that future may differ from past)
  • difficult to separate past correlation effects between independent risk and systemic risk OR to identify pure effect of each past systemic risk
  • internal systemic risk cannot be modeled using standard correlation modeling techniques
53
Q

how can we consider correlation effects for independent risk?

(Marshall et al.)

A

assume ind’t risk to be uncorrelated with any other source of uncertainty, either within a particular valuation class or between classes

54
Q

how can we consider correlation effects for internal systemic risk?

(Marshall et al.)

A
  • assumed to be uncorrelated with ind’t risk and with each source of external systemic risk
  • tends to be correlated between valuation classes AND between OCLs and PLs
55
Q

how can we consider correlation effects for external systemic risk?

(Marshall et al.)

A
  • reasonable to assume each risk category is uncorrelated with ind’t risk and internal systemic risk
  • correlation may exist between risks that belong to similar external risk categories -> must aggregate to broader, uncorrelated categories
56
Q

what are the five correlation bands names and thresholds?

Marshall et al.

A
  • Nil = 0%
  • Low = 25%
  • Medium = 50%
  • High = 75%
  • Full = 100%
57
Q

how does the normal distribution represent risk margins for insurance liabilities?

(Marshall et al.)

A

-produces higher risk margin at lower probabilities of adequacy, irrespective of the size of the consolidated CoV

58
Q

how does the lognormal distribution represent risk margins for insurance liabilities?

(Marshall et al.)

A
  • produces higher risk margin at higher probabilities of adequacy as long as consolidated CoV is not too high
  • extremely high CoVs can cause risk margin to reduce as a percentage of the CoV
59
Q

how can actuaries sensitivity-test the final risk margins?

Marshall et al.

A

vary the key assumptions and measure the impacts

60
Q

what key assumptions should be sensitivity-tested?

Marshall et al.

A

-CoVs and correlation coefficients assumed for independent risk, internal systemic risk, and each external systemic risk category

61
Q

what happens to our central estimate after including the risk margin?

(Marshall et al.)

A

our provision for a particular insurance liability will be larger than its central estimate

62
Q

how would we scenario test changing key assumptions to produce a central estimate at the level of our risk-margin inclusive provision for insurance liabilities?

(Marshall et al.)

A
  • valuation outcomes (e.g. claim frequencies, claim severities, loss ratios, etc.) can be compared against the central estimate for various assumption scenarios
  • can consider the risk margin inclusive valuation outcomes as well as changes required to produce these outcomes in the context of emerging experience
63
Q

what internal checks should proposed CoVs be subjected to?

Marshall et al.

A
  • for each source of uncertainty, CoVs should be compared between valuation classes for OCLs, PLs and total insurance liabilities
  • comparison should be made between OCLs and PLs within classes as well
64
Q

for indepedent risk, what two main dimensions should internal benchmarking be done for?

(Marshall et al.)

A
  • portfolio size (larger portfolio -> lower volatility arising from random effects)
  • length of claim run-off (longer run-off, more time for random effects to impact)
65
Q

how should OCL CoVs vary by short vs. long-tail portfolios?

Marshall et al.

A
  • OCL CoVs for short-tail portfolios should be lower than similarly-sized long-tailed portfolios
  • OCL CoVs for short-tailed portfolios should be substantially lower than smaller long-tailed portfolios
66
Q

how should CoVs vary by PL vs. OCL for long-tailed lines?

Marshall et al.

A
  • PL CoVs for long-tailed portfolios should be higher than OCL CoVs for same portfolios due to law of large numbers
  • PLs for long-tailed lines will be smaller, resulting in more volatility
  • larger difference for small portfolios (with higher ind’t risk components) than for large portfolios (smaller ind’t risk components)
67
Q

how should CoVs vary for PL vs. OCL for short-tail portfolios?

(Marshall et al.)

A
  • PL CoVs for short-tailed should be lower than OCL CoVs for same portfolios due to law of large numbers
  • PLs for short-tailed lined will be larger since most of the OCLs will have already closed -> less volatility for PLs
68
Q

for internal systemic risk, how can the CoVs be compared?

Marshall et al.

A

compare in the context of each valuation class:

  • classes with homogeneous claim groups should have similar CoVs
  • long-tailed portfolios should have higher CoVs than short-tailed portfolios (more complicated)
69
Q

for external systemic risk, how should CoVs vary by long vs. short-tail, and what are two exceptions?

(Marshall et al.)

A
  • long-tailed portfolios should have higher CoVs than short-tailed portfolios
  • exceptions: event risk and liability risk for home classes
70
Q

when is external benchmarking most beneficial?

Marshall et al.

A

when little information is available for analytics

71
Q

how should (and shouldn’t) external benchmarking be used?

Marshall et al.

A
  • primarily used as a reasonability check

- should NOT form basis of risk margin analysis

72
Q

what must be considered when using external benchmarks?

Marshall et al.

A

-differences between benchmark portfolios and claims portfolios being analyzed

73
Q

what does a hindsight analysis do?

Marshall et al.

