Public

Application Paper on
Macroprudential Supervision

PublicApplication Paper on Macroprudential Supervision
Adopted by the Executive Committee on 27 August 2021

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About the IAISThe International Association of Insurance Supervisors (IAIS) is a voluntary membershiporganisation of insurance supervisors and regulators from more than 200 jurisdictions. The
mission of the IAIS is to promote effective and globally consistent supervision of theinsurance industry in order to develop and maintain fair, safe and stable insurance markets
for the benefit and protection of policyholders and to contribute to global financial stability.
Established in 1994, the IAIS is the international standard setting body responsible fordeveloping principles, standards and other supporting material for the supervision of theinsurance sector and assisting in their implementation. The IAIS also provides a forum forMembers to share their experiences and understanding of insurance supervision andinsurance markets.
The IAIS coordinates its work with other international financial policymakers andassociations of supervisors or regulators, and assists in shaping financial systems globally.
In particular, the IAIS is a member of the Financial Stability Board (FSB), member of theStandards Advisory Council of the International Accounting Standards Board (IASB), andpartner in the Access to Insurance Initiative (A2ii). In recognition of its collective expertise,
the IAIS also is routinely called upon by the G20 leaders and other international standard
setting bodies for input on insurance issues as well as on issues related to the regulationand supervision of the global financial sector.
Application Papers provide supporting material related to specific supervisory material(ICPs and/or ComFrame). Application Papers could be provided in circumstances where
the practical application of principles and standards may vary or where their interpretationand implementation may pose challenges. Application Papers do not include newrequirements, but provide further advice, illustrations, recommendations or examples ofgood practice to supervisors on how supervisory material may be implemented. The
proportionality principle applies also to the content of Application Papers.
International Association of Insurance Supervisors c/o Bank for International Settlements
CH-4002 Basel
Switzerland
Tel: +41 61 280 8090
Fax: +41 61 280 9151
www.iaisweb.org
This document was prepared by the Macroprudential Supervision Working Group in
consultation with IAIS members.
This document is available on the IAIS website (www.iaisweb.org).
© International Association of Insurance Supervisors (IAIS), 2021.
All rights reserved. Brief excerpts may be reproduced or translated provided the source isstated.

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Contents
List of Abbreviations .......................................................................................................... 51

2

3

Introduction .................................................................................................................. 6
1.1

Terminology ............................................................................................................ 7

1.2

Scope of application................................................................................................ 7

1.3

Proportionality ......................................................................................................... 7

1.4

Structure ................................................................................................................. 7

Data collection for macroprudential purposes ................................................................ 8
2.1

Consideration of data to collect ............................................................................... 8

2.2

Risk dashboard for monitoring key macroprudential indicators................................ 9

2.2.1

Constructing a risk dashboard ......................................................................... 9

2.2.2

The use of a risk dashboard........................................................................... 10

Insurance sector analysis............................................................................................. 11
3.1

Steps and approaches for insurance sector analysis ............................................ 11

3.2

Common quantitative analysis methods ................................................................ 13

3.2.1

Trend analysis ............................................................................................... 13

3.2.2

Stress testing ................................................................................................. 14

3.2.3

Sensitivity analysis ......................................................................................... 19

3.3

Common qualitative analysis methods .................................................................. 20

3.3.1
3.4

4

Market intelligence and risk workshop with stakeholders ............................... 20

Common quantitative and qualitative analysis methods ........................................ 20

3.4.1

Vulnerability analysis ..................................................................................... 20

3.4.2

Horizontal reviews ......................................................................................... 21

Assessing systemic importance ................................................................................... 22
4.1

Assessing systemic importance of an individual insurer ........................................ 23

4.1.1

Indicator-based approach .............................................................................. 23

4.1.2

Assessing systemic risk using the indicator-based approach ......................... 29

4.1.3

Reduced-form approach ................................................................................ 30

4.1.4

Comparison between indicator-based and reduced form identification ........... 33

4.2

Assessing systemic importance of the insurance sector ....................................... 34

4.2.1

Macroprudential sector-wide stress tests ....................................................... 35

4.2.2

Sector-wide systemic risk assessment ........................................................... 35

4.2.3

Evaluation of recovery and resolution plans ................................................... 36

4.2.4

Evaluation of the sector-wide exposure to systemically risky activities ........... 36

4.2.5

Cross-sectoral analysis .................................................................................. 36

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4.3
5

6

Interplay between the individual insurer and sector-wide levels ............................ 37

Supervisory response .................................................................................................. 37
5.1

Introduction ........................................................................................................... 37

5.2

Types of supervisory responses............................................................................ 39

5.2.1

Strengthening the ERM framework ................................................................ 39

5.2.2

Crisis management and planning ................................................................... 40

5.2.3

Preventive and corrective measures .............................................................. 40

Transparency ............................................................................................................... 41
6.1

Importance of transparency .................................................................................. 41

6.2

Possible macroprudential reporting ....................................................................... 42

6.2.1

Financial stability report (FSR) ....................................................................... 42

6.2.2

Other forms of macroprudential reporting....................................................... 43

Annex 1

Example indicators and data elements .............................................................. 44

Annex 2

Example risk dashboards .................................................................................. 48

South African Reserve Bank Heat Map ........................................................................... 48
EIOPA Risk Dashboard (RDB) ........................................................................................ 51
Annex 3

Example topics for analysis ............................................................................... 54

Annex 4

Example of ORSA analysis................................................................................ 57

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List of Abbreviations
CDS

Credit Default Swap

ComFrame

Common Framework for the Supervision of IAIGs

CQS

Credit Quality Steps

EBIT

Earnings Before Interest and Taxes

ERM

Enterprise Risk Management

ESAs

European Supervisory Authorities

ESRB

European Systemic Risk Board

FSB

Financial Stability Board

FSR

Financial Stability ReportGDP

Gross Domestic Product

GME

Global Monitoring Exercise

IAIG

Internationally Active Insurance Group

IAIS

International Association of Insurance Supervisors

ICP

Insurance Core Principle

IIM

Individual Insurer Monitoring

LOB

Lines of Business

LTGM

Long-Term Guarantee Measures

MES

Marginal Expected Shortfall

ORSA

Own Risk and Solvency Assessment

OSN

Overall Solvency Need

RDB

Risk Dashboard

SCR

Solvency Capital Requirement

VaR

Value at Risk

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1

Introduction

1.
Insurers provide financial and economic functions that support economic activity bycontributing to the flow of savings into investments and enabling risk transfer by assuming therisks of households and businesses in return for a premium. In essence, the core business ofan insurer is exposed to various types of inherent risks.
2.
Macroprudential supervision is aimed at identifying and, where necessary, addressing
both vulnerabilities of individual insurers and the insurance sector to shocks from the external
environment (inward risks) and the build-up of systemic risk at the individual insurer level orwithin the sector as a whole that may be transmitted to the external environment (outward
risks).
3.
This Application Paper on Macroprudential Supervision (“Paper”) provides further
guidance on the supervisory material related to macroprudential supervision in Insurance Core
Principle (ICP) 24. As part of the holistic framework for the assessment and mitigation ofsystemic risk in the insurance sector (“Holistic Framework”), the IAIS revised ICP 24 to more
explicitly address, among others, the build-up and transmission of systemic risk at theindividual insurer and sector-wide level. The Holistic Framework and ICP 24 were adopted by
the Annual General Meeting in November 2019.
4.
The key elements of the Holistic Framework are: supervisory material, the IAIS Global
Monitoring Exercise (GME) and implementation assessment. While each key element
represents an essential building block in itself, the overall effectiveness of the Holistic
Framework depends on the elements working together. ICP 24, which is supported by thisPaper, is part of the supervisory material outlining an enhanced set of policy measures for a
supervisor’s macroprudential purposes intended for insurers at the legal entity and insurancegroup levels, as well as the insurance sector as a whole. The GME is designed to assess
global insurance market trends and developments and to detect the possible build-up of
systemic risk in the global insurance sector. With the Holistic Framework there is a feedback
loop between the GME and macroprudential surveillance and supervision by individual
jurisdictions. For instance, vulnerabilities building-up in certain jurisdictions may have crossjurisdictional implications that merit monitoring at the global level. Correspondingly,
supervisors may gain a better understanding of underlying trends at the jurisdictional level
when such trends are assessed at a global level.
5.
This Paper does not establish new standards or expectations for the supervisor’s
implementation of a macroprudential supervision framework, but instead provides additional
detail to assist with implementation, and examples of good practice. It should not, however,be considered as an exhaustive guide to macroprudential supervision.
6.

This Paper provides guidance and examples on:•••

Considerations on developing and applying a macroprudential supervision framework
in a proportionate way;Ways that supervisors may tailor requirements of data collection according tojurisdictional circumstances and market structure; andThe practical application of the elements included under ICP 24.

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1.1

Terminology

7.
In this Paper, all terms have the same meaning as described in the IAIS Glossary, theIntroduction to the ICPs as well as within ICP 24 itself and the Holistic Framework overarching
document.
1.2

Scope of application

8.
This Paper and most of its concepts are relevant to the business of insurers andreinsurers, as well as to both insurance legal entities and insurance groups. Its
recommendations are applicable across supervisory approaches. From a macroprudential
point of view and because of the disparity – especially in size – between jurisdictions, analyses
conducted at geographic regional level should also be considered in the scope of the
Application Paper.
9.
The scope of macroprudential supervision should cover both individual insurers as wellas the insurance sector as a whole.
1.3

Proportionality

10.
This Paper should be read in the context of the proportionality principle, which
acknowledges supervisors’ flexibility to tailor their application of supervisory requirements andsupervision to achieve the outcomes stipulated in the Principle Statements and Standards, as
described in the Introduction to ICPs and Common Framework for the Supervision ofInternationally Active Insurance Groups (ComFrame). The guidance, illustrations,recommendations or examples of good practice in this Paper do not supersede thisoverarching proportionality principle.
11.
According to ICP 24.0.1, a jurisdiction’s macroprudential supervision processes andprocedures should be proportionate to the nature, scale and complexity of its insurance
sector’s exposures and activities. The supervisor may increase or decrease the intensity of
the requirements as described in ICP 24, for example, by varying the frequency, scope andgranularity of data collection for macroprudential purposes, insurance sector analysis,
systemic importance assessment, and development and application of supervisory
requirements. Supervisors may also decide on varying the form and level of detail on theinsurance sector publications and comprised data and statistics.
1.4

Structure

12.
This Paper follows the structure of ICP 24, which deals with five different elements ofmacroprudential supervision. The remainder of this Paper is structured as follows:
•
•
•
•
•

Section 2: Data collection for macroprudential purposes
Section 3: Insurance sector analysis
Section 4: Assessing systemic importance
Section 5: Supervisory response
Section 6: Transparency

13.
The annex includes the following examples of indicators and data elements for datacollection, risk dashboards and types of analysis:••

Annex 1: Example indicators and data elements
Annex 2: Example risk dashboards

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Page 7 of 61••Annex 3: Example topics for analysis
Annex 4: Example of ORSA analysis

2

Data collection for macroprudential purposes

2.1

Consideration of data to collect

14.
Sound macroprudential supervision is reliant on timely and good quality data andinformation to support analysis and ultimately well-informed decision-making. Data collection
for macroprudential purposes is a critical element of macroprudential supervision andsystemic risk assessments at an individual insurer level and a sector-wide level (refer to ICP
24.1).
15.
Supervisors should put in place appropriate policies and processes to collect regularand systematic financial, technical and statistical information from insurers it supervises.
Supervisors should collect both quantitative and qualitative data from insurers or use data andanalysis from other external or internal sources. Data and information can be requested on alegal entity level or group-wide basis. Supervisors should first make use of the data sets thatare available and consider the costs and benefits of obtaining additional data
16.
Data collection for macroprudential purposes should consider certain aspects, which
are described in ICP 24.1.1. In particular:
•

•

•

•

•

Data collected should be aligned with supervisory needs by defining required
information (eg in what form, from whom and how often). Required information candiffer according to market developments, market conditions, market structure, etc.;
Data could be collected from other supervisors when an insurer operates in multiple
jurisdictions (refer to ICP 25 (Supervisory Cooperation and Coordination)). Data could
also be collected from other relevant authorities within a jurisdiction. Supervisors
should ensure that they have in place appropriate safeguards for information sharing
as described in ICP 3.2. Macroprudential supervision data collection activities should
be well coordinated;
Data coverage should support macroprudential analysis at both the individual insurer
and at the sector-wide level, covering a representative sample of the respective market
or risk. As an example, this could be based on including at least 75% of the local
insurance market or specific business lines, as appropriate;
Supervisors should develop validation rules to address data quality and deficiencies.
It is good practice to have in place a data validation rules programme to check forcorrectness, meaningfulness and security of data that is input into a system. Data
validation rules should be implemented through the automated facilities of a data
dictionary, or by the inclusion of explicit application programme validation logic;
Systems and processes should be developed to collect and analyse ad-hoc data toaddress evolving and emerging risks, such as climate-related risk 1 or cyber risk; and1 The IAIS, in partnership with the United Nations-convened Sustainable Insurance Forum (SIF), published theApplication Paper on the Supervision of Climate-related Risks in the Insurance Sector in May 2021. The Paper
provides insurance supervisors with concrete tools to further strengthen their efforts in assessing and addressing
risks from climate change.
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•The data collection process should be transparent, including by being explicit about
the purpose and objectives of the data request, and consistent across all selected
insurers.

