Captives
and Solvency ii
Captive
Insurance and Captive Reinsurance Companies after the Solvency ii
Directive
from the Solvency ii
Association, the largest Association of Solvency ii Professionals
in the world
PROPORTIONALITY - LEVEL 2
MEASURES
CEIOPS-CP-45/09, 2 July 2009,
Consultation Paper No. 45
Draft CEIOPS’
Advice for Level 2 Implementing Measures on Solvency II: Technical
Provisions – Article 85 h, Simplified
methods and techniques to calculate technical
provisions
3.1.2
Proportionality assessment – a three step process
3.24 Whereas the ultimate
aim of calculating technical provisions is to assign an appropriate valuation to the underlying
insurance obligations, it would not be appropriate to reduce this
valuation as only providing a single number.
Instead, it is important
that consideration is given to the different stages of the valuation
process.
These stages
would generally include data, analysis, modelling an
validation:
3.25 The assessment of proportionality of the selected
valuation methodology to the nature, scale and complexity of the
underlying risks is an integral part of this
process.
3.26 It would be appropriate
for such an assessment to include the following
three steps:
• Step
1: Assess nature, scale and complexity of underlying
risks
• Step 2:
Check whether valuation methodology is proportionate to risks as
assessed in step 1, having regard to the degree of model error
resulting from its application
• Step 3:
Back test and validate the assessment carried out in steps 1 and
2
Below, these steps are
discussed in more detail.
3.27 Rather than proposing
a prescriptive rule, the outlined process is intended to set out
general expectations on (re)insurance undertakings and supervisors
as to how proportionality should be applied when selecting a
valuation methodology.
It is important that a flexible and principle-based framework is
maintained to allow undertakings to follow an
approach
which is appropriate with regard to their specific
circumstances and risk profile.
Relation to
undertaking’s internal governance and to supervisory
review
3.28 We note that it is
the responsibility of the (re)insurance undertaking to choose an
adequate and reliable calculation of the technical
provisions.
Whereas this
responsibility ultimately lies with the administrative or management
body of the undertaking, the actuarial function
plays an important role in coordinating the valuation of technical
provisions and in providing regular reports to the management
body on its mandatory tasks performed.
3.29 An assessment of the proportionality of the chosen
valuation methodology vis-à-vis the nature, scale and complexity of
the underlying risks (as described in this sub-section) should be
seen as part of this process, which is part of the
(re)insurance undertakings’ internal system of
governance.
3.30 Information on the
methodology chosen by the undertaking (including
an assessment of proportionality) would also be important for the
supervisory review of the undertaking’s compliance with the
valuation requirements.
In this context, there
should be an open dialogue between the undertaking and the
supervisor about the adequacy of the methods and their potential
weaknesses.
3.31 For the discussion
between undertaking and supervisor, objective quantitative figures
or metrics might be helpful.
However, these figures should
be a natural result of the usual actuarial work
and should not be applied as rigid thresholds but be seen as a basis
for discussion.
3.1.2.1 Step 1:
Assess nature, scale and complexity of risks
3.32 In this step, the
(re)insurance undertaking should assess the nature, scale and
complexity of the risks underlying the insurance obligations.
This is intended to provide a
basis for checking the appropriateness of specific valuation methods
carried out in step two and shall serve as a guide to identify where
simplified methods are likely to be
appropriate.
3.33 In elaborating on
this assessment, this sub-section analyses:
• The
scope of risks to be considered;
• The
interpretation of the three indicators “nature”, “scale” and
“complexity”; and
• The
combination of the three indicators in an overall
assessment.
Which
risks?
3.34 For an assessment of nature, scale and complexity it
is important to clarify the scope of
risks which shall be included in the analysis.
We note that this scope will
depend on the purpose and context of the assessment.
3.35
For the purpose of calculating technical
provisions, the assessment should include
all risks which materially affect (directly or indirectly)
the amount or
timing of cash flows required to settle the insurance and reinsurance obligations
arising from the insurance contracts in the portfolio to bevalued.
Whereas this will generally
include all insured risks, it may also
include others
such as inflation.
