Article: Solvency II Directive 2009 (2009/138/EC) is a Directive in European Union law that codifies and harmonises the EU insurance regulation. Primarily this concerns the amount of capital that EU insurance companies must hold to reduce the risk of insolvency.
Following an EU Parliament vote on the Omnibus II Directive on 11 March 2014, Solvency II came into effect on 1 January 2016. This date had been previously pushed back many times.
Aims
EU insurance legislation aims to unify a single EU insurance market and enhance consumer protection. The third-generation Insurance Directives established an "EU passport" (single licence) for insurers to operate in all member states if they fulfilled EU conditions. Many member states concluded the EU minima were not enough, and took up their own reforms, which still led to differing regulations, hampering the goal of a single market.
Political implications of Solvency II
A number of the large Life Insurers in the UK are unhappy with the way the legislation has been developed. In particular, concerns have been publicly expressed over a number of years by the CEO of Prudential, the UK's largest Life Insurance company.
Doubts about the basis of the Solvency II legislation, in particular the enforcement of a market-consistent valuation approach have also been expressed by American subsidiaries of UK parents - the impact of the 'equivalency' requirements are not well understood and there is some concern that the legislation could lead to overseas subsidiaries becoming uncompetitive with local peers, resulting in the need to sell them off, potentially resulting in a 'Fortress Europe'.
Background
Since Directive 73/239/EEC was introduced in 1973, more elaborate risk management systems developed. Solvency II reflects new risk management practices to define required capital and manage risk. While the "Solvency I" Directive was aimed at revising and updating the current EU Solvency regime, Solvency II has a much wider scope. A solvency capital requirement may have the following purposes:
To reduce the risk that an insurer would be unable to meet claims;
To reduce the losses suffered by policyholders in the event that a firm is unable to meet all claims fully;
To provide early warning to supervisors so that they can intervene promptly if capital falls below the required level; and
To promote confidence in the financial stability of the insurance sector
Often called "Basel for insurers," Solvency II is somewhat similar to the banking regulations of Basel II. For example, the proposed Solvency II framework has three main areas (pillars):
Pillar 1 consists of the quantitative requirements (for example, the amount of capital an insurer should hold).
Pillar 2 sets out requirements for the governance and risk management of insurers, as well as for the effective supervision of insurers.
Pillar 3 focuses on disclosure and transparency requirements.
Contents
Title I General rules on the taking-up and pursuit of direct insurance and reinsurance activities
Chapter I Subject matter, scope and definitions
Chapter II Taking-up of business
Chapter III Supervisory authorities and general rules
Chapter IV Conditions governing business
Chapter V Pursuit of life and non-life insurance activity
Chapter VI Rules relating to the valuation of assets and liabilities, technical provisions, own funds, solvency capital requirement, minimum capital requirement and investment rules
Chapter VII Insurance and reinsurance undertakings in difficulty or in an irregular situation
Chapter VIII Right of establishment and freedom to provide services
Chapter IX Branches established within the community and belonging to insurance or reinsurance undertakings with head offices situated outside the community
Chapter X Subsidiaries of insurance and reinsurance undertakings governed by the laws of a third country and acquisitions of holdings by such undertakings
Title II Specific provisions for insurance and reinsurance
Title III Supervision of insurance and reinsurance undertakings in a group
Title IV Reorganisation and winding-up of insurance undertakings
Pillar 1
The pillar 1 framework set out qualitative and quantitative requirements for calculation of technical provisions and Solvency Capital Requirement (SCR) using either a standard formula given by the regulators or an internal model developed by the (re)insurance company.
Technical provisions are divided on claim provisions, pertaining to earned business and premium provisions, pertaining to unearned business. Premium provisions are not equal to unearned premium reserve.
The value of technical provision should be equal to the sum of best estimate of the liabilities and risk margin. The best estimate corresponds to the probability-weighted average of future cash-flows, taking into account the time value of money. Usage of central actuarial estimate is required and no margin for prudence is allowed. Only cash-flows that are within contract boundaries are taken into consideration. Solvency II specifies exact rules for determination of these contract boundaries.
Technical provisions represent the current amount the (re)insurance company would have to pay for an immediate transfer of its obligations to a third party.
The SCR is the capital required to ensure that the (re)insurance company will be able to meet its obligations over the next 12 months with a probability of at least 99.5%. In addition to the SCR capital a Minimum capital requirement (MCR) must be calculated which represents the threshold below which the national supervisor (regulator) would intervene. The MCR is intended to correspond to an 85% probability of adequacy over a one-year period and is bounded between 25% and 45% of the SCR.
For supervisory purposes, the SCR and MCR can be regarded as "soft" and "hard" floors respectively. That is, a regulatory ladder of intervention applies once the capital holding of the (re)insurance undertaking falls below the SCR, with the intervention becoming progressively more intense as the capital holding approaches the MCR. The Solvency II Directive provides regional supervisors with a number of discretions to address breaches of the MCR, including the withdrawal of authorization from selling new business and the winding up of the company.
Criticisms
Think-tanks such as the World Pensions & Investments Forum have argued that European legislators pushed dogmatically and naïvely for the adoption of the Basel II and Solvency II recommendations. In essence, they forced private banks, central banks, insurance companies and their regulators to rely more on assessments of credit risk by private rating agencies. Thus, part of the public regulatory authority was abdicated in favor of private rating agencies. The calibration of the standard formula for assessing equity risk has been strongly criticized by the German economist Stefan Mittnik for the fact that the procedure used for determining correlations between different asset classes gives rise to spurious (i.e., unreliable) correlations or spurious relationships.