17.
Annex 1 provides examples of indicators and data elements that could be used tomonitor trends and assess the build-up of systemic risk for individual insurers and theinsurance sector as a whole. These include macroeconomic and microeconomic data,
indicators to support the assessment of liquidity risk, macroeconomic exposure, counterparty
risk, as well as cross-sectoral indicators.
2.2

Risk dashboard for monitoring key macroprudential indicators

18.
Supervisors should determine an approach to aggregate, analyse and present data toallow for sector-wide monitoring of vulnerabilities and macroeconomic instability. There aremany risk assessment and prioritisation methods and tools available to supervisors thatprovide a general overview of key risks and also identify relative trends in the insurance
industry. A risk dashboard represents a link between data collection and analysis methods
and is one such tool that can cater to jurisdictional objectives by including relevant indicatorsfor supervisors to assess risks and trends of the insurance industry in aggregate at thejurisdictional level.
19.
A risk dashboard may contain both quantitative and qualitative information and should
be updated on a regular basis. The frequency of updating may depend on the availability of
data, the stage of the financial cycle and other market developments or impending disruptions.
Typically, risk dashboards use a combination of indicators and may summarise information
visually (eg a traffic light system), providing insight into both historical trends as well as thecurrent risk environment. A risk dashboard may also include specific risk parameters.
20.
A risk dashboard may be constructed on a flexible basis, according to categories ofrisks deemed most significant or imminent. These may include: macroeconomic risk, credit
risk, market risk, funding and liquidity risk, profitability and solvency risk, as well as risks arisingfrom interlinkages and imbalances. Supervisors have the option of adding (or deleting)categories to allow for sector specific risks (eg insurance underwriting risk).
21.
The remainder of this section provides general guidance and examples on theconstruction and use of a risk dashboard. Annex 2 provides examples of risk dashboards usedby South Africa and EIOPA.
2.2.1

Constructing a risk dashboard

22.
A risk dashboard may include the following components: key risk categories, key risk
indicators, a risk assessment scale and a risk trend as well as any other component thesupervisor deems necessary.
Key risk categories
23.
The supervisor may identify key risk categories that are most relevant for thejurisdiction’s insurance industry and the environment in which they operate.
Key risk indicators
24.
The next step is to identify key risk indicators for each risk category. Specifically, thesupervisor may develop a set of indicators, grouped into main risk categories, including moregranular subcategories within each main category. Key risk indicators are usually data that
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can be measured over time, such as interest rates, inflation rates and combined ratios (foradditional examples refer to Annex 1). Indicators may be based on a combination of publicly
available market data and supervisory reporting data, and in alignment with analysing trends,
emerging risks and vulnerabilities. Risk indicators may also be qualitative or subjective innature and require judgment by the supervisor.
Risk assessment scale25.
A colour-coded risk assessment scale such as red (high), amber (medium-high), yellow(medium-low) and green (low) could then be applied to the risk indicator level. The scale may
be applied based on the historical distribution of the risk indicator. This may be accomplishedby applying numerical ranges of the risk indicator to different scales. Additionally, supervisors
may use expert judgement and/or apply statistical means when conducting risk assessments.
Some risk indicators may not lend themselves to historical distributions and the assessment
scale may be qualitative or subjective in nature. Another potential method of conducting risk
assessments is to apply a likelihood and probability of impact scale to assess the level of risk.
Finally, supervisors may find it beneficial to define these risk assessment scales in a mannerthat is transparent and consistent over time. Supervisors should document whichever method
they employ step-by-step, illustrating how they arrived at their risk assessment ratings.
26.
Overall risk levels, identified by the related sets of indicators, should reflect theriskiness of the insurance sector as a whole. The relative importance of the various indicators
can be assessed through the application of specific weight parameters. In principle, the same
weights can be applied for each indicator; however, weights can be increased if indicators areof significant importance for a risk category or reduced if indicators are highly correlated.
Risk trend
27.
Another key component of a risk dashboard is the trend or direction of the risk, which
provides some perspective or comparison of current risk levels, as well as the comparison topeer groups or cross-sectoral analysis. The trend is usually indicated by an increasing, flat ordecreasing arrow and is indicative of the risk direction from the previous reported risk level tothe current risk level. Advanced risk dashboards may contain prospective or forward-looking
trend indicators. However, obtaining reliable forecast data may be a challenge. Trends
typically reflect the behaviour of the risk by indicating how a certain exposure or indicator has
developed over time. The behaviour of the risk, based on trends, can be assessed against
thresholds or other indicators.
2.2.2

The use of a risk dashboard

28.
A risk dashboard may be used as a tool to help satisfy many of the objectives in ICP
24 and monitor both inward and outward risks (including the identification of the build-up of
systemic risk in the insurance sector). A risk dashboard may be tailored to the specificities ofa certain jurisdictional market and be used to identify interplays between sector-wide risks
identified in the dashboard to individual insurer analysis in the same way that the IAIS analyses
risks and trends from both an individual insurer and sector-wide perspective on a global basis,
as part of its GME. 2 Additionally, the interplay may act as an early warning indicator of a buildup of systemic risk in the insurance sector.

Refer
exercise2

tohttps://www.iaisweb.org/page/supervisory-material/financial-stability/file/87206/global-monitoring-

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29.
The risk dashboard may be used as a tool for supervisors to compile data to perform
analyses of the insurance sector and financial markets. The analyses may be both quantitativeand qualitative in nature and include historical trends and the current risk environment, as wellas prospective risks. Risk dashboards could primarily consider inward risks but can also beenhanced to incorporate outward risks.
30.
Supervisors may also consider using the risk dashboard in a top-down, risk-focused,supervisory approach. Starting at the top with a sector-wide risk dashboard, supervisors may
wish to channel their supervisory resources towards identifying individual insurers who
contribute to sector-wide risks and potential systemic risk or activities. When examining an
individual insurer, the supervisor should be aware of the broader market in which the insurer
operates to be able to better understand the context of certain risk factors.
31.
A risk dashboard may also be used to identify and implement risk mitigation tools (refer
to Section 5). As described in ICP 24.5, supervisors may publish any relevant sections of therisk dashboard (ie indicators and/or methodology) (refer to Section 6).
3

Insurance sector analysis

3.1

Steps and approaches for insurance sector analysis

32.
The objective of this section is to provide a non-exhaustive list of examples ofmacroprudential analysis methods, to support the implementation of ICP 24.2. Such methodsof analysis can highlight key risks, vulnerabilities and trends of economic, financial andtechnical insurance factors that can affect the actions of individual insurers and the insurance
market as a whole. It is useful for supervisors to have an overview of risks but also identify
and monitor specific sources of certain trends and risks. Supervisors can decide on the mostappropriate method of analysis to use, depending on jurisdictional needs.
33.
This Paper is not intended to prescribe which method of analysis is better, as this would
largely depend on supervisors’ needs and data availability. Instead, the purpose of this Paper
is to suggest a range of possibilities that supervisors may consider, to broaden knowledge on
the insurance market and for supervisors to put in place (directly or indirectly) mitigating
actions to limit systemic risk (refer to Section 5 for further information).
34.
It may be useful for supervisors to take into consideration two different but
complementary steps:
1. Identification of key risks and trends to assist supervisors to verify whether a risk factor
is emerging and could have wider implications for the stability of the insurance sector;
and
2. In-depth analysis/assessment of risks and related trends through quantitative insights.
35.
For the identification of key risks and trends, it is important for supervisors to also
consider historical trends, the current risk environment and a forward-looking component. By
monitoring historical trends of factors/indicators over time supervisors can observe the driversof such changes as well as sources of risk that could destabilise the insurance sector.
36.
Supervisors should assess insurers’ exposure to both inward and outward risks using
the most appropriate analysis method. Assessment of second-round effects could be useful

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for supervisors in determining outward and inward risks. 3 An outward risk assessment of
second-round effects induced by endogenous factors, following actions taken by financial
institutions, households, regulators and/or policymakers in response to an initial shock or
scenario could be performed. For inward risk, supervisors could assess whether insurers haveincurred losses from second-round effects that resulted in premium increases (eg catastrophic
risk, cyber risk or operational risk connected to business interruption). Such analysis may becomplex; hence, supervisors may need to rely more on qualitative assessments. The analysis
of insurance indicators and data elements (mentioned in Section 2 and Annex 1) may be
performed at an individual insurer and/or sector-wide level. Analysis methods are further
discussed below and in Annex 3.
37.
Finally, supervisors should apply qualitative and quantitative methods of analysis,
particularly in the case of forward looking indicators that could help identify existing, new andemerging threats to financial stability in the insurance market. Quantitative and qualitative
methods of analyses can also be done for exogenous factors (global macroeconomic andfinancial markets) and endogenous factors (domestic) in the insurance sector.
Table 1: Common quantitative and qualitative analysis methods
Quantitative analysis
methods
Trend analysis(refer to 3.2.1)

Qualitative analysis
methods

Both quantitative andqualitative analysis
methods

Market intelligence analysis(refer to 3.3.1)

Vulnerability analysis (refer
to 3.4.1)

Stress test analysis (refer to3.2.2)

Horizontal reviews (refer to3.4.2)

Sensitivity analysis (refer to3.2.3)
38.
Such analysis methods may, for instance, be employed to assist in identifying andmonitoring the following example risk exposures and activities (refer to Annex 3 for further
information):•

Liquidity monitoring•

Derivatives monitoring ••Interconnectedness
Reinsurance analysis

39.
It is important to understand the phenomena that could trigger short, medium and longterm events that generate significant risks. Many analysis methods, quantitative or qualitative,
may help supervisors identify risks to which the insurance sector is exposed, at a specific point
in time, or to monitor current and forecast future results. 4 Qualitative methods can be useful,particularly during stressful conditions where the behaviour of policyholders and entities could
significantly deviate from “normal” periods.
3 For example, when assessing the impact of Covid-19, first-round effects would be related to the pandemic itself,

whereas second-round effects may be related to the impact of regulatory or other actions. Another example ispossible fire sales: a scenario that could cause rapid asset sales (first round effects), which could result in a
substantial deterioration in market prices and other entities beyond what was initially envisioned.
4 Quantitative methods may be used to forecast future operational results of insurers for supervisors to monitor
against an insurers actual results to determine whether results are in range with expectations.
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40.
While some analysis methods could assist supervisors’ analysis of existing or newly
identified risks (eg vulnerability or market intelligence analysis), other analysis methods may
be used for more in-depth investigations to highlight low likelihood, high impact risk events (egstress testing or sensitivity analysis). Outcomes of the analysis can help supervisors act withgreater awareness and achieve the objectives described in the principle statement of ICP 24.
Common quantitative and qualitative analysis methods are explained in more detail in the next
section.
3.2

Common quantitative analysis methods

3.2.1

Trend analysis 5

41.

Trend analysis may include:••

A financial and macroeconomic overview that observes the trends of the key
macroeconomic and financial indicators (eg annual growth of gross domestic product(GDP), inflation, unemployment rate, etc.);
A relative analysis to observe how trends in the insurance sector compare to trends in(i) insurance sectors in other jurisdictions, geographic region and across the globe, (ii)between segments of the insurance sector both within and across jurisdictions, (iii)
other parts of the financial system and (iv) the real economy.
There should be a focus on key insurance and financial variables, such as:- Profitability and capital strength indicators;- Combined ratio of non-life insurance;- Return on Equity;- Equity prices;- Expected earnings;- Composition of the qualified capital resources;- Composition of the investments;- Life insurance guarantees compared with asset performance; and- Breakdown for minimum guaranteed rate offered in life contracts.
Other key insurance and financial variables may be requested for further in-depth trend
analysis based on supervisory judgement.

42.
Supervisors may also consider using, as necessary, outlier indicators from themacroprudential perspective (eg during an economic crisis or other unanticipated event) in
performing trend analysis. For example, outlier indicators could be aspects related to the levelof dependence on data providers, digitalisation and/or public funds. 6 Using outlier indicatorsin trend analysis may give supervisors further insight on activities that may have an effect on
the real economy and the stability of the insurance sector.
43.
The analysis of the main historical trends in the insurance sector may be carried out
by supervisors periodically (eg quarterly, semi-annually or annually), depending on theavailability of data (refer to Section 2).

5 A trend is a data pattern that shows persistent characteristics even if there are deviations (relative to trend).

6 The Holistic Framework uses an outlier criterion for each of the indicators in the Individual Insurer Monitoring (IIM)

exercise, which is employed by the IAIS as part of its GME in order to identify individual insurers that develop
significantly different from the sample.

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44.
Macroeconomic data (referenced in Annex 1) can be used for trend analysis and could
possibly impact the development or evolution of the insurance sector as it influences thestrategic choices of insurers.
45.
Data relevant for risks to the insurance sector can be extracted/processed from
reporting and statutory financial statements based on accounting standards and solvency
regulations. For this analysis, it is important to have a well-structured database (with clear data
extraction criteria) in order not to compromise the reliability of the outcomes.
46.
The temporal observation of factors, including resilience 7, highlights trends that canhelp supervisors in assessing risks and determining the need to take preventive or corrective
action (refer to ICP 10.0.2) to strengthen financial stability in the insurance market.
3.2.2

Stress testing47.
As described in ICP 24.2.6 to 24.2.8, supervisors should have in place an appropriate
form of stress testing to support the analysis of the current risk environment and to assess theresilience of the insurance sector to severe but plausible scenarios. In addition, stress testing
may help to test the solvency, liquidity or profitability of insurers under stressed market
conditions. Stress testing analysis helps supervisors have a forward-looking perspective of
the insurance sector by considering plausible scenarios to capture potential future adverse
developments. 8
48.
The depth of supervisory stress testing exercises would depend on the scope of thestress test (entities involved and stressed factors) and the approach supervisors choose tofollow (ie bottom-up or top-down, as discussed below). Stress tests should be fully integrated
in a jurisdiction’s broader monitoring and supervisory framework and not be considered as astand-alone exercise. This would not preclude designing and using stress tests to assess andmonitor assumptions and parameters included in the in-force regulatory framework.
Assumptions should always be confirmed and verified especially for forward-looking
perspectives.
49.
To obtain plausible results in line with the purpose of ICP 24.2.6, supervisors shouldhave in place an appropriate form of stress testing, which is applied to the insurance sector
as a whole or a significant sub-sample of insurers, according to their exposures to specificrisks. The resilience of individual insurers or the insurance sector should be tested against
severe but plausible scenarios based on an economically consistent set of events/shocks.
50.
Insurance stress tests should have a common set of characteristics for how they arebeing conducted, the approach and the data that are being used, the frequency at which thetest is being conducted, market coverage and the technical structure/features/specificationsof the tests.

7 Resilience in this context refers to the ability of an insurer to recover quickly from difficulties and find alternative

solutions.

8 This type of supervisory stress testing, as described in ICP 24, should not be confused with stress testing andscenario analysis performed by an insurer as part of its own ERM (which is described in ICP 16 (Enterprise Risk
Management for Solvency Purposes).
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Top-down versus bottom-up stress testing approaches
51.
Stress tests are usually conducted using a bottom-up or top-down approach. In thebottom-up approach, each insurer receives a set of pre-defined, common adverse scenarios
to be performed in its portfolio before reporting the results to the supervisor.
EIOPA example to establish a bottom-up stress testing framework:
When designing and setting-up a bottom-up framework, as well as determining thestructure and main elements of such an exercise, the supervisor could consider theelements reported below. For more detail, refer to EIOPA (2019) Methodological principles
of insurance stress testing. Available at:https://www.eiopa.europa.eu/sites/default/files/publications/methodological-principlesinsurance-stress-testing.pdf

On the other hand, in a top-down approach 9 supervisors essentially run the entire analysis
themselves and assess the impact of the scenarios on the insurer(s) directly. In a bottom-up
stress testing exercise, insurers are asked to calculate the impact of a common adverse
scenario that allows supervisors to do benchmarking and assess financial resilience in theinsurance sector. Parameters for the bottom-up stress testing exercise could be provided bysupervisors in the form of sensitivity parameters or scenarios. If the stress tests are of a

9 An example of stress test analysis conducted with the top-down approach can be seen in the Financial Stability

Report N.1/2019 (Bank of Italy), in the section dedicated to Insurance
https://www.ivass.it/pubblicazioni-e-statistiche/pubblicazioni/altre-pubblicazioni/2019/rsf1/FSR_n1_2019_ENG.pdf?language_id=3
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(page

36).

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macroeconomic and financial nature, macroeconomic scenarios could be the input of satellite
models 10 that link macroeconomic variables to microeconomic and insurance-specific ones.
52.
In cases where supervisors may not have sufficient expertise or resources available todevelop supervisory stress testing, or complement its supervisory stress testing initiatives,
they may also consider benchmarking (horizontal reviews) of stress tests performed by the
insurers themselves. As discussed above, stress testing is also required to be conducted by
IAIGs and other insurers as necessary as part of their own Enterprise Risk Management(ERM), for instance as part of the Own Risk Solvency Assessment (ORSA). 11 Supervisors
could also provide guidance to the market with specifications on how to conduct stress tests
to be included in the ORSA. In this way, supervisors could perform a horizontal review of
ORSA reports from different insurers, with risks and assumptions that may help supervisors
identify areas of potential risk, particularly with a forward-looking perspective. Annex 4
includes an example of ORSA analysis used by IVASS.
53.
Both of the aforementioned approaches have advantages and disadvantages asshown in Table 2. In the bottom-up approach, supervisors may need to consider the integrityof the data to ensure reliability of the tests conducted. They should therefore ask for a uniform
set of data and apply uniform scenarios across institutions in order to be able to makeconsistent comparisons between insurers. Comparability could also be achieved throughengagements with insurers on approximations and simplifications, which could be applied in
the calculation of their post-stress positions and through a validation process. In the top-down
approach, supervisors would build on data already collected as part of the supervisory
reporting. This may be a drawback as such data may have limitations considering it was not
specifically designed for stress testing. Further, while the use of uniform datasets orapproaches can enhance comparability, it could also limit risk sensitivity insights whencompared to the bottom-up or more tailored approaches.
Table 2: Advantages and disadvantages of top-down versus bottom-up approaches:
Advantages

Top-Down

Bottom-Up

Supervisors control the process
which can be used more
effectively to get results.