3.36 Hence where an
(re)insurance undertaking assess the nature, scale and complexity of
the risks – and subsequently considers whether a
specific valuation method is proportionate to these risks -
it should only have regard to the risk characteristics of the
cash-flows related to settling the insurance contracts but not to
other risks to which the undertaking may be exposed.
Following such an approach is
expected to improve the comparability and consistency of such
assessments across
different
undertakings.
Nature and
complexity
3.37 Nature and complexity of
risks are closely related, and for the purposes of an
assessment of proportionality could best be characterised
together.
Indeed, complexity could be seen as an integral part of the
nature of risks, which is a broader
concept
3.38 In mathematical
terms, the nature of the risks underlying the insurance contracts
could be described by the probability distribution of the future
cash flows arising from the contracts.
This encompasses the following
characteristics:
• The
degree of homogeneity of the risks;
• The
variety of different sub-risks or risk components of which the risk
is comprised;
• The way in
which these sub-risks are interrelated with one
another;
• The level
of certainty i.e. the extent to which future cash flows can be
predicted;
[Note that this only refers to the randomness (volatility) of the
future cash flows.
Uncertainty which is related
to the measurement of the risk (model error and parameter error) is
not an intrinsic property of
the risk, but dependent on the
valuation methodology applied, and will be considered in step 2 of
the proportionality assessment process.]
• The nature
of the occurrence or crystallisation of the risk in terms of
frequency and severity;
• The type
of the development of claims payments over time;
or
• The extent
of potential policyholder loss, especially in the tail of the claims
distribution.
3.39 The first three
bullet points in the previous paragraph are in particularrelated to
the complexity of risks generated by the
contracts, which in general terms can be described as the quality of
being intricate (i.e. of being “entwined” in such a way that it is
difficult to separate them) and compounded (i.e. comprising a number
of different sub-risks orcharacteristics).
3.40 For example,
in non-life insurance travel insurance
business typically has relatively stable
and narrow ranges for expected future claims, so would tend to be
rather predictable.
In contrast, credit insurance
business would often be “fat tailed”, i.e. there would be the risk
of occasional large(outlier) losses occurring, leading to a higher
degree of complexity and uncertainty of the risks.
Another example in non-life
insurance is catastrophe (re)insurance covering
losses from hurricanes where there is
very considerable
uncertainty over expected losses, i.e. how many hurricanes occur,
how severe they are and whether they hit heavily insured
areas.
3.41 In life insurance,
the nature and complexity of the risks would for example be impacted
by the financial options and guarantees embedded into the contracts
(such as surrender or other take-up options), particularly those
with profit sharing features.
3.42 When assessing the nature and complexity of the
insured risks, additional information in relation to the
circumstances of the particular portfolio should be taken into
account.
This could
include:
• The
type of business from which the risks originate (e.g. direct
business or reinsurance business);
• The degree
of correlation between different risk types, especially in the tail
of the risk distribution; and
• Any risk
mitigation instruments (such as reinsurance or derivatives) applied,
and their impact on the underlying risk
profile.
3.43 The undertaking
should also seek to identify factors
which would indicate the presence of more
complex and/or less predictable risks.
This would be the case, for
example, where:
• The
cash-flows are highly path dependent;
or
• There are
significant non-linear inter-dependencies between several drivers of
uncertainty; or
• The
cash-flows are materially affected by the potential future
management actions; or
• Risks have
a significant asymmetric impact on the value of the cashflows, in
particular if contracts include material embedded options and
guarantees or if there are complex reinsurance contracts in place;
or
• The value
of options and guarantees is affected by the policyholder behaviour
assumed in the model; or
• The
undertaking uses a complex risk mitigation instrument, for example a
complex non-proportional reinsurance structure;
or
• A variety of
covers of different nature is bundled in the contracts;
or
• The terms
of the contracts are complex (e.g. in terms of franchises,
participations, or the in- and exclusion criteria of
cover).
3.44 The degree of
complexity and/or uncertainty of the risks is associated with the
level of calculation sophistication and / or level of expertise
needed to carry out the valuation.
In general, the more complex
the risk, the more difficult it will be to model and predict the future cash
flows required to
settle the obligations arising from the insured
portfolio.