The demanding nature of Solvency II legislation compared to current regulations has attracted criticism. According to RIMES, complying with the new legislation will impose a complex and significant burden on many European financial organizations, with 75% of firms in 2011 reporting that they were not in a position to comply with Pillar III reporting requirements.
The Matching adjustment mechanism of Solvency II has also been criticised as a form of creative accounting that hides the real value of liabilities.
See also EU law European company law
Own risk and solvency assessment
References External links
Text of Solvency II
EU FAQ on Solvency II
Lloyd's of London guidance
Solvency II Association |
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Norway: Financial Sector Assessment Program-Technical Note-Insurance Sector Stress Tests
Author:
International Monetary Fund. Monetary and Capital Markets Department
International Monetary Fund. Monetary and Capital Markets Department
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Current site Google Scholar Close Publication Date: 17 Sep 2015 eISBN: 9781513576497 Language: English Keywords: ISCR ; CR ; risk ; capital ; underwriting ; regulation ; market ; Norway
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Abstract Full Text Related Publications
This Technical Note presents key findings of insurance sector stress tests on Norway. Although the financial condition of insurance companies under Solvency I has generally been sound, insurers face major challenges going forward, thus placing an important premium on sound risk management and effective oversight by supervisors. The stress tests (under Solvency II) confirm that life insurers are vulnerable to severe shocks. The stress tests pointed to the high sensitivity of life insurers to market risks such as equity prices, real estate prices, and credit spreads. The risks to insurers are particularly pronounced if interest rates fall further from the current levels.
Abstract
This Technical Note presents key findings of insurance sector stress tests on Norway. Although the financial condition of insurance companies under Solvency I has generally been sound, insurers face major challenges going forward, thus placing an important premium on sound risk management and effective oversight by supervisors. The stress tests (under Solvency II) confirm that life insurers are vulnerable to severe shocks. The stress tests pointed to the high sensitivity of life insurers to market risks such as equity prices, real estate prices, and credit spreads. The risks to insurers are particularly pronounced if interest rates fall further from the current levels.
Background
1. The insurance sector is relatively small
. In terms of premium revenues relative to GDP, the life insurance and non-life insurance sectors are smaller than in many peer countries (
Figure 1
). This is in part because large shares of pension liabilities reside with the National Insurance Scheme Fund and the Norwegian Public Service Pension Fund.
Figure 1.
The Size of the Insurance Sector
Citation: IMF Staff Country Reports 2015, 255;
10.5089/9781513576497.002.A001
Sources: OECD; and IMF
World Economic Outlook database. Download Figure
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View Full Size Figure 1.
The Size of the Insurance Sector
Citation: IMF Staff Country Reports 2015, 255;
10.5089/9781513576497.002.A001
Sources: OECD; and IMF
World Economic Outlook database. Download Figure
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Figure 1.
The Size of the Insurance Sector
Citation: IMF Staff Country Reports 2015, 255;
10.5089/9781513576497.002.A001
Sources: OECD; and IMF
World Economic Outlook database. Download Figure
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2. The insurance sector is concentrated
. The Norwegian life insurance sector is one of the most concentrated in Europe: the three largest companies account for about 80 percent of gross written premiums (
Figure 2
). The degree of concentration is also high for the non-life insurance sector (although less so than in the life insurance sector), where, at 37 percent, the share of foreign-owned institutions is large.
Figure 2.
Norway: Concentration in the Insurance Sector
Citation: IMF Staff Country Reports 2015, 255;
10.5089/9781513576497.002.A001
Sources: EIOPA; and IMF staff estimates.
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View Full Size Figure 2.
Norway: Concentration in the Insurance Sector
Citation: IMF Staff Country Reports 2015, 255;
10.5089/9781513576497.002.A001
Sources: EIOPA; and IMF staff estimates.
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Figure 2.
Norway: Concentration in the Insurance Sector
Citation: IMF Staff Country Reports 2015, 255;
10.5089/9781513576497.002.A001
Sources: EIOPA; and IMF staff estimates.
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3. Many insurance companies are part of financial conglomerates
. At end-2013, the seven largest conglomerates accounted for 74 percent of total financial system assets (
Table 2
). Their core activities are in lending and life insurance, except for Gjensidige which operates mostly in the non-life insurance sector. The conglomerate structure allows earnings and risk diversification in normal times, but leaves room for contagion if institutions are hit by large shocks.
Table 2.
Norway: Largest Financial Groups, December 2013
1/
(In percent of total assets)
Sources: Finanstilsynet and the Norwegian Mutual Fund Association.
1/
Credit institutions comprise banks, mortgage companies and finance companies. Eksportfinans and Kommunalbanken are not included in the figures The total for financial groups comprises aggregate total assets in the various segments and may diverge from the conglomerates/groups’ own financial statements. The total market comprises Norwegian credit institutions’ business abroad and foreign financial institutions’ subsidiaries and branches in Norway. For SpareBank 1 Gruppen and Eika-Gruppen, the owner banks are included in the market shares.
Table 2.