The accuracy of the results
leverages off insurers’ more informed
knowledge of risks (the calculation
fully accounts for risk profiles andproactive risk management byinsurers eg hedging or risk transfer).

Uniformity of the test based on aprescribed set of scenarios.

Results could reflect the actual
vulnerability of insurers to theprescribed shocks based on their risk
profile or identify additional risks andvulnerabilities.

Knowledge of the criteria,
methods and information (egEmbeds individual specificities.

10 Financial linkages models that directly connect macroeconomic assumptions and risk parameters
https://www.elibrary.imf.org/staticfiles/misc/toolkit/pdf/chap1.pdf
11 Further information in ICP 16.2 quantitative techniques to measure risk, ICP 16.10-16.14 and ComFrame
standards integrated therein, and ICP 24.2.5 on horizontal reviews.

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type, date of data) used for the
stress exercise.
Disadvantages Resource-intensive exercise forsupervisors.

Resource-intensive for participants
and supervisors.

Supervisors may not have all theavailable data for risk
assessment (eg individual
specificities such as assets andliabilities as well as management
practices of each insurer).

Lack of transparency as the insurer
is privy to information thatsupervisors may not have.

Use of models may limit
flexibility of approach.

Participants tend to present morefavourable results.

54.
Depending on the approach taken, supervisors may need to obtain the necessary datafrom insurers on their portfolios to facilitate the conducting of the actual stress test.
Frequency of stress testing exercises
55.
The frequency of conducting stress tests should take into account the entire cycle ofthe exercise, namely the design phase, the running phase and the follow-up phase. Dependingon the objective, the complexity of the scenario(s), the number/complexity of the insurers
included in the scope, supervisors should plan for sufficient time between stress test
exercises. For example, stress testing exercises could be conducted every two/three years,
with a provision that supervisors conduct stress tests more frequently in the event ofunanticipated market crises or shocks, in which case, reference scenarios could be redefinedor simplified.
Market coverage
56.
As discussed above, ICP 24.2.6 recommends that stress testing exercises be applied
to the sector as a whole, or to a significant sub-sample of insurers. Depending on the objectiveof the analysis, supervisors may wish to focus on individual legal entities and/or insurancegroups.
Example of a top-down stress test (IVASS)
Shocks are based on the values of the different asset classes observed at a particular timeinterval. The interval is determined by considering the maximum value and the 75th
percentile of the historical series of the BTP-Bund spread as this is the primary risk factor
for the Italian insurance sector. The stresses are applied to:•••

Italian government bonds
Corporate bonds for AAA, AA, A, BBB and BB rating classes separately
EquityBonds values are recalculated by using the following formula (Duration approach):
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D => related modified duration
Δi => change of BTP-Bund spread (bond)
ΔP => change of bond value
The results are defined in terms of the impact on the capital requirement and solvency
position (eg represented by the solvency ratio).
This example of top-down stress only reflects stress on assets. The stress would also
impact liabilities. Liabilities are indirectly considered as they are closely linked to thecomposition of the product portfolio that determines the obligations of the insurers (different
from each other) and of the market as a whole. It is more complex to generalise the stresson liabilities.
57.
It is good practice for stress tests to be broad in scope and include a balanced numberof insurers in order to provide a comprehensive view of insurance sector vulnerabilities. A low
coverage of insurers being stress tested may hide the vulnerabilities in the sector while, on
the other hand, covering every insurer may not necessarily produce more information.
Different criteria could be used to assess the market share of tested insurers such as the grosswritten premium, total assets, etc.
Technical structure and specifications
58.
Stress tests could include: i) a macroeconomic scenario generator that consistently
translates macroeconomic shocks into shocks for both the assets and liabilities (eg a parallel
lowering of the risk-free rate curve of 50 basis points); and ii) a stochastic generator of
insurance losses based on a correlation structure that could capture possible correlations withthe asset or the liability side (eg on the asset side, disinvestments due to massive redemptions(mass laps), and on the liability side, insurance drivers such as mortality/lapse /claims
frequency could be considered).
59.
Stress tests examine the solvency, liquidity or profitability of insurers for a specific time
horizon. The most common approach for stress testing is to examine an insurer over one year
(consistently with the widely applied supervisory framework) against a set of instantaneousand permanent shocks. However, supervisors could extend the timeframe of the stress test
exercise moving towards a multi-period framework where the post stress solvency position of
the insurer is assessed against a set of risks that evolves over longer time horizons (eg 3 or 5
years). In this case, it would be important to consider that the level of complexity required todesign and apply multi-period shocks to an industry that already bases its business on
stochastic projections is extremely high. 12 Multi-period frameworks bring several advantages
such as the possibility of prescribing both permanent and non-permanent shocks (eg a dropin the market followed by a recovery), more realistic scenarios based on sequences of shocks(eg shocks to lapses lagged with respect to shocks to markets) and the possibility to analyse
the time evolutions of key indicators (eg assets over liabilities or the capital requirements). At
the same time, the forecasts of scenarios become less reliable if the time horizon is extended.
12 For an initial discussion on the complexity of multi-period stress test exercise please refer to EIOPA (2020)
Second discussion paper on methodological principles of insurance stress testing. Available at:https://www.eiopa.europa.eu/sites/default/files/publications/consultations/eiopa-bos-20-341_seconddiscussion_paper-methodological-principles-for-stress-testing.pdf

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This forward-looking approach allows for supervisors to observe that insurers may survive asingle shock but could face severe challenges in surviving or resisting a prolonged shock
scenario or multi-period shocks. Against this background, any multi-period initiative should be
carefully evaluated from a cost-benefit perspective.
3.2.3

Sensitivity analysis

60.
Sensitivity analysis is an evaluation of the degree by which a model’s results vary in
response to changes to the values of input variables. It refers to a “what if analysis” that
evaluates what changes materialise if the values assumed by specific parameters change as
well. Sensitivity analysis could be complementary to stress testing analysis, however, it could
be that shocks in a sensitivity analysis are less or equally severe than that of a stress test.
Additionally, sensitivity analysis aims to evaluate the impact of the variation of an individual
risk factor (only one at a time) identified on the basis of sector vulnerabilities or on a specificsample of selected insurers. In other words, sensitivity analysis is performed on mostprominent/material risks that could have spillover effects in high volatility scenarios. In suchcircumstances, the scenarios usually consist of the variation of a single risk factor, where
supervisors could evaluate or capture potential future developments of the effects arising fromthe factor considered.
61.
Sensitivity analysis exercises can make use of data that is readily available tosupervisors, provided that there is a structured and homogeneous database, with establishedcriteria for extracting and acquiring information. The data extracted by insurers should always
follow the same criteria 13 to assist supervisors in understanding the macroeconomic
implications of a given factor. In the case of a non-homogeneous database, the data could beacquired in a homogeneous way through ad hoc requests to insurers (including sampling).
62.

Sensitivity analysis provides supervisors with the ability to:Assess the solvency, liquidity or profitability position of the insurance sector in
response to a shock affecting a single aspect of interest, particularly asset classassumption (eg sovereign bonds), an increase in bond spreads (eg +100 basis points)
and keeping other asset classes at their reporting values (baseline); andContribute to more informed policy choices (ie the reactivation of specific monitoring
analysis to create more awareness in a specific moment, such as monthly liquidity risk
monitoring).

••

An example of sensitivity analysis on asset classes
The composition and duration of assets at the latest available data point (using balance
sheet data) can be used for sensitivity analysis. The following investment categories canbe considered for each insurer in a sample:
•
•
•
•
•

National government securities (eg Italian, French, UK, US, Japan, China);
Corporate bonds divided by Credit Quality Steps (CQS) and by sector (financial
and non-financial);
Structured notes and collateralised securities per CQS and per sector in line withthe breakdown envisaged for corporate bonds;
Equities; andDebt or equity mutual funds.

13 If different criteria is used, the information may not be comparable or may express different factors.

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For each type of investment category, the relative weighted average duration is determinedon the basis of the value of each security for which the insurer reports the duration. Shockscenarios can be applied, to the insurance sector in its entirety, with the assumption thatfor securities without duration, the duration is equal to the average duration of theinvestment class.
3.3

Common qualitative analysis methods

63.
Supervisors could also consider qualitative analysis methods (eg review ofquestionnaires, surveys, or published material) to monitor and assess specific risks that might
not necessarily be identified by quantitative analysis methods. This type of qualitative
vulnerability analysis can be conducted on a quarterly, semi-annual or annual basis tocomplement quantitative assessments.
3.3.1

Market intelligence and risk workshop with stakeholders

64.
In line with the purpose of ICP 24.2.3, supervisors should identify the key sources ofmarket and industry information and take into account all relevant factors when assessing theinformation. Supervisors should ensure that there is an appropriate internal focus on regularly
reviewing macroprudential supervision issues and market specificities and, where appropriate,
initiate senior level engagements with insurers on these issues. For this purpose, it could be
useful for supervisors to keep abreast of the main risks observed by financial and insurance
analysts that can influence the development of the insurance market.
65.
Macroprudential supervision uses approaches from a multi-disciplinary and crosssectoral perspective in order to identify activities, trends and developments that might
negatively impact the risk profile of insurers. Supervisors could assess analytical perspectivesof relevant stakeholders in public and private sectors by setting up periodic meetings (egannual workshops) with different stakeholders involved (directly or indirectly) in thedevelopment of the insurance market (eg credit rating agencies, consultant firms, supervisory
colleges).
66.
Annual or periodic qualitative exchange of views with stakeholders allows: (i)supervisors to deepen their assessments on key risks in the insurance sector, and (ii) market
participants to benefit from the sharing of ideas on issues that present challenging or
innovative aspects for the evolution of the insurance sector.
67.
Supervisors could benefit from comparative analyses conducted by different
stakeholders on main risks of the sector from different perspectives, both in terms of impact
and probability of occurrence.
3.4

Common quantitative and qualitative analysis methods

68.
Other analysis methods could have both quantitative and qualitative approaches that
could help supervisors monitor and assess risks in the insurance sector. The analyses could
be conducted on a quarterly, semi-annual or annual basis to complement quantitative
assessments.
3.4.1

Vulnerability analysis

69.
As part of monitoring the primary sources of vulnerability in the insurance sector,
supervisors may determine certain risk factors that could generate aspects of vulnerability andcompromise the financial stability of the sector's insurance market. For example, such analysis
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Supervisors could use this analysis to conduct investigations on inward and outward risks.
Considering this analysis is performed on risks influenced by social and economic-financial
events that may change over time, this analysis may require the use of ad-hoc information.
70.
This analysis can be conducted according to proportionality and is based on the
supervisor's information needs. Supervisors should take into account the materiality of the risk
to be monitored. This analysis may be conducted on a sample of insurers in terms of market
share and/or exposure to the risks under investigation.
71.
The information and data for this analysis may not be available to the supervisor
through public or supervisory reporting and require that additional quantitative and qualitative
data be requested. Standard requests, planned periodic reporting, are typically used formonitoring known risk factors while additional requests may be necessary to investigate
specific aspects arising from supervisory concerns.
3.4.2

Horizontal reviews72.
To study aspects from a macroprudential perspective, consistent with ICP 24.2,
supervisors could perform or make use of both public and other sources of information, that
include horizontal reviews of insurers and relevant data aggregation.
73.
Horizontal analyses can relate to quantitative or qualitative aspects, both of whichshould be structured appropriately for accurate interpretation.
74.

Horizontal quantitative analysis could be conducted on:••

Readily available statutory data; orData collected from periodic structured data calls (using specific templates that request
detailed information not included in statutory returns.

75.
In both cases, supervisors should aggregate the data to examine homogeneity orstrong deviations, as well as common aspects for certain insurers. This analysis could be
useful to understand the distribution of certain indicators that could offer information ondifferent areas of vulnerability.
76.

Horizontal qualitative analyses can be conducted through:••Pre-set questionnaires with multiple choice answers (eg perception of risk level: high,medium-high, medium, medium-low, low); or
Questionnaires with open-ended responses.

77.
The benefit of having pre-set questionnaires is that they solicit information that is easierto understand and compile. The added benefit of having open-ended questionnaires is togauge specificities or behaviours related to specific business strategies of insurers. For
example, the behaviour of similar entities with similar risk profiles could be better observed.
The evaluation of this information can allow supervisors to have an overview that could be astarting point for further study on other macroprudential and quantitative analysis methods.
78.
Supervisors may also find it useful to perform peer group or benchmarking analysis forhorizontal reviews. As described in ICP 24.2.5, the criteria for establishing a peer group or
benchmarking for horizontal analysis should be considered carefully by the supervisor. It is
common practice to ensure peer group participants have common features or meet common
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criteria for inclusion. For example, within the IIM exercise, the IAIS has established a minimum
set of criteria that ensures analysis of selected groups with significant aggregate size andinsurance activities outside of the home jurisdiction. In addition, insurers can be further
grouped by business type (primarily life, primarily non-life, or composite) and regulatory regime
or geographic region. Bespoke criteria can be developed to build peer groups for almost any
specific activity. Peer groups should be periodically reviewed to make sure prior participants
continue to qualify for inclusion. Some benchmarking options are readily available throughfinancial data providers. 14
4

Assessing systemic importance

79.
Identification of systemic importance in the insurance sector is one of the paramountobjectives of macroprudential supervision. As described in ICP 24.3, supervisors are required
to have “an established process to assess the potential systemic importance of individual
insurers and the insurance sector”. This section provides guidance and examples on how suchprocesses can be set up and used in practice, both from the perspective of individual insurers(Section 4.1) as well as from a sector-wide perspective (Section 4.2).
80.
The potential systemic exposures, activities and transmission channels, as describedin ICP 24.0.4, are briefly summarised below. 15 These are relevant regardless of theperspective of the assessment.
Liquidity risk (asset liquidation)
81.
Liquidity risk arises as a result of imbalances between liquidity sources and needs,
although not as important for insurers as it is for banks. It becomes a macroprudential concern
if a shock (the trigger event) leads to reactions causing liquidity shortages across an entire
sector or across several sectors.
82.
If liquidity risk materialises for an insurer or a number of insurers, this could trigger adownward pricing spiral in the financial markets. Through these price impacts, shocks could
be transmitted to other parts of financial markets and the real economy by triggering writedowns on similar assets at other firms, distorting the signalling function of prices or impacting
the ability of firms to fund activities.
Interconnectedness (exposure channel)
83.
Interconnectedness refers to interlinkages with other parts of the financial system andthe real economy. Two main aspects of interconnectedness are counterparty exposure andmacroeconomic exposure. Indications of increased interconnectedness can be related to ahigh correlation of the balance sheet with the financial markets, interconnectedness with banks
and other financial institutions, non-bank financial intermediaries or other insurers.
84.
Insurers are participants in the overall financial system, either as providers of financial
services or as providers of funds that are used in the proper function of the financial system.
As such, insurers are connected with other parts of the financial system, including otherinsurers, banks, funds, brokers, custodians etc. Failure of one or more insurers could have
14 During Covid-19 crisis, the IAIS, through its risk dashboard of key market indicators, monitored the global
insurance sector’s performance through, but not limited to, comparing the MSCI World Insurance Index value
relative to the MSCI World Index; MSCI World Bank Index; and MSCI World Financial Index.
15 A full description of the IAIS view on the sources of systemic risk in the insurance sector can be found in Section
2 of the Holistic Framework overarching document.