For example, where losses are
the result of interaction of a number of different factors, the
degree of complexity of the modelling would be expected to also
increase.
3.45 Therefore, to
appropriately analyse and quantify more complex
and/or less predictable risks, more sophisticated and
elaborated tools will generally be required as well as sufficient
actuarial expertise.
Scale
3.46 Assigning a scale
introduces a distinction between “small” and
“large” risks.
The undertaking may use a
measurement of scale to identify (sub-) risks where the use of
simplified methods would likely to be appropriate, provided this is
also commensurate with the nature and complexity of the
risks.
3.47 For example, where
the undertaking assesses that the impact of
inflation risk on the overall risk profile of the portfolio
is small, it may consider that an explicit recognition of inflation
scenarios would not be necessary.
A scale criterion may also be
used, for example, where the portfolio to be measured is segmented
into different sub-portfolios.
In such a case, the relative
scale of the individual sub-portfolios in relation to the overall
portfolio could be considered.
3.48 Related to this,
a measurement of scale may also be used to
introduce a distinction between material and non-material
risks.
Introducing materiality in this context would
provide a threshold or cut-off point below which it would be
regarded as justifiable to omit (or not explicitly recognise)
certain
risks.
3.49 Different
interpretations of “scale” may be applied when considering risks,
depending on the type of assessment to be made.
For example, the undertaking
may interpret the scale of a risk as the degree
to which the undertaking is vulnerable to the risk.
Following this option, in
assessing the scale of a risk one should consider both the likelihood
of the risk being realised and the impact of that risk when
realised.
The scale of the risk would
increase as either the likelihood or the (potential) impact of the
risk increases:
Scale = vulnerability to risk = likelihood x
impact
3.50 Related to this, the
scale of a risk may be defined in terms
of the SCR, so that it would relate to the vulnerability of the
undertaking under a “worst case” scenario:
Scale = SCR = vulnerability to risk under
“worst case” scenario
3.51 Such interpretations
of “scale” would seem adequate for the
determination of regulatory capital requirements, which are
intended to define the amount of capital resources which the
undertaking needs to be protected against the realisation of the
risk.
However, they may be less suitable in the context of a
valuation of technical provisions which is in the focus of this
paper.
3.52 Here, a more natural approach would be to measure the scale
of the risk in terms of the best estimate of the underlying
obligations:
Scale = size of best
estimate
3.53 To measure the scale
of risks, further than introducing an absolute quantification of the
risks the undertaking will also need to establish a benchmark or reference volume which leads to a
relative rather than an absolute assessment.
In this way, risks may be
considered “small” or “large” relative to the
established benchmark.
Such a benchmark may be
defined, for example, in terms of a volume measure such as premiums
or technical provisions that serves as an approximation for the risk
exposure.
3.54 For the examples
described above, introducing a benchmark volume would lead to the
following relative assessments of scale:
Scale = (relative) size of best
estimate
Scale =
likelihood x (relative) impact
Scale = SCR
/ volume measure
3.55 To illustrate this,
suppose that in a line of business (LOB) a portfolio of contracts is
given with overall “smooth” risk characteristics, but with some
single mass claims.
Then the undertaking may
decide to measure the “scale” of risks in terms of the size of the
best estimate, establishing as a
benchmark the best estimate for
the overall portfolio in the LOB.
On this basis, the undertaking would consider the risks generated by
the mass claims as “small” or “large” depending on whether the best
estimate relating to these mass claims would be small or large
compared to the best estimate for the overall
portfolio.
3.56 To determine an
appropriate benchmark for a relative measurement of scale, it is
important to specify at which level the assessment is carried out: a
risk which is small with regard to the business of the undertaking
as a whole may still have a significant impact within a smaller
segment, e.g. a certain line of business.
For the calculation of
technical provisions, Article 70 of the Level 1 text stipulates in
this regard that the starting point for this valuation is defined by
the level of homogeneous risk group (HRG).
However, other levels are also
relevant; for example, the calculation of the
standard formula SCR necessitates a specification of the value of
technical provisions per LOB.