A

compares past estimates of OCL’s and PL’s against the latest view of the equivalent liabilities

74
Q

how does a hindsight analysis treat any movement/variation in past estimates of OCL/PL’s vs. latest view of liabilities?

(Marshall et al.)

A

-convert to a coefficient of variation reflecting actual past volatility -> this volatility is combination of ind’t risk, internal systemic risk, and external systemic risk

75
Q

when is hindsight analysis more useful?

Marshall et al.

A

for short-tailed portfolios where serial correlation between consecutive valuations is less significant

76
Q

why should hindsight analyses be interpreted carefully?

Marshall et al.

A
  • models may have improved since previous valuations
  • future external sources of systemic risk may be significantly different from past episodes (which could make it appear as though estimates were off)
77
Q

what does mechanical hindsight analysis do?

Marshall et al.

A

applies a mechanical approach to estimating the OCL’s and PL’s by systematically removing the most recent claims experience

78
Q

what types of risk can mechanical hindsight analysis be used to analyze?

(Marshall et al.)

A
  • independent risk
  • internal systemic risk
  • all past sources of uncertainty
79
Q

by focusing on what, can mechanical hindsight analysis be used to analyze independent risk?

(Marshall et al.)

A

by focusing on periods with stable experience

80
Q

by focusing on what, can we use mechanical hindsight analysis to analyze internal systemic risk?

(Marshall et al.)

A

by applying the technique using a number of actuarial methods and observing the differences in volatility

81
Q

by focusing on what, can we use mechanical hindsight analysis to analyze all past sources of uncertainty?

(Marshall et al.)

A

by applying the approach across all past periods

82
Q

what do current documentation practices of risk margin analysis range from and to?

(Marshall et al.)

A

from a thorough discussion of all assumptions underlying the risk margin analysis to no discussion at all

83
Q

at least how often should a full application of the risk margin analysis framework be applied?

(Marshall et al.)

A

every three years

84
Q

when central estimate valuations are conducted, what key assumptions of risk margin analysis should be reviewed?

(Marshall et al.)

A
  • any emerging trends
  • emerging systemic risks
  • changes to valuation methodologies
85
Q

when a model is fit to past systemic episodes and trends, what should residual volatility exclusively reflect?

(Marshall et al.)

A

random effects ONLY (i.e. the independent risk)

86
Q

what factors does the choice of statistical method depend on?

(Marshall et al.)

A
  • valuation class being assessed
  • materiality of ind’t risk for that class relative to overall claims portfolio risk margin
  • cost and effort associated with applying the method
87
Q

why is a GLM a good choice for analyzing ind’t risk for OCLs?

(Marshall et al.)

A

-GLM is used for reserving purposes to identify the key factors that have contributed to past claim costs

88
Q

what statistical methods can be used to support the analysis of premium liabilities’ independent risk?

(Marshall et al.)

A
  • bootstrapping
  • GLM
  • Bayesian
89
Q

what is a simpler approach than statistical methods for assessing independent risk for premium liabilities?

(Marshall et al.)

A
  • assume: valuation class where central estimate of claim cost component of PL is calculated by combining projected claim F and average claim size
  • for both claim F and avg. claim size, past systemic episodes (ex: seasonality, inflation) can be removed
  • CoV can be derived for residual volatility
90
Q

why is an objective assessment of the model infrastructure and its ability to reflect/predict the insurance process important?

(Marshall et al.)

A

models represent a simplified view of the insurance process

91
Q

what approach is used to assess internal systemic risk?

Marshall et al.

A

balanced scorecard approach

92
Q

how does the balanced scorecard approach work for internal systemic risk?

(Marshall et al.)

A
  • for specification, parameter, data risk components -> qualitative assessment of modeling infrastructure is completed
  • risk indicators are weighted together to develop an overall score for each valuation class
  • scores are mapped to a CoV
93
Q

what is the qualitative assessment of modeling infrastructure used in the balanced scorecard approach to assessing internal systemic risk?

(Marshall et al.)

A
  • identifying risk indicators for each risk component

- score on scale of 1 to 5 (5 represents best practice)

94
Q

what does the risk indicator weight reflect in the balanced scorecard approach?

(Marshall et al.)

A

-reflects each risk indicator’s importance to the modeling infrastructure

95
Q

what additional risk indicators might be required for PL’s?

Marshall et al.

A

-whether OCL’s are used as an input
-whether credible portfolio level pricing analysis is used as an input
(both would drive risk score up and CoV down)

96
Q

what is an example of a risk indicator that may be less relevant for short-tail portfolios in PL assessment?

(Marshall et al.)

A

-large variance in OCLs may only affect the most recent accident periods and have a small impact on projected claim frequencies and avg. claim sizes

97
Q

how can actuaries get an idea for the amount of potential variability (range of CoV) associated with a particular modeling approach?

(Marshall et al.)

A

analyzing both the scoring approach AND past model performance, combined with judgment

98
Q

what is the minimum CoV suggested, and why?

Marshall et al.

A

5% because no model can perfectly replicate the insurance process

99
Q

why aren’t CoV scales linear?

Marshall et al.