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contagion effects to the rest of the financial system. At the same time, the failure of otherfinancial institutions could affect the financial health of an insurer, with the insurer potentiallyacting as an amplifier of existing systemic risk.
85.
Additionally, direct interconnectedness can occur within conglomerates, and is ofparticular relevance in cases where an insurer is part of a larger financial group, which includes
banks or other financial institutions that have been identified as systemically important. Withinsuch a conglomerate, the bank and insurer are exposed to weaknesses in each other throughfinancial, reputational and operational links.
Limited substitutability (critical functions 16)
86.
The failure of a large insurer in a critical niche market may become a systemic concern
if it leads to financial problems for its counterparties, particularly if these counterparties are
critical financial market participants themselves. Limited substitutability refers to the difficultyfor other components in the financial system to ensure the continuation of supply of insurance
coverage after a failure or distress of an individual insurer that performs a specialised function.
87.

Alongside these three main exposures, it is important to assess other factors such as:
•

•

•

•

The extensive use of leverage (other than regular debt in the form of policyholders’reserves), can be an indication of risk building and cascading exposures between
leverage providers which could be banks, funds, etc. that are exposed to credit risk of
insurers;
Products and/or assets with non-linear reaction to volatility (ie extensive usage ofoption-like payoffs including exotic-type of payoffs with path-dependence, look-backprovisions, barrier type of write-off);
Size of the exposure of activities matters at both the individual insurer level and sectorwide. It could well be that individual insurers may have small exposure to certain
activities, but at the aggregate level there could be a significant build-up ofvulnerabilities; andGlobal activity may be a proxy for the complexity of an insurance group, as well as theextent to which other jurisdictions’ economies or financial systems might be impacted.

Depending on the jurisdictional circumstances, there may be other factors, or emerging risks,that are relevant to include in the assessment of systemic importance.
4.1

Assessing systemic importance of an individual insurer

88.
There are two main, albeit non-exhaustive, approaches to identifying systemic risk, theindicator-based approach and the reduced-form approach.
4.1.1

Indicator-based approach89.
In the indicator-based approach for the identification of systemically important insurers,
supervisors define a set of indicators that proxy different aspects of the systemic footprint of
the insurer. In choosing the appropriate indicators, supervisors could take into account thefollowing elements, as examples:
1. A total balance sheet approach, including off-balance sheet items that may contributeto systemic risk;
16 Consistent with ICP 24 and the Holistic Framework, use of the term “critical function” is in a general sense toindicate transition channels.

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2. The potential systemic exposures and activities (as described above), including theinterconnectedness with the financial system and real economy; and3. Limited substitutability.
90.
Elements 1-3 can be used as tools to assess systemic risk by applying a principlesbased approach with underlying theoretical concerns. The indicator-based approach is incontrast to the reduced-form approach that strives to identify systemically important insurers
using statistical relationships. Given elements 1-3 in the assessment of systemic risk, thesupervisor can identify indicators within these elements to identify potential systemic risk.
91.
One example of an indicator-based approach is the IIM exercise employed by the IAIS
as part of its GME. While the IIM exercise is aimed at assessing systemic risk at a global level,supervisors may nevertheless find it useful to consider when designing an approach aimed atassessing systemic risk within their own jurisdictions. 17
Total balance sheet approach
92.
Insurers are assessed according to their entire exposure in terms of assets andliabilities, including capital resources, to evaluate the systemic footprint of an insurer. In the
total balance sheet approach, supervisors should evaluate the following:
•
•

•

•

•

How the insurer’s assets correlate with financial markets to allow risk from financial
markets to affect the financial status of the insurer (inward risk);
How the revaluation of insurer’s assets can cause financial instability through channels
such as fire sales, mark-to-market repricing, credit risk, run on liabilities, default of areinsurer etc. (outward risk);
How insurance liabilities interact with financial markets and the real economy, witheither a run or a reduction in the supply of insurance liabilities, having detrimental
effects on the real economy and/or financial markets (macroeconomic exposure);
How capital can sustain systemic shocks of the financial system (inward risks) andhow capital can shield off any adverse effects of a systemic event to the real economy(outward risks). Capital should be evaluated both in terms of quantity, quality andduration (short-term vs. long-term); andHow liquidity could be affected in times of stress 18 and how liquidity shortages could
have both inward and outward repercussions in the systemic profile of the insurer.

93.
While the total balance sheet approach is important, off-balance sheet items should be
judged holistically. For example, the quality and availability of contingent financing during
times of stress should be thoroughly evaluated.
94.
Capital interconnectedness is the notion that securities issued by financial institutions(banks or insurers) and held by other financial institutions should prompt supervisors toevaluate them separately as potential resources of liquidity or solvency. During systemic
Refer to https://www.iaisweb.org/page/supervisory-material/financial-stability/file/87206/global-monitoringexercise, in particular Section 4.1 “The IIM assessment is no longer focussed on identifying prospective G-SIIs, butrather aims to support a comprehensive assessment by the IAIS on the potential build-up of systemic risk in theinsurance sector as a whole by looking at potential systemic risk from activities or exposures concentrated inindividual insurers.”
18 When assessing the availability of contingent financing during times of stress it is important to note that the stressscenarios that impact the insurer and the provider of contingent financing may be markedly different. While theprovider of the contingent financing may be robust under scenarios of extreme stress for the insurer, it does notnecessarily follow that the contingent finance would be available under a less extreme scenario (from the insurer's
perspective) emanating from a different suite of changes to the external environment.
17

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events, financial institutions are usually highly correlated in terms of revaluations,recapitalisation demand and eventual failures. In the total balance sheet approach, thisinterconnected capital should be evaluated separately, with conservatism in its ability to be aresource for the insurer.
95.
In addition, supervisors should take into account any existing measures that the insureror the sector have taken to mitigate risks from these activities and evaluate effectiveness
if/when possible. Examples of these mitigating measures include:••••

Risk transfer to wider and deeper markets that may be able to handle risks more
appropriately;
The existence of central clearinghouses that mitigate counterparty risk in derivatives;
Conservative haircuts and sufficient high quality collateral held against exposures; andGeographic and economic diversification of exposures.

Table 3 shows examples of indicators that a total balance sheet approach could take into
account when assessing systemic risk.
Table 3: Examples of indicators in a total balance sheet approach19
Indicator

Type of
Indicator

Total assets/liabilities

Accounting

Size of the insurer

Net income/earnings before incometax (EBIT)/comprehensive income

Accounting

Measures of financial
performance 20

Financial ratios

Accounting

Measures of financial
performance

Liquidity indicators

Accounting

Ability of the insurer to pay
liabilities in a short period

Interpretation

Systemic risk activities
96.
Table 4 provides several examples of potential systemic activities that can be used toassess systemic impact. These examples can assist in forming indicators relevant to these
activities. For example, indicators in the form of exposures to these activities that have thespecific characteristics shown in Table 4.

19 As previously discussed, the IIM is another example of an indicator-based approach. The indicators used in thisexample can be linked with the broad categorisations of the IIM. The IIM provides further granularity and can be
another useful source of information.
20 A persistently low or negative EBIT brings into question the financial viability of the insurer.
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Table 4: Examples of potential systemic activities
Exposures/activities

Financialguarantee
insurance

Securities
Holding
lending or
Guaranteedbankrepurchaseproducts
issuedagreements 21
securities

Use of leverage

X 22

Interconnectedness withbanks and other financial
institutions
Interconnectedness with nonbank financial intermediation

X

X

Issuance of options andguarantees with exposure tofinancial market volatility

X

Low liquidity

X

Short-term funding relianceX

Wide-spread under reserving

X

X

Interconnectedness97.
In assessing the interconnectedness of an individual insurer with the broader financial
system, supervisors need to conduct proper analysis of a quantitative and qualitative nature.
Several indicators have been devised, including specific indicators, such as the amount ofderivatives written to financial institutions, the amount of securities held by an insurer andissued by other financial institutions, and statistical measures indicating the dependence of an
insurer’s financial variables to that of other insurers or the market, and the evaluation of thesystemic risk of an insurer, based on market interactions with other participants in the financial
system. Dependence on recapitalisation in stressed market conditions is also a form ofinterconnectedness with the financial market. Solvency should be analysed in this respect toevaluate the extent of reliance on recapitalisation on a sector-wide level.
98.

Examples of these indicators are presented in Table 5.

21 Non-linear reaction to volatility can come if repurchase agreements are collateralised with structured securities
such as collateralised debt obligations. Liquidity risk can emerge if the collateral assets suffer substantial haircuts
during systemic events.
22 Leverage is due to the option-like nature of pay-offs. A small change in the underlying variable (interest rate)
could have a higher influence in the value of the guarantee. When these changes correlate to financial markets (asin the case of interest rates), there is the potential for systemic risk.

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Table 5: Examples of indicators for assessing interconnectedness
Indicator

Type of indicatorInterpretation

Stock beta

Statistical-financial

Assesses the sensitivity of theinsurer’s share price to movements
in financial markets

Correlation, taildependence, Spearman
ρ, Kendall τ.

Statistical-financial

Evaluate the dependence of an
insurer’s financial variables tovariables of other insurers and of thefinancial system

Exposure in derivatives

Exposure-balance
sheet

Measure of exposure to non-linear
instruments with market volatility the
insurer is exposed

Exposures in otherfinancial institutions’capitalExposure-balance
sheet

Measure of how much an insurer is
exposed to other financial
institutions’ potential distress

Reinsurance
recoverables

Exposure-balance
sheet

Measure of exposure to reinsurance

Off-balance sheet
financing

Financial statement
disclosures

Measure of exposure to the general
financial system including shadowbanking

Wholesale funding

Exposure-balance
sheet

Measure of reliance to large
institutional investors for funding

99.
Supervisors should use these indicators in conjunction with other indicators and not in
isolation, acknowledging that some indicators are impacted by non-economic volatility. For
example, statistical measures of interconnectedness in reduced form 23 can move when thereis temporary market turmoil without the fundamentals of the insurers having changed.
100. Moreover, purely exposure measures do not take into account the inherent risk
underlying these indicators. For example, if an insurer reports significant amounts ofreinsurance recoverables, the recoverables may be with one reinsurer or be diversified
between a pool of reinsurers, which could have different risk implications from thediversification effect. Likewise, wholesale funding may differ between long-term exposuresfrom established financers as compared to short-term and opportunistic.
Interconnectedness with the real economy
101. The systemic footprint of an insurer is contingent on the macroeconomic profile of thejurisdiction(s) in which the insurer operates and with the real economy in general. Potential
macroeconomic vulnerabilities could have detrimental effects to insurers’ balance sheets andcause failures. At the same time, an insurer could be small in systemic footprint using regular

23 Here “reduced form” means without any economic model behind these models. These metrics are able toreplicate statistical relationships.

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indicators but, given the macroeconomic vulnerabilities of a particular jurisdiction, the insurer
could become systemically important.
102.
•
•
•
•

Examples of such cases include the following:
The insurer’s assets are very large compared to the jurisdiction’s GDP;
The insurer is a large financer of important infrastructure works in a particularjurisdiction;
The insurer’s failure would have triggered a bail out, in the absence of an effective
resolution regime and/or policyholder protection scheme 24; andThe insurer’s failure could cause collateral defaults from third-party suppliers,
contractors etc.

103. Supervisors should assess the systemic footprint of the insurer with respect to the sizeof the broader economy, as well as other factors within the non-financial sector. Indicators
should be devised to evaluate the systemic footprint of the insurer vis-à-vis the overall
economy (refer to Table 6).
Table 6: Examples of indicators for macroeconomic impact assessment
Indicator

Interpretation
Non-Financial Sector

Non-financial sector investments Measure of the importance of an insurer to real
held by insurer as share of total non- economy financing
financial sector investments
Employment

Measure of importance of an insurer as providerof employment

Size of pension, long-term care and Measure of an insurer’s share of coverage ofother socially sensitive coveragesocially sensitive coverage
Assets to GDP

Indicator that shows the size relative to thejurisdiction’s GDP
Public Sector

Resolvability without public funds

Qualitative indicator that reflects whether publicfunds are required to successfully resolve a failed
insurer

Recovery without public funds

Qualitative indicator that reflects whether publicfunds are required to successfully keep an insurer
as a going concern

24 Refer to ICP 12.2.3, “Resolution should seek to minimise reliance on public funding. In principle, any publicfunding used for the resolution of the insurer should be recouped from the insurance sector in a transparent manner.
The phrase “reliance on public funding” does not refer to the use of funds from policyholder protection schemes tosupport the implementation of resolution actions.”

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Assets to Government Revenue 25

Indicator that shows whether the government hasenough resources to assist a failing insurer

Limited substitutability/critical functions
104. Table 7 provides examples of indicators that can be used in the assessment of limited
substitutability/critical functions. The following examples can be tailored to each jurisdiction’s
needs:
Table 7: Examples of indicators for limited substitutability/critical functions
Indicator

Interpretation

Market power in insurance lines of Measure of whether the failure of an insurer
business (LOB) that are key for the could have an impact in the provision of
economy 26
insurance services
Amount of pension assets/healthcare
Measure of socially important coveragecoverage compared to the sector
Share of reinsurance market

Measure of how important the reinsurer is inproviding reinsurance

105. In many instances, there are overlaps between indicators of different elements ofsystemic risk. For example, an indicator under limited substitutability/critical functions may
also be valid under interconnectedness. The taxonomy of indicators presented previously is
indicative and serves as examples of how jurisdictions can implement their systemic risk
assessment methodology.
4.1.2

Assessing systemic risk using the indicator-based approach

106. When supervisors select indicators to monitor systemic risk in the insurance sector,
they should have a process of blending all the analyses into a final assessment highlighting
the extent of systemic importance of an insurer. This may be based on a binary pass/failapproach, or supervisors could also employ a proportional approach where insurers are
subject to supervisory measures without necessarily having a definite score of systemic
footprint. There are various approaches that supervisors can use to blend these variables into
one score.
Relative scoring
107. Supervisors could assign an overall score, based on prior considerations of the relative
weights of each indicator for a pool of insurers. The final score is the aggregate result ofindividual scores of each indicator. Thereafter, insurers are benchmarked relative to an
average measure, for example, the weighted/unweighted average of all indicators 27 from the
25 A comparison of assets to government revenue should only be used when other indicators signify that an insurer

may not be systemically important.
26 Ideally, the market share as an indicator of market power should be evaluated recognising that there is potential
for new market entrants. However, this is likely a subjective exercise as it is not a directly observed variable.
27 To add indicators of different units of measurement some sort of standardisation needs to occur. For example,
one can standardise them by indexing them to 100, taking percentage changes, using a Z-score (distance frommean/median in standard deviations) or ad-hoc weights.
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entire pool of insurers. Insurers’ overall score above thresholds as determined from the sample
could be deemed systemically important, while those scoring below the thresholds would not
be considered as systemically important financial institutions.
Absolute scoring
108. Similar to relative scoring, supervisors could assign scores to each indicator and blend
them into a single score. In an absolute scoring system, supervisors set scoring thresholds
according to supervisory judgement. Insurers who score above the threshold will beconsidered systemically important.
109. While absolute and relative scoring both have their merits, there are some challenges
with the measures. In the case of relative scoring, when insurers’ risk characteristics move intandem, the average will also move, hence the relative score may not reflect change despite
the prevalence of systemic risk in the financial system. In addition, the relative approach isburdened with the potential exclusion of size effects. Some systemic indicators may be large
for smaller institutions but overall they may not have a substantial impact, thus a weighting
technique could be established to improve the information content of the relative scores.
110. Absolute scores try to address the aforementioned shortcomings of relative scores by
having a hard threshold that is required for a pass/fail in systemic risk assessments. However,thresholds are subject to supervisory judgement, which could create potential conflicts with
the industry. Moreover, the time-varying nature of systemic risk may render these thresholds
obsolete in the event that systemic risk has increased or decreased significantly and perhaps
the indicators may not fully reflect the actual measurement of systemic risk.
111. As such, the assessment of systemically important insurers is not an exact science but
a blend of science and supervisory judgement. Supervisors should be able to explain
succinctly the assumptions and the rationale behind systemic risk assessment. In the IIM
exercise, scoring is predominantly based on absolute scoring, recognising that absolutescoring better reflects the changes to systemic risk over time. Relative rankings continue tobe calculated as additional information for input.
4.1.3

Reduced-form approach

112. Unlike the indicator-based approach for identifying systemically important insurers,
there is the reduced form approach, which bases the assessment on observable statisticalproperties of stock and bond prices of the insurer. Behind this methodology is the assumptionthat markets are efficient and correctly price the value of assets and liabilities.
113. Changes in the market value of assets and liabilities reflect changes in the true valueof the insurer, thus a systemically risky insurer is priced by the market based on its contribution
to some market-wide distress indicator. These reduced-form models are “objective” in thesense that there is no ad-hoc choice of variables that define the systemic footprint.
114. Reduced form models require an abundance of data to do appropriate time series
econometric analysis with publicly available data for publicly traded entities. Therefore, forinsurers that are not publicly traded, these models will not work and supervisors should resort
to more structural identification of systemic risk. Moreover, these reduced-form models usually
cover groups and not legal entities.