Norway: Largest Financial Groups, December 2013
1/
(In percent of total assets)
Credit institutions Securities funds Non-life insurance Life insurance Total conglomerates DNB 40 17 1 27 35 SpareBank 1/ Collaborating savings banks 15 5 7 3 12 Nordea 11 10 0 7 10 KLP 0.5 15 2 31 6 Storebrand 1 12 1 23 5 Eika-Gruppen 5 1 2 0 4 Gjensidige 0.5 0 27 1 1 Total financial conglomerates/alliances 73 60 40 92 74 Other institutions 27 40 60 8 26 Total market 100 100 100 100 100
Sources: Finanstilsynet and the Norwegian Mutual Fund Association.
1/
Credit institutions comprise banks, mortgage companies and finance companies. Eksportfinans and Kommunalbanken are not included in the figures The total for financial groups comprises aggregate total assets in the various segments and may diverge from the conglomerates/groups’ own financial statements. The total market comprises Norwegian credit institutions’ business abroad and foreign financial institutions’ subsidiaries and branches in Norway. For SpareBank 1 Gruppen and Eika-Gruppen, the owner banks are included in the market shares.
View Table Table 2.
Norway: Largest Financial Groups, December 2013
1/
(In percent of total assets)
Credit institutions Securities funds Non-life insurance Life insurance Total conglomerates DNB 40 17 1 27 35 SpareBank 1/ Collaborating savings banks 15 5 7 3 12 Nordea 11 10 0 7 10 KLP 0.5 15 2 31 6 Storebrand 1 12 1 23 5 Eika-Gruppen 5 1 2 0 4 Gjensidige 0.5 0 27 1 1 Total financial conglomerates/alliances 73 60 40 92 74 Other institutions 27 40 60 8 26 Total market 100 100 100 100 100
Sources: Finanstilsynet and the Norwegian Mutual Fund Association.
1/
Credit institutions comprise banks, mortgage companies and finance companies. Eksportfinans and Kommunalbanken are not included in the figures The total for financial groups comprises aggregate total assets in the various segments and may diverge from the conglomerates/groups’ own financial statements. The total market comprises Norwegian credit institutions’ business abroad and foreign financial institutions’ subsidiaries and branches in Norway. For SpareBank 1 Gruppen and Eika-Gruppen, the owner banks are included in the market shares.
4. Prudent macroeconomic policies have reduced macroeconomic risks
. Real mainland GDP growth has averaged about 2½ percent during 2010–14 and, at 3½ percent, unemployment is low. High levels of oil production and exports, together with Norway’s fiscal rule and oil fund (the Government Pension Fund Global—GPFG), have resulted in strong fiscal and external positions (see the Aide Memoire of the mission). The macroeconomic policy frameworks are sound, enhancing the economy’s capacity to absorb shocks. The GPFG and the fiscal rules have provided a significant degree of insulation from sharp changes in oil prices and the so-called “Dutch disease,” and allowed the use of counter-cyclical fiscal policy. In addition, Norway’s flexible exchange rate has helped absorb foreign exchange shocks, while its flexible inflation targeting framework has enabled the inflation target to be met without causing significant volatility in interest rates and output. Norway’s well-being indicators are among the highest in the world, which may increase demand for insurance products (
Figure 3
). On the other hand, rising longevity and low interest rates pose risks to life insurers.
Figure 3.
Product Allocation in Life Insurance
Citation: IMF Staff Country Reports 2015, 255;
10.5089/9781513576497.002.A001 Source: FSA. Download Figure
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Product Allocation in Life Insurance
Citation: IMF Staff Country Reports 2015, 255;
10.5089/9781513576497.002.A001 Source: FSA. Download Figure
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Figure 3.
Product Allocation in Life Insurance
Citation: IMF Staff Country Reports 2015, 255;
10.5089/9781513576497.002.A001 Source: FSA. Download Figure
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Table 3. Norway’s Well-Being Indicators Source: OECD,
How’s Life? 2013. Measuring Well-being
. Table 3. Norway’s Well-Being Indicators Life satisfaction Jobs and earnings Household income Work-life balance Health Safety Education Norway rank (among 35 countries) 2 2 3 3 13 16 17 Scores: Maximum 10 8.9 38001 9.8 9.4 10 9.5 Norway 9.7 8.6 31458 9.1 8.1 9.1 7.2 Average 6.2 6.2 23047 7.3 6.9 8.3 6.3 Minimum 0 2.3 11039 0 0.6 0 0.7 Source: OECD,
How’s Life? 2013. Measuring Well-being
. View Table Table 3. Norway’s Well-Being Indicators Life satisfaction Jobs and earnings Household income Work-life balance Health Safety Education Norway rank (among 35 countries) 2 2 3 3 13 16 17 Scores: Maximum 10 8.9 38001 9.8 9.4 10 9.5 Norway 9.7 8.6 31458 9.1 8.1 9.1 7.2 Average 6.2 6.2 23047 7.3 6.9 8.3 6.3 Minimum 0 2.3 11039 0 0.6 0 0.7 Source: OECD,
How’s Life? 2013. Measuring Well-being
.
5. The specific features and relatively small size of the domestic financial market have affected the portfolio allocation of insurers
. The limited risk-taking ability of life insurers offering guaranteed rates forces insurers to hold larger shares of their investments in bonds and smaller shares in equities (
Figures 3 , 4 , 5 , and 6
). As insurers have been increasingly offering unit-linked products,
2
they have started reallocating investments away from bonds towards equity and other assets. Reflecting the small size of the government securities market, insurers’ holdings of private sector bonds and real estate investments are larger than in many countries. This factor has supported demand for covered bonds issued by banks/mortgage companies. Given a shortage of longer-term local currency investment opportunities, insurers also look abroad for suitable assets, and for hedges for the related currency exposure.