A

marginal improvement in outcomes between fair and good modeling approaches is less than the marginal improvement between poor and fair modeling approaches

100
Q

for internal systemic risk, why are CoVs for long-tailed portfolios higher than those for short-tail portfolios?

(Marshall et al.)

A

it’s more difficult to model insurance process underlying long-tailed portfolios
-key predictors are less stable for long-tailed portfolios

101
Q

how can communication with business experts help with evaluating external systemic risk?

(Marshall et al.)

A
  • portfolio and claim management can provide insights into emerging trends and future sources of external systemic risk
  • tailored to important topics for both central estimate and risk margin purposes
102
Q

what six categories should discussions with business experts about external systemic risk consider?

(Marshall et al.)

A
  • underwriting and risk selection
  • pricing
  • claims management
  • expense management
  • emerging portfolio trends
  • environment in which the portfolio operates
103
Q

what is an example of a risk category that is more relevant for higher probabilities of adequacy?

(Marshall et al.)

A

-probability of an emerging latent risk is extremely low -> would not have a material impact on a 75th percentile risk margin

104
Q

how can one identify key risks?

Marshall et al.

A
  • scoring system can be used to rank individual risk categories for each valuation class in order of importance
  • risk categories that show up as important for a number of classes are key risks
105
Q

what are four examples of economic and social risks?

Marshall et al.

A
  • levels of standard inflation (AWE and CPI)
  • general economic conditions
  • fuel prices
  • driving patterns
106
Q

what general economic conditions constitute as economic and social risks? (3)

(Marshall et al.)

A
  • unemployment rates
  • GDP growth
  • interest rates
107
Q

what is an example of an economic/social risk that is less relevant for auto OCLs than auto PLs?

(Marshall et al.)

A

uncertainty around driving conditions

108
Q

how does uncertainty around AWE (average weekly earnings) impact some classes more than others?

(Marshall et al.)

A

tends to be greater for long-tailed classes

109
Q

for what type of claims are legislative, political, and claims inflation risks more material, and how are the risks treated?

(Marshall et al.)

A
  • long-tailed classes

- risks are aggregated and referred to as superimposed inflation

110
Q

for long-tailed classes, what are four examples of risks within the legislative, political, and claims inflation risk category?

(Marshall et al.)

A
  • precedent setting in courts
  • changes in medical costs
  • changes in legal costs
  • systemic shifts in large claim frequency or severity
111
Q

for short-tailed risk, what is an example of a risk within the legislative, political, and claims inflation risk category?

(Marshall et al.)

A

risk that claim inflation will increase at a level different from that used for central estimate purposes

112
Q

how can discussions with claim managers help to analyze claim management process change risk?

(Marshall et al.)

A
  • help identify current or future changes to process
  • identify past systemic episodes impacted by claim management process & process changes contributing to those episodes
  • consider reporting patterns, payment patterns, reopening rates, etc.
113
Q

is claim management process risk typically more relevant for OCLs or PLs, and why?

(Marshall et al.)

A
  • OCL
  • for example, OCLs for short-tailed classes are materially impacted because this risk impacts the emergence pattern for credible claim estimates
114
Q

why should an actuary spend time with product and claim management to consider expense risk?

(Marshall et al.)

A
  • to understand key drivers of policy maintenance and claim handling expenses
  • allows actuary to identify key sources of variation relative to central estimate assumptions
  • help identify past systemic episodes
115
Q

what does event risk relate to?

Marshall et al.

A

single events that cause a large number of claims

116
Q

for event risk for OCLs, what should the focus of discussions with claim management be on?

(Marshall et al.)

A
  • focus on material outstanding events
  • set expectations on final claim cost outcomes
  • range of dev. patterns on past events may influence view on uncertainty
117
Q

for event risk for PLs, what can be used to quantify event risk?

(Marshall et al.)

A
  • past experience for event claims
  • output from proprietary cat models
  • output from models for perils not covered by cat models
118
Q

when analyzing past experience to help quantify PL event risk, what are four examples of parameters we should allow for changes in?

(Marshall et al.)

A
  • portfolio size
  • geographical spread
  • inflation
  • reinsurance arrangements
119
Q

for what classes can latent claim risk be material?

Marshall et al.

A

workers compensation and liability classes

120
Q

why is latent claim risk difficult to quantify?

Marshall et al.

A

it has extremely low frequency and extremely high severity

121
Q

what is an example of where recovery risk may be significant?

(Marshall et al.)

A

subrogation for auto insurance

122
Q

when assessing recovery risk, what is the goal?

Marshall et al.

A

identify systemic events that may lead to different recovery outcomes than those used for central estimate purposes

123
Q

for non-reinsurance recoveries, how can a range of reasonable outcomes about recovery risk be developed?

(Marshall et al.)

A

by analyzing past experience and talking to claim management about current/future trends in recovery levels

124
Q

for reinsurance recoveries, how can a range of reasonable outcomes about recovery risk be formed?

(Marshall et al.)

A
  • determining how shifts in reinsurance market conditions (such as catastrophes) impact the ability of the reinsurer to pay
  • discussions with reinsurance management to help identify possible scenarios and quantify impact

exam 7 (21 decks)

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