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115. Some common reduced-form models 28 that could be used to identify systemically risky
insurers are presented below:
MES
116. Marginal Expected Shortfall (MES) is calculated as the expected negative return of theequity of an insurer given that the market return has declined by a specific amount, usually
the 95% Value at Risk (VaR) of negative returns. A model for returns that takes into accountfat tails and extreme events is usually calibrated in order to have a mathematical expectationthat can be modelled.
117. If the model is properly estimated, it shows the sensitivity of an insurer to extreme
movements of the market. If the market is in systemic distress and the loss of equity value isworse than that of the market, there is a good chance that the insurer may be systemic. In apool of insurers, MES would be calculated per insurer and then insurers would be ranked insystemic risk according to their MES.
118. MES requires a model for returns but at the same time there are multiple models for
returns. Supervisors should try to estimate the MES using a variety of models to ensure thatthe ranking is consistent when each return model is used for the same pool of insurers.
SRISK
119. SRISK is a forward-looking, market-based measure of systemic risk that captures risks
that are pertinent to the entire financial system due to contagion and interlinkages. SRISK has
been defined by Engle and Brownlees (2017) 29 as the capital shortfall of an institution when
the whole financial sector is in distress. It assumes that the entire financial system isconstrained, or in distress, such that any single financial institution whose equity falls
sufficiently relative to its liabilities: (i) would be unable to raise additional capital; (ii) would not
be acquired by another market player, or (iii) would be unable to conduct an orderly resolution.
It also assumes that any existing debt cannot be renegotiated.
120. Using equity returns from the insurer, SRISK is defined as the expected capital shortfall
given that the market is in crisis. A prudential factor is used as a threshold where the firm
remains solvent, which in some jurisdictions is 8%.
121. Unlike MES which looks at insurers in a more abstract way (as a variable of the stock
market), SRISK takes into account the capital structure of the insurer (debt/equity mix) andthe prudential regulation. Both measures, MES and SRISK, condition their value on the market
being in distress. In the language of ICP 24 these are measures of inward risk, ie risks
emanating from the financial markets to the insurer. As with MES, insurers are then ranked
according to their SRISK value from more systemic to less systemic.
ΔCoVaR
122. ΔCoVaR is a measure that was defined by Brunnermeier and Adrian (2016) 30 anddiffers from MES and SRISK in that it ranks insurers according to their systemic footprint fromtheir outward risk. In other words, ΔCoVaR measures the impact to the market of the distress28
Asurveyonsimilartype
ofmodels
can
be
found
here:
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1983602. Also the paper of Berdin, Elia and Sottocornola(2015) analyses the use of these models in the assessment of systemic risk: https://ssrn.com/abstract=2701821
29 Engle and Brownlees (2017) https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1611229
30 Brunnermeier and Adrian (2016) https://www.nber.org/papers/w17454

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of a particular insurer. In ΔCoVaR there are two states of financial markets, the median or
normal state and the crisis state.
123. The CoVaR per state (crisis or non-crisis) is similar to the VaR of the financial market
return given a state, crisis or non-crisis. The difference between CoVaR at crisis state and the
CoVaR at the normal state is called ΔCoVaR and ranks insurers according to their contribution
to the risk of the entire financial market.
124. Thus, ΔCoVaR is a systemic risk measure of outward risk of insurers to the rest of thefinancial markets. Like MES and SRISK, ΔCoVaR ranks insurers according to the value of theindicator from more systemic to less systemic.
125. Table 8 presents a list of comparative characteristics between the three measures; noone method is deemed more favourable over the others.
Table 8: Comparison of measuresMES SRISK ΔCoVaR
Reliance on market data

X

X

Capital structure of insurer

X

Considers regulatory indicator

X

Inward risk

X

X

X

Outward risk

X

126. Reduced-form models have many advantages compared to indicator-based
approaches, however, there are some shortcomings with this approach. Table 9 summarises
some of the pros and cons of reduced form models.
Table 9: Features of reduced form models
Pros

Cons

Based on publicly available information Markets may overreact with increased
and real time data
volatility due to panics, euphorias that may
skew results
Market data can be forward looking, by Companies have no effective way to de-risk
including market expectations
based on some objective indicators. Instead
the systemic footprint and supervisory
measures are contingent on the market’s
behaviour
Calibrated according to econometric Estimation errors during calibration
techniques without noise from static
prudential information and discrepanciesof accounting standards

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Not all companies may be publicly traded,thus many of the measures may not becalculated
Relies on market information with theassumption that market data includes all
relevant factors
4.1.4

Comparison between indicator-based and reduced form identification

127. Both methods are intended to identify systemically important insurers from different
perspectives. The indicator-based method assumes that systemic risk can be identified fromusing a set of indicators that eventually filter out those insurers without a systemic footprint.
The indicator-based approach is based on supervisors’ thinking on how systemic risk isevolving. Indicator-based approaches use mostly accounting or prudential data. In this Paper,
also included are some statistical measures in the indicator-based approach (refer to Table5). The drawback of relying solely on prudential and statutory data is that data can sometimes
be backward-looking while trying to provide a view on current trends for insurers.
128. Reduced-form methods rely on market data to identify systemically important insurers.
Their premise is that efficient markets reflect all the available information and are able tocapture more information than prudential or statutory returns. For each insurer, its systemic
footprint is estimated either by the expected capital shortfall or some stock return indicator
drop under extreme market conditions. The advantage of these methods is that they reflect
objectivity in terms of variable selection, they tend to be forward-looking in nature, andaggregate market information is used instead of information from prudential returns only.
However, these methods also have some weaknesses. For example, they carry significant
non-economic volatility 31 which reduces the validity of the signal. At the same time, theyrequire market data which may not be available for many insurers. These measures have to
be calibrated to different markets creating a comparability issue between insurers listed indifferent stock exchanges. The assumption of efficient markets is strong as not all markets are
mature enough to aggregate sufficient information to identify systemic risk.
129. Another weakness with reduced form indicator is the quality of calibration. As
calibration requires econometric techniques, these techniques tend to suffer from estimation
errors and small sample effects in case of data scarcity. In addition, these methods may not
be able to capture all the nuances of an insurer in terms of particular liability and productfeatures that could have profound impact in systemic risk.
130. A good practice would be to blend both approaches to gauge the true systemic footprintof an insurer. At the same time, supervisors could run both approaches individually andcompare the results accordingly. In a perfect world where both methods have been properly
utilised and calibrated, they should provide similar identifications of systemic risk.
131. In addition to de-risking, as described below, it is advisable that systemic risk should
not be evaluated only with reduced-form models given their econometric-statistical nature
which an insurer cannot necessarily influence with its decisions. Reduced-form models can
31 By non-economic volatility we mean volatility which does not necessary reflect fundamental changes in the realvalue of financial assets but reflect temporary supply/demand imbalances which are smoothed out in a relative
short period.

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be used as an ancillary tool but should not be the sole method of determining systemic
importance. Supervisors should consider in their systemic risk assessment the fact that
insurers should be able to de-risk with their own decisions, in addition to the supervisor’s own
systemic risk reduction process. As such, reduced form models may not be able to assist in
both the insurer’s and the supervisor’s attempt to reduce systemic risk.
De-risking
132. Supervisors should have clearly defined methodologies of assessing and monitoring
the systemic importance of individual insurers. If there is a formal identification methodology
for systemically important insurers, the methodology should include a means by which an
insurer identified as systemically important can exit such identification by reducing its systemic
footprint. Hence, supervisors should communicate their assessment methodologies asappropriate, and be in regular engagements with insurers to reduce systemic footprints.
Supervisors should have established forms of communication for this purpose and provide
assistance and guidance to insurers on the workings of their thresholds and scoring
methodology.
Use of proportionality
133. Identifying systemically important insurers is a data-intensive exercise that requires
significant resources for data collection, validation and compilation while applying supervisoryjudgement. The supervisor should consider using proportionality to narrow the scope of
insurers it assesses as systemically important rather than assessing the entire insurance
sector. Criteria that could be applied include: balance sheet size, gross written premiums,
amount of technical provisions, market share, number of employees in the entire insurancegroup (including subsidiaries), etc. For example, supervisors may prefer to assess a few
insurers that have more than 50% of market share. Such quantitative thresholds should be
evaluated for several consecutive years in order to improve analyses. Supervisors may also
assess whether smaller insurers collectively or in niche markets have a systemic footprint (egcredit insurance).
134. Even if there is a cut-off period for insurers to provide data to supervisors for systemicrisk assessments, supervisors may sill encounter challenges in finding data to support their
methodology. A best-effort approach could be for supervisors to communicate with market
participants on data gaps that may be resolved through a data call. The additional datacollected can make the process more transparent by encouraging greater participation by
insurers in the exercise.
4.2

Assessing systemic importance of the insurance sector

135. Systemic risk may arise not only from the distress or disorderly failure of individual
insurers, but also from the collective exposures of insurers at a sector-wide level. Clearly, theidentification of a single systemically important insurer already provides some indication thatthe sector could pose systemic risks. However, it could also very well be that no individual
insurer is systemically risky while common behaviours of certain insurers could still causesignificant disruption to the wider financial system and real economy. Supervisors should take
into consideration this sector-wide approach when assessing systemic importance.
136.

The following methods could help assess the systemic risk in the insurance sector:

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•
•
•
•
•

Macroprudential sector-wide stress tests that focus on the interconnectedness of theinsurance sector both for inward and outward risks;
Sector-wide systemic risk assessment with the methodologies described previously forthe entire insurance sector or a large sample of it 32;
Evaluation of recovery and resolution plans;
Evaluation of the sector-wide exposure to systemically risky activities; andCross-sectoral analysis.

In addition, many of the concepts and examples of indicators described under Section 4.1 may
be equally relevant when assessing systemic importance from a sector-wide perspective.
4.2.1

Macroprudential sector-wide stress tests

137. The objective of macroprudential stress tests is to establish links between theinsurance sector in its entirety and the financial system. These tests are intended to identify
whether the insurance sector can be severely impacted by the actions of individual insurers
and other financial undertakings or whether the insurance sector can cause contagion effects
to the rest of the financial system. While traditional stress testing techniques can be applied,they may be limited in scope. 33 Network analysis may be more suitable to model direct-linksof the insurance sector with the rest of the financial system. Network analysis considers links
between insurers in the form of each insurer being a node of risk concentration and risk linking.
138. Such network analysis may be easier to perform within the insurance sector, while
expanding the analysis outside the insurance sector can be data-intensive. Simpler
approaches to network analysis could be the balance sheet approach to financial crises 34,
which was initially used for macroeconomic vulnerability analysis but can potentially be used
to assess insurers’ balance sheets.
4.2.2

Sector-wide systemic risk assessment

139. The indicator-based and reduced forms of assessing the systemic footprint of
individual insurers can be used to assess the systemic importance of the insurance sector. As
the insurance sector comprises the sum of all individual insurers, the sector may beconsidered as systemically risky itself if some insurers are identified as systemically importantin nature. However, as noted above, the aggregate impact of insurers that have not been
identified as systemically risky should also be considered when evaluating the systemic riskof the sector as a whole.
140. There is no clear-cut rule on how many insurers would need to undergo systemic risk
evaluation to ensure that the sector is well-represented. In this instance, supervisors would
need to exercise supervisory judgement and use the proportionality principle to assess
whether a large or small sample of insurers needs to be selected.

32Although the scope is different, supervisors may find the IAIS’ GME a useful source of input in terms of choosing

relevant indicators (refer to the IAIS’ GME, in particular Section 4.2).

33 Here “traditional” implies methodologies using pricing and risk models that structurally price assets and liabilities,

their interactions and risk implications.
34 https://www.imf.org/external/pubs/ft/wp/2002/wp02210.pdf
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4.2.3

Evaluation of recovery and resolution plans

141. If supervisors and/or resolution authorities have recovery and/or resolution plans 35 inplace for a sufficient number of insurers, these plans can serve as guides on the systemic risk
footprint of the sector. Recovery and resolution plans contain a wealth of information about
individual insurers and consequently evaluating them jointly can identify potential systemicrisk in the insurance sector. Furthermore, information can be gained about resolvability andpossible common behaviour to shocks.
142. Supervisors and/or resolution authority should always assess the feasibility of whether
private sector interventions could assist in avoiding the use of public funds for successful
recovery or resolution. Moreover, a failed recovery or resolution of a single institution may notnecessarily trigger system-wide effects to the broader financial system. Therefore, theevaluation of these plans should be holistic and sector-wide focused to take into account
events of a systemic nature with a high correlation of occurring in the insurance sector.
143. If required, supervisors and/or resolution authority could also take a group-wide viewof recovery and resolution plans to assess their adequacy and capital fungibility as well as
potential conflicts that may arise between different jurisdictions.
4.2.4

Evaluation of the sector-wide exposure to systemically risky activities

144. Even if individual insurers are deemed non-systemically risky, it could still be the casethat their combined activities can pose systemic risks to the insurance sector as a whole.
Supervisors need to properly identify potential systemic activities before they conduct sectorwide assessments of these activities.
145. Supervisors can then assess whether the aggregate exposure to these activities could
have systemic impact. Examples of indicators that could be employed for such evaluations
include the following:
•
•
•
•
4.2.5

Total exposure of potential systemic activities to total activities;
Sensitivity of repricing of potential systemic activities to changes in volatility, underlying
assets, economic variables or insurance technical variables 36;
Value of non-hedging derivatives and other volatility sensitive instruments; andValue of short term funding compared to total funding. 37
Cross-sectoral analysis

146. Cross-sectoral analysis links the insurance sector with other parts of the financial
system such as banks, funds, payment systems and the public sector. This analysis can bebased on tools such as network analysis that assesses the impact of cross holdings of balance
sheets between insurers and other financial institutions. This approach ensures that insurers
are assessed on both inward and outward risks through interconnectedness. As mentioned inearlier sections, cross-sectoral analysis is data and resource intensive and it may not always