3.57 All in all, the
following four different levels may usefully be distinguished
in the context of a calculation of technical
provisions:
• Te
individual homogeneous risk group
(HRG);
• The
individual line of business (LOB);
• The
business of the undertaking as a whole and
• The
group to which the undertaking belongs.
3.58 Depending
on the purpose and context of the valuation, the
benchmark established to measure “scale” should relate to one of
these four levels.
For example, where it is the purpose to calculate the technical
provision for a given LOB, the benchmark should relate to
same level (e.g. in terms of the size of the overall best estimate
in the LOB).
3.59 In particular, where
the calculation of technical provisions is carried out in the context of a solo assessment, it would not be
appropriate to consider a group-related
benchmark.
3.60 Considering the
various options to define “scale” as described above, we note that
it would not seem feasible to define a universal metric for “scale”
that will apply in all cases.
Considering this, specifying
the content and structure of a “scale” criterion in Level 2 would be
considered to be excessive.
This does not preclude the
possibility to set up additional criteria and/or guidance (on Level
2 or 3, respectively) concerning the
definition and application
of “scale” to support the principles-based proportionality
assessment framework outlined in this
sub-section.
3.61 Following this principles-based framework, (re)insurance
undertakings would be expected to use an
interpretation of scale which is best suited to their specific
circumstances and to the risk profile of their
portfolio.
Whatever interpretation of
“scale” for risks or obligations is followed, this should lead to an
objective and reliable assessment.
Combination of
the three indicators and overall assessment
3.62 It can be concluded from
the discussions above that the three indicators
- nature, scale and complexity - are strongly interrelated,
and in assessing the risks the focus should be on the combination of all three factors.
This
overall assessment of proportionality would ideally be more
qualitative than quantitative, and cannot be reduced to a
simple formulaic aggregation of isolated assessments of each of the
indicators.
3.63 In terms of nature
and complexity, the assessment should seek to identify the main qualities and characteristics
of the risks, and should lead to an evaluation
of the degree of their complexity and
predictability.
In combination with the
“scale” criterion, the undertaking may use such an assessment as a
“filter” to decide whether the use of simplified methods would be
likely to be appropriate.
For this purpose, it may be helpful to broadly categorise the risks
according to the two dimensions “scale” and
“complexity/predictability”:
3.64 An assessment of nature,
scale and complexity may thus provide a useful basis for the second
step of the proportionality process where it is decided whether a
specific valuation methodology would be proportionate to the
underlying risks.
3.1.2.2 Step 2:
Quantitative assessment of the model error
3.65 The second step of
the proportionality assessment process concerns the assessment whether a specific valuation methodology can be
regarded as proportionate to the nature, scale and complexity of the
risks as analysed in the first step.
3.66 To carry out this
assessment, the undertaking has to analyse whether the valuation
methodology in question takes into account the properties and
characteristics of risks identified in the first step in a
proportionate way, and also has due regard to the scale of the
risks.
3.67 Ultimately, when a
decision needs to be taken whether a given
valuation methodology can be regarded as proportionate, the
supervisory objective underlying the valuation requirements would
need to be considered.
3.68 For the best estimate, this means that a given
valuation technique should be seen as proportionate if the resulting
estimate is not expected to diverge materially from the
“true” best estimate which is given by the mean of the underlying
risk distribution, i.e. if the model error implied by the
measurement is immaterial.
More generally, a given
valuation technique for the technical provision should be regarded
as proportionate if the resulting estimate is
not expected to diverge materially from the current transfer
value specified in the Level 1 text.
3.69 Where in the
valuation process several valuation methods turn out to be
proportionate, the undertaking should generally apply the method which is likely to include the smallest
degree of model error.
3.70 Introducing materiality in this context would serve as
a threshold below which it would be regarded as justifiable to
potentially misstate (i.e. measure incorrectly) the risks in the
valuation of technical provisions.
3.71 In the following,
this second step of the proportionality assessment process is
explored further, considering:
• How
materiality should be interpreted in this
context;
• How an
assessment of the estimation uncertainty in the valuation may be
carried out in practice; and
• Which
approach can be taken in cases where – e.g. due to a lack of data –
it is unavoidable for the undertaking to apply a valuation method
which leads to an increased level of estimation uncertainty in the
valuation.