3 Figure 4.
Investment Portfolio Allocation: Life Insurers (2013)
Citation: IMF Staff Country Reports 2015, 255;
10.5089/9781513576497.002.A001 Source: OECD Global Insurance Statistics . Download Figure
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View Full Size Figure 4.
Investment Portfolio Allocation: Life Insurers (2013)
Citation: IMF Staff Country Reports 2015, 255;
10.5089/9781513576497.002.A001 Source: OECD Global Insurance Statistics . Download Figure
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Figure 4.
Investment Portfolio Allocation: Life Insurers (2013)
Citation: IMF Staff Country Reports 2015, 255;
10.5089/9781513576497.002.A001 Source: OECD Global Insurance Statistics . Download Figure
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Figure 5.
Investment Portfolio Allocation: Non-life Insurers (2013)
Citation: IMF Staff Country Reports 2015, 255;
10.5089/9781513576497.002.A001 Source: OECD Global Insurance Statistics . Download Figure
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View Full Size Figure 5.
Investment Portfolio Allocation: Non-life Insurers (2013)
Citation: IMF Staff Country Reports 2015, 255;
10.5089/9781513576497.002.A001 Source: OECD Global Insurance Statistics . Download Figure
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Figure 5.
Investment Portfolio Allocation: Non-life Insurers (2013)
Citation: IMF Staff Country Reports 2015, 255;
10.5089/9781513576497.002.A001 Source: OECD Global Insurance Statistics . Download Figure
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Figure 6.
Portfolio Allocation to Public and Private Sector Bonds (2013)
(In percent)
Citation: IMF Staff Country Reports 2015, 255;
10.5089/9781513576497.002.A001 Source: Source: OECD Global Insurance Statistics . Download Figure
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View Full Size Figure 6.
Portfolio Allocation to Public and Private Sector Bonds (2013)
(In percent)
Citation: IMF Staff Country Reports 2015, 255;
10.5089/9781513576497.002.A001 Source: Source: OECD Global Insurance Statistics . Download Figure
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Figure 6.
Portfolio Allocation to Public and Private Sector Bonds (2013)
(In percent)
Citation: IMF Staff Country Reports 2015, 255;
10.5089/9781513576497.002.A001 Source: Source: OECD Global Insurance Statistics . Download Figure
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6. Financial sector regulation is closely aligned with EU norms, as required by Norway’s participation in the European Economic Area (EEA)
. Thus, new EU initiatives in the area of insurance are to be adopted by Norway.
7. Currently, the valuation basis for assets, with the exception of held-to-maturity bonds, is market-consistent valuation
. For bonds held to maturity and loans, insurers can use amortized cost. This category represents about 30 percent of total assets for life insurers, 20 percent for non-life insurers and 10 percent for pension funds.
8. The valuation of insurance liabilities is based on discounting future benefits with the (single) interest rate used when calculating the premiums (the guaranteed rate), which means that applying the current low market rates would increase the need for technical provisions
. The maximum guaranteed rate has been reduced on several occasions, and was reduced from 2.5 percent to 2.0 percent in 2015. The reduction of the rate only applies to new premium accrual, and does not affect the valuation of existing liabilities. Biometrical risk assumptions (i.e. mortality, longevity, and disability) have historically not been updated frequently, but larger revisions of mortality assumptions have been implemented in 2007 and 2014.
9. The new mortality tariff implemented in 2014 is a dynamic tariff that includes a trend factor to cover the expected future continuous increase in life expectancy
. Due to the large revisions, the undertakings have been granted a maximum 7-year transition period to increase the value of existing technical provisions.
4
More than half of the increase in technical provisions is expected to be financed by the policyholders through lower profit allocations.
10. Under Solvency I, non-life insurance undertakings generally do not discount their premium provisions or provisions for outstanding claims—neither for accounting purposes nor for solvency purposes—but this will change under Solvency II
. Discounting is allowed for long-tailed business (e.g. workers’ compensation insurance) for accounting purposes, but not for solvency purposes. According to the current minimum requirements for technical provisions, the total of (1) premium provisions, (2) provisions for outstanding claims, and (3) fluctuation provisions is stipulated to cover the undertakings’ overall future contractual claim payments and associated costs with a high degree of probability (99 percent).
Recent Performance
11. The financial condition of insurance companies under Solvency I has generally been sound
. They have low expense ratios, and made 3–4 percent real returns on their investments in 2012–14 (
Table 4 , Figures 7 and 8
). Life insurers used about two-thirds of their profits after allocation of guaranteed returns to increase technical reserves to adopt the new mortality table and share profits with policyholders, and yet recorded pre-tax profits of about 0.5 percent of total assets in 2010–14. Non-life insurers have performed better, recording pre-tax profits of 27.7 percent of gross premiums. While insurers increased their premiums in real terms in 2012, this reversed in 2013. In 2014, the premiums rose by 10 percent. The capital buffer of life insurers (under Solvency I) has steadily increased (relative to insurance liabilities) since 2011 and was about 10.2 percent at the end of 2014, while the buffer capital of non-life insurers was significantly higher. Solvency ratios have remained stable at comfortable levels (
Figure 8
). Solvency capital consists of own funds and specific insurance funds. Tier 1 own funds is about 72 percent of total solvency margin capital in life insurance, compared with 53 percent in the non-life sector.