35 Resolution planning is subject to an “as necessary” requirement for IAIGs in ComFrame in ICP 12; recovery

plans are required for all IAIGs in ComFrame in ICP 16 and other insurers “as necessary” in ICP 16. Although
recovery and resolution plans are useful tools, it is not expected that all jurisdictions will have this tool available (egwhen there is no IAIG).
36 This sensitivity analysis should be conducted for sectoral exposure to potential systemic activities.
37 Ideally, any cross holding of debt between insurers should prompt the supervisor to discourageinterconnectedness.
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be possible to perform detailed reviews. That said, cross-sectoral exposures can be elicitedfrom supervisory data and stress tests could be augmented with a cross-sectoral view in mind.
147. Cross-sectoral analysis is currently in the toolkit of the Holistic Framework. The crosssectoral analysis can help put into perspective insurers’ integral role in the financial sector andtheir exposures to other financial sectors as well as help provide a better grasp ofinterconnectedness across sectors. 38
4.3

Interplay between the individual insurer and sector-wide levels

148. The assessment of systemic importance done at the individual insurer and sector-widelevels should not be done in isolation, as there may be important interplays between the two.
Assessing sector-wide vulnerabilities requires the examination of individual insurers andcommonalities among insurers’ behaviour and activities. At the same time, the sector-wide
vulnerabilities can also inform supervisors about individual insurers, for instance byhighlighting insurers whose exposures develop in a different direction or at a faster pacecompared to their peers.
149. On a global level, systemic risk assessments for individual insurers has been moreestablished than that of sector-wide assessments. As a result, aside from aggregation ofindividual insurer data, stress-testing exercises and recovery and resolution plans, mostjurisdictions are still in the process of developing methods and techniques to assess sectorwide vulnerabilities. The IAIS acknowledges this development phase and supports
jurisdictions maturing their risk assessment frameworks for sector-wide analysis.
150. The 2007/2008 global financial crisis illustrated that a stable financial system is morethan the sum of its parts and that microprudential (individual insurer) assessments should becomplemented by macroprudential (sector-wide) assessments. This is particularly relevant
when there is rising interconnectedness risks between insurers and other players in financial
markets. For example, when banks and insurers (or other non-bank financial intermediaries)
are part of the same financial conglomerate or where a banking group owns insurance
subsidiaries, spillovers to the insurance entity from its parent or affiliates could become asource of systemic risk. This was evident during the global financial crisis where certain
insurance groups were supported using public funds to prevent negative impact on thefinancial system and real economy.
5

Supervisory response

5.1

Introduction

151. The objective of this section is to provide further guidance and examples to support
effective interaction between macroprudential analysis and supervisory responses (refer to
ICP 24.4). A macroprudential perspective in the development and application of supervisory
requirements is important to help limit the build-up of systemic risk and contribute to theresilience of the financial system. Depending on the outcome of macroprudential analysis,
supervisory responses may be targeted at individual insurers and/or the insurance sector asa whole (or a subset thereof). Systemic risk varies over time and supervisory responses could
be tailored to circumstances at each point in time.

38 Refer to the Holistic Framework overarching document for more information.

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152. With the adoption of the Holistic Framework, which includes enhanced and additional
standards in ICPs and ComFrame, 39 supervisors are expected to have in place a broad toolkit
to identify and, where necessary, address vulnerabilities within the insurance sector andidentify the build-up of systemic risk. Supervisors should also have the necessary flexibility to
tailor their supervisory responses to the nature, scale and complexity of their insurance sector
exposures and activities, based on their macroprudential analysis.
153. Based on the outcome of the macroprudential analysis, which includes the assessmentof systemic importance (refer to Sections 3 and 4), supervisors are expected to limit the buildup of systemic risks and mitigate those risks. Supervisory response can be twofold in nature:••

General supervisory requirements aimed at reinforcing the resilience of the insurance
sector and limiting the possibility of any disorderly failures; andTargeted supervisory requirements, focused at addressing a specific potential
systemic exposure (eg to liquidity risk, interconnectedness (macroeconomic andcounterparty exposure) or lack of substitutability).

154. While both approaches can be taken independently from each other, there can also
be a mixed approach where measures can be taken at both levels. The second approach
includes a supervisory decision to expand the application of certain measures to those
insurers that have demonstrated systemic exposure.
155. Two different types of triggers are possible: rule-based, automatic, triggers (eg thebreach of a pre-defined condition or threshold) or triggers based on supervisory discretion.
Table 10: Types of triggers

Rule-based/automatic
trigger

Pros

Cons

Transparency

Rigidity

Simplicity

Wrong signal

Reactivity
Supervisory discretion
trigger

Deep and global analysis

Lack of reactivity

Flexibility
156. In order for these measures to have successful outcomes, it is important thatmacroprudential frameworks are based on efficient and robust coordination and cooperation
processes with relevant supervisors in other jurisdictions or other financial sectors. This isespecially appropriate in the case of IAIGs, through the setting up of crisis management
groups (refer to ComFrame integrated in ICP 25 (Supervisory Cooperation and Coordination)).
These may include:••

Sharing the results of macroprudential analysis;
Exchanging on the necessity of applying preventive or corrective measures; and39 For an overview of these standards, refer to Section 3 of the Holistic Framework overarching document, notably

Table 1, as well as ICP 24.4.4.

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•
5.2

Providing appropriate guidance on the analysis of supervisory requirements: ERM,
recovery and resolution plans.
Types of supervisory responses

157. Many supervisory measures described in this section are essentially microprudential
instruments that are applied with a macroprudential perspective in mind. Indeed,microprudential requirements can mitigate potential spillover effects from the distress or
disorderly failure of an individual insurer or from the common exposures or behaviours of a(subset) of the insurance sector, therefore contributing to the overall resilience of the financial
system. Macroprudential analysis should provide guidance and direction in conducting morein-depth and more targeted analysis of microprudential requirements to be applied.
158. Supervisors should consider modifying the granularity and the frequency of
requirements. These can take the shape of requirements, such as the strengthening of the
ERM framework, additional arrangements (more statements, more frequent supervisory
reporting or disclosures), or results from decisions (incentive or prescriptive), enhanced crisis
management and planning, and preventive or corrective measures.
5.2.1

Strengthening the ERM framework

159. As described in the introductory guidance of ICP 16 (Enterprise Risk Management for
Solvency Purposes), requirements on ERM are primarily microprudential in nature (aimed atenhancing the sound operation of the insurer and ensure the adequate protection ofpolicyholders) but, collectively practiced in the industry, it also supports the operation andfinancial conditions of the insurance sector as a whole.
160. The outcomes of macroprudential analysis should provide direction to supervisors
when setting requirements and increasing or decreasing the intensity of such requirements. If
a potentially systemic exposure is identified by trends in certain risks and activities in themacroprudential analysis, supervisors should require insurers to strengthen their ERM
framework. 40 The next subsections provide a non-exhaustive list of examples of suchrequirements, related to counterparty risk and liquidity risk in particular.
161. The results of macroprudential analysis could be useful for guiding the expectations of
ERM as well as assessing its relevance and robustness. For example, stress testing or
scenario analysis can be helpful to better understand, assess or address concerns raised bymacroprudential analysis. This could also be done by specifying criteria or analyses as part ofthe supervisory risk assessments to achieve effective supervision and consistency acrossinsurance groups. Supervisors may also need to communicate with other financial services
supervisors on the results of the analysis to address any potential spillover effects that could
arise.
162. Macroprudential analysis is the most appropriate tool to identify and measureinterdependencies and the concentration risk in the financial sector. Based on the risks theassessment may highlight, supervisors may require insurers to strengthen their risk appetitestatement or to establish a counterparty risk appetite statement to define more stringent limits.

40 In particular, in deciding whether it is necessary to require more detailed requirements, the supervisor shouldtake into account the nature, scale and complexity of the insurer’s activities that lead to increased risk exposure aswell as the risk amplification effects related to the size of the insurer.

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The Application Paper on Liquidity Risk Management also provides a range of measures that
could be used to address liquidity concerns raised by macroprudential analysis.
5.2.2

Crisis management and planning

163. Crisis management and planning tools, such as recovery and resolution planning, areaimed at reducing the likelihood and adverse impact of a disorderly failure of an insurer. It isgood practice for supervisors to require recovery and resolution plans 41 at least for those
insurers that it has assessed to be systemically important.
164. Macroprudential analysis is particularly relevant to determine the scope of applicationof the recovery and resolution plans. These analyses may help to identify the most
systemically risky activities and thus for which insurers this requirement is needed.
165. Macroprudential analysis is also a valuable tool to assess the quality and feasibility of
the recovery and resolution plans. It may help to ensure that the recovery solutions envisaged
are sufficiently robust to address any spillover effect.
166. The concepts for both recovery and resolution planning are described in ICP 12 (Exitfrom the Market and Resolution) and ICP 16 (Enterprise Risk Management for Solvency
Purposes) and further guidance is provided in the Application Paper on Recovery Planningand the Application Paper on Resolution Powers and Planning. These Papers provide
guidance on the decision of the supervisor and/or resolution authority on the need for theseplans, as well as a description of the main elements of such plans.
5.2.3

Preventive and corrective measures167. In the event that systemic risk materialises, or there are signs of the build-up of
systemic risk based on macroprudential analysis, supervisors should have at their disposal a
sufficiently broad set of powers. ICP 10 (Preventive Measures, Corrective Measures andSanctions) puts forward various measures to address supervisory concerns. The measuresdescribed in ICP 10.2 may also be applied if an insurer or group of insurers, with common
exposures, operate in a manner that could pose a threat to financial stability. The following
are non-exhaustive examples of supervisory measures that may be considered:•

Restrictions on business activities:-•

Prohibiting the insurer from issuing new policies or new types of product;
Withholding approval for new business activities or acquisitions; andRestricting the ownership of subsidiaries.

Directions to reinforce the insurer’s financial position, such as:-

Requiring measures that reduce or mitigate risks (for example, restricting
exposures, through either hard or soft limits, to individual counterparties, sectors,
or asset classes);Requiring an increase in capital; and41 Recovery plans are required for IAIGs and other insurers as necessary; resolution plans are required for IAIGs

as necessary. Recovery plans are developed by the insurer, and identify in advance options to restore the financial
condition and viability under severe stress. Resolution plans are developed to identify, in advance, options forresolving all or part(s) of an insurer to maximise the likelihood of an orderly resolution, the development of whichis led by the supervisor and/or resolution authorities in consultation with the insurer in advance of any
circumstances warranting resolution.

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•

Restricting or suspending dividend or other payments to shareholders.

Other powers, including:-

Requiring the insurer to prepare a report describing actions it intends to undertaketo address specific activities the supervisor has identified, through macroprudential
surveillance, as potentially posing a threat to financial stability;
Temporarily delaying or suspending, in whole or in part, the payments of theredemption values on insurance liabilities or payments of advances on contracts;
Lowering the maximum rate of guarantees for new business or introducing
additional reserving requirements; orIncentivising the use of a system-wide lending facility, when available, for marketwide liquidity issues extending to insurers.

168. In some cases, supervisors may require the development of a report that would aim atpresenting, in a coherent and summarised manner, all applicable measures that the insurer
intends to undertake in order to address macroprudential concerns. In that sense, it is the least
intrusive measure, as it allows insurers to first develop their own action plan. If supervisors
are not satisfied with the report or the progress made by insurers to implement it, supervisors
are expected to take additional preventive or corrective measures accordingly.
169. It is important for supervisors to document and communicate to insurers the precise
assessment of potential systemic exposures or activities that led to the requirement. While
insurers should be able consider their inward risk and vulnerabilities (as part of the ERM), it
may be more difficult for insurers to examine how their activities or vulnerabilities may affectothers, and hence, may lead to a systemic risk.
170.

As an example, such a report could include the following elements:

•
•
•
•

Additional elements to its liquidity management planning;
Additional elements to their recovery plan;
An outline of intra-group financial relations; andA description of linkages to other measures.

6

Transparency

6.1

Importance of transparency

171. As described in ICP 24.5, the supervisor is required to publish relevant data andstatistics on the insurance sector. As described in ICP 24.5.1, it may enhance market
efficiency by allowing market participants to make more informed decisions, reduce the costto the public of acquiring insurance sector information and may serve as a market disciplining
mechanism by facilitating comparisons of an individual insurer to the sector as a whole. Before
publishing data and statistics, the supervisor should consider any potential confidentiality or
sensitivity associated with such information.
172. Transparency may in some ways be seen as a macroprudential instrument itself. For
example, communicating macroprudential concerns may have a preventative effect bytriggering certain behaviour that limits the further build-up of the systemic risk or vulnerability.
Also, through external communication, supervisors should explain the objectives, strategy andprocesses of their macroprudential supervision. Transparency not only reinforcesaccountability of supervisors, it may also contribute to the effectiveness of macroprudential
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supervision itself, by enhancing its predictability and by managing stakeholders’expectations. 42
6.2

Possible macroprudential reporting

173. Transparency may be achieved by publishing relevant insurance data by supervisors.
Insurance data and statistics can be published by supervisors on their official webpage
allowing each user of the information to perform comparative analysis of individual insurers
with aggregated indicators of the insurance market.
174.
•
•
•
•
•
175.
•
•
•
•
•
•
•

For macroprudential purposes, supervisors may publish:
Objectives and responsibilities, goals and priorities and associated activities;
Data collected on the insurance sector necessary for macroprudential supervision(both quantitative and qualitative);
Results of the insurance sector analysis;
Results of the systemic importance assessment; andSupervisory responses based on macroprudential concerns.
Macroprudential reporting by supervisors may take the following forms:
Financial stability report;
Risk dashboard (heat-map, or other format of monitoring key market indicators);
Macroprudential database (containing datasets of indicators or data elements relevant
for macroprudential purposes) 43;
Reports on insurance sector stress test results and its specifications (methodology);
Lists of supervisory measures taken in relation to problem or failed insurers;
Lists of supervisory measures in relation to any relevant risks materialising; orOther relevant analytical reports on current risks of the insurance sector.

176. As described in ICP 24.5.2, in cases where supervisors provide other parties (eg thegovernment statistical office) with adequate means for publishing data on the insurance sector,
they should take into account principles of outsourcing supervisory activities covered in ICP
2.11.
6.2.1

Financial stability report (FSR)

177. A financial stability report is an integral part of financial stability communication andmay be a relevant tool for increasing transparency on macroprudential supervision issues in
the insurance sector.
178.
•
•
•
•
•

An FSR may include the following information on the insurance sector:
Key market developments affecting the insurance segment;
Overview of the insurance segment (its solvency, profitability etc.);
Main trends in the insurance and reinsurance segments;
Results of quantitative and qualitative insurance sector analysis;
Stress testing results;

42 For more details please refer to BIS papers on objective setting and communication for macroprudential policies:
https://www.bis.org/publ/cgfs57.pdf; https://www.bis.org/publ/arpdf/ar2018e4.pdf
43 An example is the Macroprudential Database of the Statistical Data Warehouse, European Central Bank.
https://sdw.ecb.europa.eu/browse.do?node=9689335

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Major outward and inward risks identified;
Any supervisory actions taken to maintain the stability of the insurance sector during
the reporting period; andForecasts for the future development of the sector.

•••

179. The information presented in an FSR for the insurance sector may be divided by lifeand non-life segments for better granularity. If an FSR is published, it should be on a regularbasis.
Examples of FSR

6.2.2

•

In Russia, according to the Federal Law No. 86-FZ dated July 10, 2002, the Central
Bank of the Russian Federation (Bank of Russia) publishes the FSR at least twicea year. Commonly, each publication of the FSR includes a section “Risks of
insurance companies” comprising an overview of the Russian insurance market
and its risks, both for life and non-life segments.