Materiality in
the context of a valuation of technical
provisions
3.72 In order to clarify the meaning of materiality for both
undertakings and supervisors, CEIOPS proposes using as a reference
the definition of materiality used in International Accounting Standards (IAS) as
CEIOPS considers that by using this definition undertakings should
be familiar with this concept.
This definition states
that:
“Information is material if its omission or
misstatement could influence the economic decisions of users taken
on the basis of the financial statements. Materiality depends on the
size of the item or error judged in the particular circumstances of
its omission or misstatement. Thus, materiality provides a threshold
or cut-off point rather than being a primary
qualitative
characteristic which information must have if it is
to be useful”.
3.73 In the context of a
valuation of technical provisions, this means that a misstatement of
the technical provision is material if it could influence the decision-making
or judgment of
the intended user of the information contained in the
valuation.
3.74 In its calculation of
technical provisions, the (re)insurance undertaking should address
materiality consistent with the principle set out in the above.
For this purpose the
undertaking should define a concept on materiality which should lay
down the criteria on basis of which a decision on the materiality of
a potential misstatement of technical provisions is
made.
3.75 This materiality
concept should be consistent with the
undertaking’s approach to materiality in other areas of solvency
assessment and reporting, and should be reflected in the
undertaking’s own risk and solvency assessment
(ORSA).
3.76 When determining how
to address materiality, the undertaking should have regard to the
purpose of the work and its intended users.
For a valuation of technical
provisions – and more generally for a qualitative or quantitative
assessment of risk for solvency purposes – this should include the
supervisory authority which uses the information when performing the
SRP.
Assessment of
the estimation uncertainty in the valuation
3.77 Regardless of what
methods shall be applied for the valuation of technical provisions,
it is important that an assessment of their appropriateness should
in general include an assessment of the model
error implicit to the calculations.
3.78 Such an assessment
may be carried out, for example, by:
• Sensitivity analysis in the framework of the
applied model: this means to vary the parameters and/or the data
thereby observing the range where a best estimate might be
located.
• Comparison with the results of other methods:
applying different methods gives insight in potential model errors.
These methods would not
necessarily need to be more complex.
• Descriptive statistics: in some cases the
applied model allows the derivation of descriptive statistics on the
estimation error contained in the
estimation.
Such information may assist in
quantitatively describing the sources of
uncertainty.
• Back-testing: comparing the results of the
estimation against experience may help to identify systemic
deviations which are due to deficiencies in the
modelling.
3.79 In conducting such an
assessment, the undertaking should consider the
level and the implications of the uncertainty related to the
application of the valuation technique and be able to qualitatively
describe the key risks and main sources of uncertainty in the
valuation.
Such consideration should be
based on the assessment of the nature, scale and
complexity of the risks carried out in Step 1 of the
proportionality assessment process.
In particular, where as a
result of this first step of the proportionality assessment the
undertaking has identified certain
factors that indicate an increased level of complexity and/or
unpredictability of the risks, the techniques described above should
be used to assist the undertaking in quantitatively describing these
sources of uncertainty and in deciding whether the valuation
technique considered would be appropriate to address the underlying
risks.
3.80 We note that in practice an assessment of the model error will not
be easy.
This is not only a problem for
the simplified methods but for all methods.
A precise determination of the
model error will generally not be possible, neither for simplified methods nor for more
complex so called best practice
techniques.
Applying assessment techniques
as described below may also lead to additional implementation costs
for (re)insurance
undertakings.
3.81 Therefore the undertaking
should not be required to quantify the degree of
model error in precise quantitative terms, or to re-calculate the value of its technical provisions
using a more accurate method in order to demonstrate that the
difference between the result of the chosen method and the result of
a more accurate method is immaterial.
Instead, it would be
sufficient for the undertaking to demonstrate that there is reasonable assurance that the model
error implied by the application of the chosen method (and hence the
difference between those two amounts) is
immaterial.