5 Table 4.
Average Real Net Investment Return by Type of Insurer
(in percent) Source: OECD Global Insurance Statistics . Table 4.
Average Real Net Investment Return by Type of Insurer
(in percent) Life Non-life Composite 2012 2013 2012 2013 2012 2013 Australia 12.2 13.0 5.4 3.2 n.a n.a Austria … … 1.3 … 1.2 … Belgium 2.3 3.6 0.7 2.0 2.2 3.1 Canada … … 3.6 2.0 5.9 −1.6 Chile 5.4 4.8 3.4 4.5 n.a n.a Czech Republic −0.6 0.0 3.2 −0.1 1.0 1.0 Estonia 1.2 0.5 … 0.1 n.a n.a Germany 3.0 4.0 1.7 2.4 n.a n.a Hungary 1.7 5.6 1.6 2.8 1.5 5.3 Iceland −4.0 1.5 −3.9 −0.5 n.a n.a Ireland 5.3 −1.4 3.8 2.2 n.a n.a Israel … −0.2 7.0 2.7 5.0 4.8 Italy 3.2 3.3 2.9 2.2 2.1 3.3 Japan 3.3 0.8 3.1 … n.a n.a Korea 2.8 3.0 2.3 2.3 n.a n.a Luxembourg −2.2 1.9 −2.2 −0.1 n.a n.a Netherlands 5.8 4.7 4.4 1.8 n.a n.a Norway 4.4 3.2 4.4 … n.a n.a Poland 4.0 4.5 4.7 9.9 n.a n.a Portugal 1.0 2.3 0.6 2.2 4.0 5.5 Spain 2.2 4.0 −0.2 3.1 −0.2 3.9 Switzerland 4.0 3.1 4.0 4.0 n.a n.a Turkey 0.2 −0.7 −5.6 −3.6 n.a n.a Source: OECD Global Insurance Statistics . View Table Table 4.
Average Real Net Investment Return by Type of Insurer
(in percent) Life Non-life Composite 2012 2013 2012 2013 2012 2013 Australia 12.2 13.0 5.4 3.2 n.a n.a Austria … … 1.3 … 1.2 … Belgium 2.3 3.6 0.7 2.0 2.2 3.1 Canada … … 3.6 2.0 5.9 −1.6 Chile 5.4 4.8 3.4 4.5 n.a n.a Czech Republic −0.6 0.0 3.2 −0.1 1.0 1.0 Estonia 1.2 0.5 … 0.1 n.a n.a Germany 3.0 4.0 1.7 2.4 n.a n.a Hungary 1.7 5.6 1.6 2.8 1.5 5.3 Iceland −4.0 1.5 −3.9 −0.5 n.a n.a Ireland 5.3 −1.4 3.8 2.2 n.a n.a Israel … −0.2 7.0 2.7 5.0 4.8 Italy 3.2 3.3 2.9 2.2 2.1 3.3 Japan 3.3 0.8 3.1 … n.a n.a Korea 2.8 3.0 2.3 2.3 n.a n.a Luxembourg −2.2 1.9 −2.2 −0.1 n.a n.a Netherlands 5.8 4.7 4.4 1.8 n.a n.a Norway 4.4 3.2 4.4 … n.a n.a Poland 4.0 4.5 4.7 9.9 n.a n.a Portugal 1.0 2.3 0.6 2.2 4.0 5.5 Spain 2.2 4.0 −0.2 3.1 −0.2 3.9 Switzerland 4.0 3.1 4.0 4.0 n.a n.a Turkey 0.2 −0.7 −5.6 −3.6 n.a n.a Source: OECD Global Insurance Statistics . Figure 7.
Insurance Sector Performance Indicators Under Solvency I
Citation: IMF Staff Country Reports 2015, 255;
10.5089/9781513576497.002.A001
Sources: EIOPA; and Norwegian authorities.
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Insurance Sector Performance Indicators Under Solvency I
Citation: IMF Staff Country Reports 2015, 255;
10.5089/9781513576497.002.A001
Sources: EIOPA; and Norwegian authorities.
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Figure 7.
Insurance Sector Performance Indicators Under Solvency I
Citation: IMF Staff Country Reports 2015, 255;
10.5089/9781513576497.002.A001
Sources: EIOPA; and Norwegian authorities.
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Figure 8.
Combined Ratio for the Non-life Segment in OECD Countries (2012–2013)
(In percent)
Citation: IMF Staff Country Reports 2015, 255;
10.5089/9781513576497.002.A001 Source: OECD Global insurance Statistics . Download Figure
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View Full Size Figure 8.
Combined Ratio for the Non-life Segment in OECD Countries (2012–2013)
(In percent)
Citation: IMF Staff Country Reports 2015, 255;
10.5089/9781513576497.002.A001 Source: OECD Global insurance Statistics . Download Figure
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Figure 8.
Combined Ratio for the Non-life Segment in OECD Countries (2012–2013)
(In percent)
Citation: IMF Staff Country Reports 2015, 255;
10.5089/9781513576497.002.A001 Source: OECD Global insurance Statistics . Download Figure
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Risks and Vulnerabilities
12. Life insurers face major challenges, which heighten the importance of sound risk management and effective oversight by supervisors
. A continued low-interest rate environment would adversely impact earnings and claims-paying capacity over the medium term, as some 83 percent of life insurers’ liabilities carry guaranteed minimum rates of return.