•

De Nederlandsche Bank (DNB) publishes the FSR twice a year withmacroprudential indicators and statistics as well. In it, DNB raises awareness of
systemic risks among stakeholders, providing analysis of the current developments
within the financial sector and their implications to the financial stability. One of thetools is a risk map that presents a schematic overview of the main risks, including
the vulnerabilities of insurers and pension funds. 44•

In the United States, the Financial Stability Oversight Council (FSOC) publishes anannual report to address significant financial market and regulatory developments,
including insurance and accounting regulations and standards, along with anassessment of those developments on the stability of the financial system.
Other forms of macroprudential reporting

180. If supervisors perform top-down or bottom-up stress tests in the insurance sector, they
may publish an insurance stress test report. This report could cover the jurisdiction’s stresstesting framework, including the methodological approach of the exercise, stress test results
and key findings that describe the impact of stress scenarios on the insurance sector as well
as next steps for stress testing enhancements.
181. In response to any relevant risks materialising from the stress tests, supervisors may
release public statements covering recommendations, preventive and corrective measures(refer to Section 5.2.3) aimed at mitigation of the build-up of systemic risk. For example,
supervisors could issue or update recommendations on dividend distribution andremuneration policies, advising that supervisors themselves will closely monitor compliancewith these recommendations. 45 Additionally, supervisors may conduct a survey on complianceof insurers with issued recommendations and publish the results (refer to ICP 3 (Information
Sharing and Confidentiality Requirements)).

44 An example can be found here: https://www.dnb.nl/en/news/dnb-publications/financial-stability-report/index.jsp

45 An example is the statement on dividends distribution and variable remuneration policies in the context of Covid19 issued by EIOPA in 2020: (https://www.eiopa.europa.eu/sites/default/files/publications/statement-on-dividenddistribution-april2020.pdf)

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Annex 1

Example indicators and data elements

This annex provides a non-exhaustive list of relevant indicators and data elements that could
be analysed for macroprudential purposes, in support of the implementation of ICP 24.1. Someof these indicators and data elements may exist in publicly available market data andsupervisory reporting data.
1. Macroeconomic data examples to assess the exposure of the insurance sector to
economy-wide factors
a. Solvency• solvency capital ratio (insurer and• changes in interest rates
individual level – life and non-life)•changes in GDP growth, financial
cycle

•

changes in sovereign and major
indices credit default swap (CDS)
spreads•

changes in inflation•

changes in real estate valuations•

changes in equity valuations•

changes in equity prices (local andsectoral)•downgrades in credit ratings andoutlooks (fixed income portfolios)•

duration mismatch 46•

financial strength ratings•changes in exchange rates (impact
on valuations)•insurance outlook (industry-wide):
life insurance and property andcasualty•changes in volatility indices•changes in combined ratio (lossratio plus expense ratio)b. Profitability• changes in financial revenue(impairments, investment losses
from higher risk aversion•

return on equity•

change in reinvestment rates versus
guaranteed rates•

changes in corporate dividends•

changes in new lines of business•changes in claims (life and non-life)•changes in premium income ofdifferent segments•changes in banking sector
profitability•changes in corporate sector
profitability

46 Duration mismatch occurs in the event of changes in the interest rate where when a financial institution borrows

funds, using short-term loans or bonds but lends out these funds for a longer term.

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performance of equity prices andexpected profits of the national
companies and the belonging area
(insurance or non-insurance
activities)•changes in unemployment andcorporate solvencies•changes in paid-up rates•

changes in gross and net premiumincome•changes in credit-to-GDP gap•

changes in household debt as apercentage of disposable income•changes in household debt service
ratio

•

growth in household disposable
income2. Microeconomic data examples to identify variances in insurance trends for more indepth monitoringa. General data
• market share of the insurance sector • changes in insurance pricing andunderwriting performances(individual and industry)•changes in expenses•

cancellations and policy lapses•

changes in equity value (capital andsurplus)•changes in asset allocation (bonds
equities, cash, deposits, collective
investment schemes etc.

•

changes in shareholder and policy
dividends•

changes in capital requirements•

capital contributions to shareholders•

changes in interest rate and inflation•

changes in morbidity and mortality •rateschanges in assets and liabilities(refer to 3a and 3b)•

Jaws ratio 47

changes in underwriting clauses•changes in legal coverages•

b. Data relating to specific and unforeseen events, such as pandemics, natural
disasters, cyber-attacks: (individual and industry)•changes in the frequency andseverity of events•changes in the solvency position•changes in the liquidity position•changes in profitability (realised
gains or losses)•changes in assets•changes in asset allocation•

collateral requirements as a result ofchanging market conditions•

changes in liabilities

47 The Jaws ratio measures the rate at which expenses grow relative to premiums

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switch to marked-to-model
valuations following illiquid markets•changes in operations and business
continuity

3. Liquidity risk data examples to detect possible liquidity mismatches between assets
and liabilities (individual and sector-wide level)a. Assets side: (insurance and non-insurance)• degree of liquidity of assets• ratio of bank loan funds in asset(insurance liquidity ratio)
portfoliochanges in sovereign bondinvestmentschanges in investment funds•changes in equity investments•changes in asset composition(equities, debt, cash)•

decrease in corporate debt
investments•changes in leveraged loans•changes in collateralised loan
obligations
revaluations (real estate andequities)•changes in financial guarantees•

deterioration in credit quality ofassets (due to credit rating
downgrades)•changes in derivatives holdings•

changes in securitised assets•

average duration of assets•changes in level 1, level 2 and level 3
assets (Fair Value Hierarchy)•changes in sovereign bond yields
and spreads•

changes in interest rates•

higher market volatility (VIX), higher
margin calls on options orderivatives•••

b. Liabilities side: (insurance and non-insurance)• changes in claims (life and non-life), • changes in claims (due to lower
business interruption insurance,
economic activity in motor, aviation,
pandemic insurance
marine insurance)•changes in net and gross incurredclaims•insurance claim triangles 48•

changes in net and gross written
premiums (life and non-life)•changes in direct premiums written
for LOB49

48 An insurance claims triangle is a way of reporting claims as they develop over time. Typically, insurance claims
get registered in a particular year and payments take place over several years.
49 In example, direct premiums written for certain LOB may be of particular interest: event cancellation, work
stoppage, travel insurance, mortgage guarantee, financial guarantee, export credit coverage, aviation coverageand marine coverage.

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•changes in surrenders and lapses•

total borrowing by insurancecompanies (short term and long
term)

•

average duration of liabilities•

changes in maturity or redemption
structure of non-insurance liabilities•

short term debt issued by insurers•

financial guarantees on life insurance•

line of credit or letter of credit •drawdowns

litigation and reputational risk

4. Counterparty risk examples to assess the probability of default• capital adequacy ratio of insurers• concentration: insurance sectors
assets and liabilities holdings by lifeand non-life insurers•

measuring credit quality of insurers •(non-performing loans, share prices,
implied CDS and CDS spreads,
market capitalisation, changes inshort term and long term debt, loans
loss reserve)

expected default frequencies
measure credit risk•

profitability of insurers•

derivatives holdings(local and foreign
holdings)•

specific sectors holdings
financial or real estate),
geographical areas

(eg •
and

market concentration risk (holding ofequities and debt – local and foreign)•reinsurance coverage (with local and •foreign reinsurers)

cross-sectoral holdings of otherinsurers, banks (and money-market
funds), other financial institutions andcorporates

5. Macroeconomic exposure data examples to monitor to assess the insurance sector’svulnerability to macroeconomic shocks (life and non-life)• changes in GDP growth• unemployment levels•

inflation rate•interest rate•savings rate•changes in equity prices•

changes in bond yields

In addition, there are other reports available that supervisors may find helpful when designing
data collection exercises. As an example, the World Bank has published a report on The Useof Financial Health and Stability Indicators in Insurance Supervision, specifically aimed at
supervisors in economies with less developed insurance markets. This report is not only aimed
at supporting macroprudential supervision, but also microprudential supervision. This could
be very useful for supervisors in emerging market and developing economies.
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toAnnex 2

Example risk dashboards

South African Reserve Bank Heat Map
The South African Reserve Bank (SARB) monitors a wide range of sectors, asset markets andfinancial intermediaries for signs of possible systemic risk. No single indicator can provide acomprehensive view of these y risks, thus a multitude of quantitative tools is used to support
a qualitative assessment of risk. An example of one such quantitative tool used to assess
potential risks and vulnerabilities is a financial stability heat map (Figure 1) which is an
important input into the SARB’s financial stability monitoring process. The heat map is a visual
depiction of various risk indicators and provides an easy-to-interpret overview of the evolutionof risk across different parts of the economy.
The relative simplicity of the heat map, however, presents both pros and cons. On the one
hand, it provides a broad, consistent view of changes in certain financial variables over time.
On the other hand, it only includes a subset of financial variables, and it simply aggregatesthese variables without assigning weights to them. Therefore, risk build-up in other areas ofthe economy might be missed. The construction of three different versions of the heat map,
one with all the individual indicators, one with the different sectors and one with the broad risk
or valuation categories, tries to mitigate the possibility of missing certain indicators to someextent. Also, trend changes in some variables can occur, which may send misleading signals
in the heat map (many indicators are assumed to be mean-reverting). Furthermore, someindicators might be double-sided in that risk build-up or rising vulnerability occurs when an
indicator is both increasing and decreasing which could possibly make the interpretation of
the specific indicator more difficult.
It is therefore important to use the heat map alongside various other risk identification tools fora more comprehensive view of potential risks to financial stability.
Figure 1:

Financial stability sectoral heat map

Source: SARB

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The heat map is a diagram with data values represented by colours. It provides a compact
and easy-to-grasp depiction of a large amount of data, making it easier to identify patterns andtrends. 50 Following the methodology of Arbatli and Johansen (2017), 51 raw indicators aretransformed so that the increases in each indicator can be interpreted as an increase in risk,
with the exclusion of possible double-sided risks. This entails normalising each indicator sothat all the observations are in the range of 0-1. 52 If a normalised indicator equals 0.6, forexample, it means that 60% of the historical values of the indicator are less than or equal tothe most recent observed value. Indicators are aggregated into categories. The category
average is then mapped to a continuous colour bar, where 0 is green and 1 is red.
The South African heat map currently consists of 12 categories:
i)
ii)
iii)
iv)
v)

vi)

vii)

viii)
ix)

The residential real estate market category consists of two indicators: the annual
growth rate of the Standard Bank House Price Index, and mortgage loans as a shareof total loans.
The bond market consists of the spread between the SA 10 and 2 year bond and the
SA 10 and 5 year bond, the sovereign CDS spread and the bond spread between the
US and SA 2 year and 5 year bonds.
The external sector comprises of the real effective exchange rate of the exchange rateof the rand (with 20 trading partners) and the one -month exchange rate volatility.
The equity market consists of two indicators: the JSE prices gap and the JSE priceto-earnings ratio.
The global investor sentiment category consists of the Chicago Board Options
Volatility Index (VIX) as a one-sided and double-sided indicator of risk appetite; Merrill
Lynch Option Volatility Estimate (Move Index), US Dollar Index, Commodity Research
Bureau Index, US 10 year Government Bond and MSCI Emerging Markets Index.
The banking sector category consists of five indicators, namely: averages for thesector-wide value of assets to equity, impaired advances to gross loans and advances,the liquidity coverage ratio (LCR), the assets-to-GDP gap, and the credit-to-GDP gap.
This category provides a composite measure of the buffers in the banking sector toboth solvency risk (the equity buffer) and liquidity risk (the LCR), as well as anindication of the level of credit risk building up in the system.
The insurance sector category comprises five indicators, all sector-wide, namely: theassets-to-GDP gap, the combined ratio 53 (non-life), growth in gross written premiums(life and non-life), the individual lapse ratio (life), and the solvency capital requirement(SCR) (life and non-life). This category provides a composite measure of the degreeof risk taking by insurers, the growth in new business underwriting profits, and buffers
in place to absorb an adverse shock.
The pension fund sector is represented by the assets-to-GDP gap.
Other financial institutions comprises of the assets-to-GDP gap.

50 L Wilkinson and M Friendly, 2009, ‘The history of the cluster heat map’, The American Statistician 63(2), pp 179–

184.

51 E C Arbatli and R M Johansen, 2017, ‘A heat map for monitoring systemic risk in Norway’, Norges Bank staff

memo 10.
52 This normalisation is done on the basis of each indicator’s empirical cumulative distribution function.
53 The combined ratio is an indicator of the underwriting profit. It is calculated as net claims and expenses incurred
divided by net premiums written.
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x)
xi)
xii)

The household sector category consists of three indicators: the debt-service
cost-to-disposable-income ratio, the debt-to-disposable-income ratio, and thedebt-to-GDP ratio.
The corporate sector category comprises of three indicators for the non-financial
corporate sector: the debt-to-GDP ratio, the debt-to-net-operating-profit ratio, and theinterest coverage ratio. 54
The sovereign sector category makes use of a single indicator: the gross government
debt-to-GDP ratio.

The heat map is a ‘living’ tool and is updated from time to time in line with international bestpractice.

54 The interest coverage ratio demonstrates the degree to which an entity’s EBIT cover its annual interest expenses.

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EIOPA Risk Dashboard (RDB)
BackgroundAs part of the European legislation, EIOPA as well as the other European Supervisory
Authorities (ESAs) and the European Systemic Risk Board (ESRB) are called upon to “develop
a common set of quantitative and qualitative indicators (i.e. a risk dashboard) to identify andmeasure systemic risk”. The legislation further stipulates that these dashboards should beconstructed in cooperation between the ESAs and ESRB. In response to this requirement, theESAs, together with the ESRB and the European Central Bank have determined a set ofgeneral features for all dashboards to follow:--

Each Risk Dashboard will be constructed based on the same set of risk categories:
macro risk, credit risk, market risk, funding and liquidity risk, profitability and solvency
risk and risks resulting from interlinkages and imbalances. Furthermore, each
institution has the option to add categories to allow for sector specific risks (e.g.
insurance (underwriting) risk).
All Risk Dashboards should be constructed on a flexible basis in order to allow eachauthority to reflect the most imminent risks identified.