Approach in
cases where model error is expected to be
material
3.82 Where the intended
use of a valuation technique is expected to lead
to a material degree of model error, the undertaking should
consider which alternative techniques would be
available to him.
Where practicable, another
more appropriate valuation method should be
applied.
3.83 In some circumstances, however, it may be unavoidable
for the undertaking to apply a valuation method which leads to an
increased level of estimation uncertainty in the valuation.
This would be the case where
the undertaking, to carry out the valuation, would need to make assumptions which are uncertain or
conjectural and which cannot be fully validated.
For example, this could be the
case where there are deficiencies in the data, so that there is only
insufficient pertinent past experience data available to derive or
validate assumptions.
3.84 Under these circumstances, it would be acceptable for
the undertaking to determine the best estimate of the technical
provision applying a technique which carries an increased level of
estimation uncertainty or model error.
The undertaking should document
that this is the case and consider the implications of the increased level
of uncertainty with regard to the reliability of the valuation and
its overall solvency position.
3.85 Moreover, the
increased level of estimation uncertainty will need to be reflected in the calculation of the overall solvency
position of the undertaking, particularly through the
determination of the SCR and the setting of the risk margin in the
technical provision.
3.86 However, where the undertaking uses the standard formula to
calculate the SCR, it may not be practicable to reflect the
increased estimation uncertainty in the best estimate valuation
through an increased SCR.
This is the case since the
input parameters of the standard formula (such as, in the example of
non-life underwriting risk, the best estimate of technical
provisions) would not necessarily change depending on the degree of
model error in the calculation.
3.87 In such a case,
it may be necessary to set a capital add-on to the standard formula
SCR to reflect the increased estimation uncertainty.
Alternatively, it may be more
practicable for the undertaking in these cases to introduce a margin for increased estimation
uncertainty in the calculation of the best estimate itself. Such a
margin would lead to a certain degree of conservatism in the best
estimate valuation.
3.88 A margin for increased
estimation uncertainty may for example be expressed as the
difference between the assumptions used for the valuation and the
“best estimate” assumption.
To illustrate
this, suppose the undertaking expects a claims rate of 2% in its
portfolio, but is aware of a high degree of uncertainty in this
estimate. It may then, for the purposes of calculating the best
estimate, deliberately assume a higher
claims rate (say, 5 %),
leading to a margin of 3%.
3.89 A margin for
increased estimation uncertainty may also be expressed in more
simple terms, for example as a multiplier (for example, of 105%) to
the best estimate which would result without reflecting the
increased level of uncertainty.
3.90 Where the undertaking
introduces a margin for increased estimation uncertainty in the
valuation of the best estimate, this should be
documented and the undertaking should explain why he has
chosen such an approach.
3.1.2.3 Step 3:
Back testing
3.91 As part of the actuarial control cycle, it should
be checked whether the best estimates calculated
in past years turn out to be appropriate in subsequent years.
Such back testing is
considered to be part of the validation process (re)insurance undertakings
are expected to carry out
when calculating technical
provisions.
3.92
Where the back testing identifies systematic deviation between
experience and the best estimate calculations, the first two steps
of the proportionality process described above should be
re-performed to check whether in regard to nature, scale and
complexity it would still seem appropriate to use the chosen
valuation method.
3.93 Over time an
(re)insurance undertaking's business may change considerably, as a
result of internal factors or events (such as a change in
undertaking strategy) or due to external factors or events (such as
a change in market conditions), so that the previous assessment may
no longer fully capture the nature, scale and complexity of the
risks.
Hence such a check should also
be carried out in case where there is a significant change to the
undertaking’s risk profile.
3.94 If it is found that
the previously chosen method is no longer appropriate, the
undertaking should switch towards a more appropriate method which
captures the risk profile of the portfolio in a better way.
PROPORTIONALITY - LEVEL 2
MEASURES
CEIOPS-CP-45/09, 2 July 2009,
Consultation Paper No. 45
1.
Introduction
2.
Advice - Proportionality
3.
Proportionality Assessment – A three step process
4.
Simplified Methods
5.
Reinsurance Recoverables
6.
Annex A: Gross-to-net Techniques
New:
Solvency ii and Captives, CEIOPS Level 2 measures
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