6
For example, at end-2013, the guaranteed return averaged 3.2 percent, which was higher than the return on 10-year government bonds, and the difference seems to have widened in 2014–15. In addition, life insurers’ are exposed to rising longevity risks. In response, insurers have recently started to encourage existing policyholders with guaranteed products to switch their policies to “unit-linked” (nonguaranteed) products, thus shifting risks from insurers to policy holders (
Box 1 ).
Norway: Interest Rate Developments
(In percent)
Citation: IMF Staff Country Reports 2015, 255;
10.5089/9781513576497.002.A001 Source: Norges Bank. Download Figure
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View Full Size
Norway: Interest Rate Developments
(In percent)
Citation: IMF Staff Country Reports 2015, 255;
10.5089/9781513576497.002.A001 Source: Norges Bank. Download Figure
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Norway: Interest Rate Developments
(In percent)
Citation: IMF Staff Country Reports 2015, 255;
10.5089/9781513576497.002.A001 Source: Norges Bank. Download Figure
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Box 1.
Conversion of Paid-up Policies into Unit-linked Policies
In June 2014, the Ministry of Finance (MOF) adopted regulations allowing conversion of paid-up policies into unit linked policies. The regulation entered into force on September 1, 2014.
Where paid-up policies are converted to unit-linked policies, the paid-up policyholder must relinquish the guarantee regarding previously accrued rights. The regulation requires that the paid-up policyholder must be provided with sufficient information on the consequences of the potential conversion, including written examples showing what annual return on a given investment portfolio for a given age group is needed to achieve particular pension benefits.
The regulation requires a paid-up policy to be fully provisioned before conversion to a unit-linked policy. Had full provisioning not been required, the paid-up policyholders agreeing to conversion to unit-linked policies would have been exposed to biometric risks (such as longevity) as well as the interest rate risk, thus running a fairly high risk of accumulating significantly lower pension benefits under the unit-linked contract than those that had been guaranteed by the life insurer prior to the conversion.
The requirement for full provisioning will to some extent reduce the advantage for the insurers of converting paid-up policies to unit-linked policies. In particular, switching to unit-linked policies is assumed to be primarily suited to young pension plan members with many years left to retirement, but those members typically require the highest possible provisioning due to higher life expectancy. It is uncertain whether insurers will offer the conversion until the paid-up policies are fully provisioned. The delay in the conversion offering will in its turn render the conversion less attractive to the target group as the potential for a higher long-run investment return gets reduced.
13. The implementation of Solvency II represents additional challenges for life insurers (as in many peer countries)
. Under Solvency II, liabilities will be measured at fair value (compared with the current practice of discounting liabilities using the guaranteed rate),
7
meaning that the current market interest rate level will be used to estimate the value of future liabilities. Thus, it will be difficult for life insurers to meet the capital requirements under Solvency II because of the current low interest rates. Furthermore, the increased capital requirements on paid-up policies under Solvency II pose a particular challenge to insurers. In light of future capital requirements and low interest rates, life insurers have recently increased premiums on other products and have been trying to further reduce costs. The FSA has proposed to implement Solvency II through allowing (i) a 16-year transition period for implementing the Solvency II valuation of technical provisions and (ii) the use of volatility adjustment.
8
14. In contrast, for non-life insurers, the transition to Solvency II is expected to lead to a reduction of technical provisions
. This is because the current regulation on technical provisions, including the fluctuation provisions requirement, represents a more demanding approach than the “best estimate” (“expected value”) plus risk margin assessment under Solvency II. Under Solvency II, insurers will start discounting their insurance liabilities using market rates, which will reduce present values of their liabilities and thus improve (reported) capital adequacy ratios.
15. Insurers’ asset composition largely determines their market risks
. The relatively large shares of private bonds and real estate assets of life insurers mean that they are vulnerable to credit spreads, overall economic slowdown (which could increase credit spreads), interest rate declines, and real estate price declines. On the other hand, non-life insurers’ liabilities and assets have shorter maturities, which reduce their market risks.
16. There is a possibility that the prolonged low interest rate environment will push insurers to shift their investments towards riskier assets (to maintain their profitability)
. Growth remains subdued in the euro zone, and several of Norway’s important trade partners have reduced their policy rates or adopted a negative policy deposit rate. These are likely to put pressure on interest rates in Norway. The low interest rate environment has made it difficult for life insurers, with their generally large holdings of bonds, to earn adequate returns in relation to their obligations. This could lead to a shift of portfolio allocations towards more risky assets in a search for yield to improve investment returns. The current regulations for guaranteed-rate products constrain insurers’ capacity to take investment risks, but the authorities should closely monitor the risks taken and avoid any deterioration in underwriting standards or under-pricing of premiums.
17. Life insurers face significant longevity risks
. Life expectancy at birth in Norway—which is higher than the OECD average—has been growing like in most peer countries, and is expected to grow further. Thus, the increase in longevity after contracts are written constitutes a risk. Health care costs have been growing as well.
Figure 9.
Life Expectancy At Birth in Norway and OECD Countries
Citation: IMF Staff Country Reports 2015, 255;
10.5089/9781513576497.002.A001 Sources: World Bank World Development Indicators database. Download Figure
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Life Expectancy At Birth in Norway and OECD Countries
Citation: IMF Staff Country Reports 2015, 255;
10.5089/9781513576497.002.A001 Sources: World Bank World Development Indicators database. Download Figure
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Figure 9.