RDB Structure
The EIOPA RDB is based on a large set of indicators grouped into seven risk categories plus
an additional category showing how the insurance industry is perceived by financial markets.
The risk categories are broadly aligned with those used by the other ESAs and by the ESRB
and can be listed as follows:
1. Macro risks: Macro risk is an overarching category affecting the whole economy.
EIOPA’s contribution focuses on factors such as economic growth, state of themonetary policies, consumer price indices and fiscal balances which directly impact
the insurance industry. The indicators are developed encompassing information on themain jurisdictions where European insurers are exposed to both in terms ofinvestments and product portfolios.
2. Credit risks: The category measures the vulnerability of the European insurance
industry to credit risk. To achieve this aim, credit-relevant asset class exposures of the(re)insurers are combined with the relevant risk metrics applicable to these asset
classes. For instance, the holdings of government securities are combined with thecredit spreads on European sovereigns.
3. Market risk: Most asset classes are assessed by analysing both the investment
exposure of the insurance sector and an underlying risk metric. The exposures give a
picture of the vulnerability of the sector to adverse developments. The risk metric,
usually the volatility of the yields of the associated indices, provides a picture of thecurrent level of riskiness. The risk category is complemented by an indicator that
captures the difference between guaranteed interest rates and investment returns.
4. Liquidity and funding: This category aims at assessing the vulnerability of the European
insurance industry to liquidity shocks. The set of indicators encompasses the lapse
rate of the life insurance sector with high lapse rates signalling a potential risk, holdingsof cash & cash equivalents as a measure of the liquidity buffer available, and theissuance of catastrophe bonds, where a very low volume of issuance and/or highspreads signals a reduction in demand which could form a risk.
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5. Profitability and solvency: The category scrutinises the level of solvency andprofitability of the European insurance industry. Both dimensions are analysed for theoverall industry (using group data) and include a breakdown for the life and non-life
companies (using solo data). In detail, the solvency level is measured via SCR Ratios
and quality of own funds. Standard profitability measures for the whole industry arecomplemented by indicators such as the combined ratio and the return on investments
specifically applied to the non-life and life industry respectively.
6. Interlinkages and imbalances: In this section various kinds of interlinkages areassessed, both within the insurance sector, namely between primary insurers andreinsurers, between the insurance sector and the banking sector, as well asinterlinkages created via derivative holdings. Exposure towards domestic sovereign
debt is also included.
7. Insurance (underwriting) risks: Indicators for insurance risks gross written premiums ofboth life and non-life business are an important input. Both significant expansion andcontraction are taken as indicators of risks in the sector; the former due to concerns
over sustainability and the latter as an indicator of widespread contraction in insurance
markets. Information on claims and insurance losses due to natural catastrophes also
contribute to this risk category.
8. Market perception: This category encompasses the financial markets’ perception of
the healthiness and profitability of the European insurance sector. For this purpose,
relative stock market performances of European insurance indices against the total
market are assessed, as well as fundamental valuations of insurance stocks(price/earnings ratio), CDS spreads and external ratings/rating outlooks
Data Sources
The Solvency II reporting provides information both at solo and group level. Groups represent
the most systemically relevant institutions in the European insurance industry, both from anentity perspective (i.e. size, interconnectedness, complexity) and from an activity perspective(i.e. wide spectrum of activities covered). Solvency II data are complemented by publicly
available market data.
Methodology
The level of each indicator is represented by a discrete score ranging from 1 (low risk) to 10(very high risk). The risk scores are used discretely at the level of each risk indicator, buttransformed to non-discrete scores at the level of each risk category, i.e. after aggregation.
Final scores are transformed into colour codes based on four colours to represent the final
level of the risk. Changes over time of the scores (quarter-on-quarter variation) arerepresented by arrows.
Thresholds used to transform risk levels to discrete risk scores are calculated according to
specific guidelines based on: i) Historical distribution (where a sufficiently long and significant
time series is available); ii) Pre-defined (where indicators come with a regulatory defined
threshold – e.g. SCR ratio); iii) Cross-sectoral distribution (where time series are not available).
Risk scores of each indicator are aggregated at risk category level through the use of weights
defined taking into account the relevance of the indicator for the category and its correlation
with other indicators within the category.

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Presentation
The Dashboard is published on a quarterly basis and it is includes a synthetic view of the levelof risk and the trend compared to the previous quarter for each risk category accompanied by
the narrative of the key finding.

The overview is complemented by a comprehensive list of the evolution of each indicatorgrouped by category.

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Annex 3

Example topics for analysis

Certain topics may require in-depth analysis to take into account the needs of supervisors
while considering industry vulnerabilities and differences between jurisdictional frameworks.
A non-exhaustive list of topics for which supervisors can perform in-depth analysis may
include:•Liquidity monitoring•

Derivatives monitoring•

Reinsurance analysis•

Interconnectedness

Further analysis could be done and includes impacts arising from emergency situations(health, environmental, geopolitical, etc.), such as the recent Covid-19 crisis.
These additional analyses could investigate, in more detail, the effects that certain strategic
choices can generate for the stability of the sector or, more generally, of the financial system.
Liquidity monitoring
The periodic analysis of liquidity could be included in trend analysis focused on elements that
could identify liquidity risk. This analysis method could help supervisors monitor liquidity risk
which, although less important than in the banking context, is still recognised as a potential
source of systemic risk in the insurance sector. In some instances liquidity can represent anelement requiring greater attention when taking into account the state of financial markets andany liquidity demands resulting from social or health issues (such as the current
epidemiological emergency). Supervisors should assess insurers’ exposure to liquidity risk by
taking into account both inward and outward risks.
Supervisors may carry out the analysis of liquidity on an "ordinary basis” with agreed
periodicity (for example annual, biannual, quarterly or when necessary) or with a “higher
frequency” that takes into account the availability of data and proportionality.
The liquidity monitoring could be based on a set of indicators that supervisors track (including
a supranational context) and are representative of liquidity conditions. The examination,
depending on proportionality and availability of data, could be conducted on the entire national
insurance market or on a representative sample. The elements of attention could include those
identified in the Application Paper on Liquidity Risk Management (“Liquidity Paper”); although
the perspective of the mentioned Liquidity Paper is different, it can provide ideas for specificinsights into the liquidity profiles attributable, more generally, to the insurance sector.
Periodic monitoring of liquidity can be based on data that the supervisor has at its disposal,
by periodic reporting (eg financial statements) or by ad-hoc requests that are solicited by thesupervisor to the entire market (or to a sample of it).
Supervisors could also closely monitor some factors represented in the Liquidity Paper, that
could influence the liquidity risk, including: insurable events, policyholder behaviour, funding
structure, transferability of assets and liquidity impairments on capital markets. Severe stressscenarios, including from a macroprudential perspective, should be helpful in considering
potential capital market-related devaluations that could further hinder market responsiveness.
Severe stress scenarios should be useful to consider potential correlated impairments tocapital markets that may further hinder an insurer’s ability to manage a liquidity event. The
analysis should allow the interaction between liquidity risk and losses on investments.

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Periodical liquidity monitoring could enable supervisors to detect, in a timely manner, crucial
information on adverse market circumstances, such as:
The value of unrealised gains/losses on investments; andThe assessment of the asset values’ trend linked to the development of the wholemarket situation (ie spread level).

••

Regarding the potential elements to be monitored, supervisors can perform analyses ofdifferent levels of depth:a) Can track a set of indicators that provide the liquidity situation of the sample/insurance
market.
For example, periodical (eg monthly) data collection allows the timely monitoring of
cash inflows and outflows used as proxies of liquidity strains in the life sector.
-

Claims ratio = claims/premiums
Lapse ratio =lapses/premiums
Cash and equivalents/total assets
Liquid assets/total assetsb) Can conduct a more in-depth analysis and identify indicators, calculated both at market
and individual level, structured in "main areas" on which it assesses liquidity risk. Each"main area" is analysed by suitable indicators.
Examples that may be identified for liquidity monitoring, among those mentioned in
the Liquidity Paper:•

Liabilities – aspects related to the redemption options included in the contracts.

•

Assets – assessing the degree of liquidity of the assets held by the insurer(sample) and considering the amount of cash and deposit securities considered"liquid” on the basis of criteria shared internationally, etc.

•

Interaction between assets and liabilities – assessing liquidity risk by looking
jointly at the assets and liabilities of companies (sample) according to theirduration gap.

•

Effects of liquidity risk connected to activities that are not strictly insurance –deriving for example from short-term financing, from investments in derivatives orfrom other mechanisms.

Interconnectedness
This analysis could be performed to evaluate systemic risk related to the interconnectedness
among the different players in the insurance sector. The analysis may consider the exposures(eg bonds and equities) of a particular insurance group to others (refer to Section 4).
Derivatives monitoring
This analysis may be done with periodical monitoring (eg semi-annual monitoring) aimed atverifying potential vulnerabilities in the insurance sector related to the use of derivative
instruments.
Reinsurance analysis
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This analysis is performed to identify potential vulnerabilities and/or insurance systemic risks
that could arise from the use of reinsurance. There may not always be complete data (datacould come from different institutions in different jurisdictions with different reporting systems).
Adjustments could be required, for example:•••

The codes of reinsurers are amended according to the information available on
Supranational Supervisor and Global LEI databases;
Data provider Reuters is used to check the external ratings of listed reinsurers; orCross-checks are carried out in the jurisdiction and external rating information provided
by each institution.

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Annex 4

Example of ORSA analysis

The Own Risk and Solvency Assessment (ORSA) requires an analysis of the main risks andsolvency position of an undertaking to be performed on a current and forward-looking basis.
The regulatory framework may allow the use of the ORSA as both a microprudential andmacroprudential supervisory tool. A specific report could be generated for supervisors toanalyse risks from both these perspectives.
From a macroprudential perspective, the ORSA shall form an integral part of the undertaking's
business strategy on an ongoing basis in its strategic decisions. The ORSA could assist
supervisors to identify the main factors, assumptions and strategies used at a sectoral level
for the estimation of overall solvency needs from a forward-looking basis. For this purpose, it
could be useful for supervisors to act preliminary on the regulatory framework to prescribe theinformation to be analysed. Supervisors could provide a scheme to establish a process toanalyse the ORSA but the insurers would remain free to define the content of the ORSA.
For example, the ORSA scheme could include a set of specific information, such as:a) Risk strategy and risk profile of the undertakingb) ORSA governance•

Reconciliation, if different, between strategic plan/capital management plan/ORSA•

Role and responsibilities (Board, Committees, top management, key functions andother function involved in ORSA process)•Internal reporting procedure on ORSAc) Methods and assumptions
Methods and assumptions for risk assessment, also from a forward-looking
perspective and for Overall Solvency Needs, both for quantifiable and non-quantifiable
risks. Details on stress test and reverse stress tests are included in the ORSA.
Aspects included: Time horizon and Sovereign risk.
d) Outcomes, conclusions and internal use: such as outcomes with and without LongTerm Guarantee Measures (LTGM) in terms of Technical Provision, Capital
Requirement, solvency ratio and Own Funds + self-assessment on ORSA
Example form for ORSA macroprudential analysis by IVASSARisk profile

1
2
3
4

risk appetite
limits for risk appetite
limits for single risk
criteria to calculate risk appetite

B

Governance ORSA

1
2

scope of ORSA
timing reconciliations with strategic plan, capital plan
responsibilities in ORSA process:- Administrative, Management and Supervisory Body
- key functions

3

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Company Company
A
B

Company Company
A
B

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6- other functions- outsourcing
reporting ORSA (processes)(if any) reasons for deviation from the reference date
and/or transmission terms
other requirements from regulation

C

Methodologies and assumptions

4
5

10
11

methods for identifying significant risks - from the risk
map of "net risks"
methodologies and assumptions for forward looking
assessment
timing for assessment
methodologies and assumptions for overall solvency
need (OSN)
mitigation actions (included, if any, management
action) in the management of significant risks
impact of risk concentrations (due to portfolio structure:
government bonds)- assumption for stress used
- adequacy of portfolios used
- any initiatives taken
LTGM useddata quality in the ORSA assessment
adequacy of capital requirement compared to theundertaking risk profile, taking into account LTGM
continuous compliance with capital requirements
continuous compliance with technical provisionD

Outcomes and ORSA used

1
2
3
4
5

6
7
8
9

1
2
3

4
5
6

ORSA results, OSN, in terms of- capital requirement- solvency ratio- own fundresults and possible actions taken
impacts of long-term guarantees in terms of- technical provision- capital requirement- solvency ratio- own fundembedding of ORSA outcomes in the strategies, also in- management capital plan
- products strategy
charges related to the possible demand for assets tocover OSNORSA self-assessment

Company Company
A
B

Company Company
A
B

ORSA Tool – aspects to be analysed and rated (1-4 described below)
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a) Completeness of the Report and compliance with the regulation;b) ORSA Governance and risk strategy including risk profile of the undertaking(quantifiable and non-quantifiable risks);c) Appropriateness of risk profile assessment: assumptions and methodologies used toassess current and expected risksd) Main outcomes of ORSA and internal use
From a macroprudential point of view, the general evaluation can be an average result of theanalyses carried out at an individual level (or on the sample considered)Area
1Completenessand compliancewith
requirements

2
3
4

1

Governance anduse of ORSA

2

3

1
Appropriatenessof the risk profileand strategies231
Technical
aspects of risk
assessment andprojections

2
3

Elements to consider forevaluation purposes
compliance with the EIOPA
guidelines
and
the
ORSA
Regulation
objectives and scope of application
connections and references to the
Risk Appetite Framework
internal governance processes,
risk management and evaluation
measures adopted
degree of involvement andaccountability of the Board of
Directors (if not illustrated directly
but the reference to the ORSA
Policy is reported, consider
requesting it)
assignment
of
roles
and
responsibilities within the ORSA
process to the various company
functions/responsible personnel
degree of use of the ORSA interms of corporate governancesystem, business planning andcorporate strategies, also withreference to the results produced
definition and description of the risk
profile: analysis detail, risk map(quantifiable and not)instrument adopted for the
calculation of the SCR and any
considerations on adequacy, also
over timeassessment of the adequacy of therisk profile proportionate to thenature, complexity and specificityof the businessprocess of identifying the risks towhich the company is exposed:
criteria and hypotheses forselection, possible quantification,references to group policies/local
customisations
metrics adopted and risk tolerance
levels: calculation criteria andreasonsuse of long-term growth measures:quantification and impact on

PublicApplication Paper on Macroprudential Supervision
Adopted by the Executive Committee on 27 August 2021

Generaleval.

Comments
In relation to this area, the analyst must
express a general opinion based on thelevel of completeness of the ORSA
Report as well as on the level ofcompliance with the requirements set
out in the EIOPA Guidelines, as well aswith the IVASS Regulation in theforthcoming final issue

1
1
2
2

4
The report could refer to specificcompany or group documentation towhich the ORSA process is connected.
Check if all the documentation is citedand evaluate case by case theopportunity to ask the company forfurther information

2

1

4
For this area, the complete andconscious risk mapping identified by thecompany must be evaluated.
Furthermore, with regard to the capitalrequirements calculation tool

2

3

N. A.
Area of assessment of methodologies
and technical assumptions on thecurrent and future risk assessment

1
4

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4

5

6

capital requirements, presence ofcomparisons of the SCR with andwithout their adoption
stress tests: adequacy andcomplexityofthemethods
adopted, reference time frame,risks subjected to stressed
assessments, description andmotivationoftheselected
scenarios, description of thereverse stress test scenario
Asset liability management and, inparticular,
governmentbondmanagement policy
prospective
risk
assessment(forward-looking
perspective):assumptions and methodologies
adopted, reference time horizon,
connections to the business plan

Furtherevaluation
elements

4

4

4

The analyst reports in this section any
further relevant elements that emerged
from the analyses carried out

Not analysed (does not contribute to the automatic evaluation, ie in the calculation of the simple
average)
The ORSA Report is fully adequate
The ORSA Report needs integrations/improvements on some "non-core" aspects

4
N/A
1
2

The ORSA Report needs integrations/improvements on some "core" aspects

3

The ORSA Report is inadequate to represent the process of determining the capital to face corporate
risks

4

The horizontal examination of information (or data) allows supervisors to highlight market
trends that could also be found for similar types of insurers. The result of this analysis may be
used as input to Supervisory Boards, other macroprudential analysis/tools as well as
microprudential supervision.
To perform ORSA analysis, supervisors could also obtain the following examples of
information:•

Major management actions used to manage risks•

Risk appetite compared to solvency ratios•

Type and frequency of risk factors under stress•How, if or which “qualitative” risks are considered in the overall solvency need (shocks
applied and range of shocks)

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Stress values on the main market factors
More frequent
Risk factors
Stress scenario usedvalues
Italian government bonds+75/+250 bps+100 bps
spreadCurve of risk free rate+/-100 bps-120/+300 bps
Value of equity securities-20/-40 %-25 %Spread of private bond
+50/+150 bps+125 bps
Real estate-10/-25 %-20 %From a macroprudential perspective, the assessment of the ORSA reports, should take into
consideration the supervisors needs according to proportionality, for a representative sampleof the national market (ie 75% of production – including national groups and large players).

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