Life Expectancy At Birth in Norway and OECD Countries
Citation: IMF Staff Country Reports 2015, 255;
10.5089/9781513576497.002.A001 Sources: World Bank World Development Indicators database. Download Figure
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18. The possibility of cross-sectoral contagion in Norway is to some extent limited by the regulations on exposures to companies in a conglomerate
. In particular, institutions may not provide loans/guarantees to another company within their group without consent from the MOF. This rule covers also investments in bonds issued by another entity within the group, but exemptions apply to certain exposures. At end-2014, insurers’ investments in bank debt instruments (excluding deposits) averaged 7 percent of total assets in the life sector and 9 percent in the nonlife sector (
Table 5 ). 9
However, contagion risks could be higher than implied by these figures because of contagion risks from common exposures (see the accompanying technical note on interconnectedness).
Table 5.
Insurers’ Exposures to Banks at end–2014
Sources: Norwegian authorities, and IMF staff estimates.
Table 5.
Insurers’ Exposures to Banks at end–2014
Life insurance Non-life insurance Millions of NOK
In percent of assets
Millions of NOK
In percent of assets
Deposits 30,915 2.6 7,846 3.5
Stocks and shares (inc. shares in subsidiaries)
46 0.0 1,620 0.7
Bonds and other fixed income securities
55,802 4.6 13,749 6.1 Loans and receivables 24,515 2.0 6,283 2.8 Financial derivatives 68 0.0 102 0.0 Other financial derivatives 6,400 0.5 474 0.2
Sources: Norwegian authorities, and IMF staff estimates.
View Table Table 5.
Insurers’ Exposures to Banks at end–2014
Life insurance Non-life insurance Millions of NOK
In percent of assets
Millions of NOK
In percent of assets
Deposits 30,915 2.6 7,846 3.5
Stocks and shares (inc. shares in subsidiaries)
46 0.0 1,620 0.7
Bonds and other fixed income securities
55,802 4.6 13,749 6.1 Loans and receivables 24,515 2.0 6,283 2.8 Financial derivatives 68 0.0 102 0.0 Other financial derivatives 6,400 0.5 474 0.2
Sources: Norwegian authorities, and IMF staff estimates.
Stress Test Framework and Assumptions
A. The FSA’s Insurance Stress Testing Framework
19. The authorities have a broadly adequate framework to assess potential losses
. Since 2008, insurance undertakings (and pension funds) have regularly reported stress tests to the FSA. Currently most small non-life undertakings report on a biannual basis, while the others report on a quarterly basis. The FSA has specified two stress tests to be reported. “Stresstest” I is a simplified version of the Solvency II calculations—a “Solvency II light” approach (see
Appendix I
for a description of the methodology used in the FSAP stress tests/Stresstest I). “Stresstest II” has a somewhat different approach, as it assesses the undertakings’ ability to absorb losses without breaching existing capital requirements (Solvency I and the capital adequacy requirement). In addition, the FSA obtains companies’ own risk and solvency assessment reports (ORSA), which require insurers to conduct a number of stress tests, including reverse stress tests.
20. The Stresstest I framework is based on technical specifications formulated by the European Insurance and Occupational Pensions Authority (EIOPA)
. Market and other risks are covered in the form of a combination of single-factor shocks, and companies report the sensitivity to each of the shocks assuming them to occur instantaneously. Then, the risks are added using the so-called “diversification” matrix (which reduces the overall risk below the sum of the individual risks).
Box 2.
Solvency II Capital Requirements
The Solvency II framework has three main areas (pillars).
Pillar 1 consists of the quantitative requirements (for example, the amount of capital an insurer should hold).
Pillar 2 sets out requirements for the governance and risk management of insurers, as well as for the effective supervision of insurers.
Pillar 3 focuses on disclosure and transparency requirements.
The pillar 1 framework sets out the qualitative and quantitative requirements for calculation of technical provisions and Solvency Capital Requirement (SCR) using either a standard formula given by the regulators or an internal model developed by the insurance company. Technical provisions comprise two components: the best estimate of the liabilities (i.e. the central actuarial estimate) plus a risk margin. Technical provisions are intended to represent the current amount the insurance company would have to pay for an immediate transfer of its obligations to a third party.
The SCR is the capital required to ensure that the (re)insurance company will be able to meet its obligations over the next 12 months with a probability of at least 99.5 percent. In addition to the SCR capital, a minimum capital requirement (MCR) must be calculated, which represents the threshold below which the national supervisor (regulator) would intervene. The MCR is intended to correspond to an 85 percent probability of adequacy over a one-year period and is bounded between 25 percent and 45 percent of the SCR.
For supervisory purposes, the SCR and MCR can be regarded as “soft” and “hard” floors, respectively. That is, a regulatory ladder of intervention applies once the capital holding of the insurance undertaking falls below the SCR, with the intervention becoming progressively more intense as the capital holding approaches the MCR.
21. The FSA’s stress tests (Stresstest I) are built on a number of moderate-to-severe shock assumptions, suggested by the EIOPA
.
On the asset side, (among others) these include the following:
An equity price shock of 45–55 percent (for Type 1 and Type 2 assets).
A domestic interest rate increase/decline of 0.64/0.56 basis points and a foreign interest rate increase/decline of 0.55/0.46 basis points.
10
A 25 percent decline in real estate prices.
An exchange rate movement of 25 percent.
A spread risk applying to corporate bonds, covered bonds, subordinated debt investments, depending on the contractual terms, investment instruments with equity and bond features, etc.
On the liability side, (among others) stress factors include two natural catastrophes with loss impact of NOK 5 billion each (NOK 10 billion in total), affecting insurers through their participation in the Natural Perils Pool (proportionate to their market share). This amount is more than the loss experienced during a severe storm in 1992, approximately NOK 2 billion in present value (in 2014 kroner).
22. Combined, these factors represent a severe shock
. In particular, a combination of the market, life/non-life underwriting, health underwriting, counterparty default, and operational risks correspond to the Value-at-Risk of the basic own funds of an insurance undertaking subject to a confidence level of 99.5 percent over a one-year period. These imply that the combined severe shock could happen once in about 200 years.
23. At this stage, the authorities do not conduct scenario analyses, and rely on companies’ assessment of most risks on the liability side
. Until now, the FSA has focused on verifying the companies’ own calculations through reviewing insurers’ internal models. It does not have sufficient data and resources to conduct the liability side stress tests on its own.
Recommendation
24. The mission urges the authorities to continue to improve the stress test framework
. In particular, the FSA should continue to build its capacity to conduct liability side stress tests and verify the reports by insurance companies. In addition, the authorities should consider applying macro-prudential stress scenarios. These would require additional resources for the FSA.
B. FSAP Stress Test Assumptions
25. The mission worked closely with the FSA to conduct insurance stress tests
. In particular, the assumptions used for estimating market risks and insurance liability risks (top-down approach) were jointly agreed. Other liability-side risks (life underwriting risks, health underwriting risks, non-life underwriting risks, and non-life catastrophe risks) were estimated by the insurance companies (bottom-up approach), based on the assumptions given to them by the FSA (under the FSA’s Stresstest I, which is independent of the FSAP), which were taken as given by the FSAP team.
26. Three large life and non-life insurance companies were covered on a solo basis
. 11
They represent 80 percent and 51 percent, respectively, of assets in the life and non-life sectors.
27. The FSAP stress tests used the following stress factors
:
The first scenario assumes a combination of shocks similar to the adverse scenario used for the banking stress testing exercise (with a monetary policy response,
Tables 6 and 7
). This scenario is related to an upsurge in global financial market volatility. Higher financing costs and strains on the fiscal sustainability globally are assumed to push a number of countries into a tight policy mix, with repercussions for global growth and rising financial stability risks. A slowdown in Norway’s key trading partners and, particularly, a decline in global oil prices have a strong downward impact on domestic growth, with higher unemployment and a sharp correction of real estate prices. The main difference from the banking stress test scenarios is that the insurance stress tests instantaneously apply the cumulative changes that will take place from 2015 to 2019 (as if the whole change took place immediately; as is done under the FSA’s own insurance stress tests).
The second scenario is based on the second scenario of the banking stress testing exercise. Under this scenario, there is no (monetary) policy response. Accordingly, the shock is stronger.
The third scenario applies a combination of ad-hoc shocks, better tailored to insurance companies’ vulnerabilities and, hence, with more adverse consequences for insurers. For example, instead of the 250 bp increase in interest rates, it is assumed that interest rates will decline by 100 bps (for more details see
Appendix II ). 12
The default of the largest banking counterparties, with loss given default (LGD) on all contractual obligations, was assumed as in the formula suggested by the EIOPA.
Two catastrophic events were assumed, with an increased reinsurance reinstatement premium.
Table 6.
Key Assumptions for Insurance Sector Stress Tests
(Changes in percent unless otherwise specified)
1/
Not included in the banking stress testing.
Table 6.
Key Assumptions for Insurance Sector Stress Tests
(Changes in percent unless otherwise specified)
Adverse scenario with policy response
Adverse scenario without policy response
Ad hoc assumptions Asset side
Interest rates (increase in pp)
2.5 2.5 2.5
Interest rates (decrease in pp)
1/ −1.0 Equity prices −26.0 −26.0 −50.0
(Nominal) Real estate prices
−29.0 −33.0 −40.0 Exchange rate (depreciation) −6.5 −5.6 −30 Exchange rate (appreciation) 1/ 30 Spread risk 1/ 70-750 70-750 70-750
LGD for concentration risk
1/ 45 45 45 Liability side 1/ Underwriting Demographic (mortality) Lapses Disability Operational 1/
Not included in the banking stress testing.
View Table Table 6.
Key Assumptions for Insurance Sector Stress Tests
(Changes in percent unless otherwise specified)
Adverse scenario with policy response
Adverse scenario without policy response
Ad hoc assumptions Asset side
Interest rates (increase in pp)
2.5 2.5 2.5
Interest rates (decrease in pp)
1/ −1.0 Equity prices −26.0 −26.0 −50.0
(Nominal) Real estate prices
−29.0 −33.0 −40.0 Exchange rate (depreciation) −6.5 −5.6 −30 Exchange rate (appreciation) 1/ 30 Spread risk 1/ 70-750 70-750 70-750
LGD for concentration risk
1/ 45 45 45 Liability side 1/ Underwriting Demographic (mortality) Lapses Disability Operational 1/
Not included in the banking stress testing.
Table 7.
Bank Stress Test Assumptions
(Y-o-y percentage change in relevant factors; unless otherwise stated)
Sources: Norwegian Authorities; and IMF staff estimates.
Table 7.
Bank Stress Test Assumptions
(Y-o-y percentage change in relevant factors; unless otherwise stated)
Baseline Scenario Adverse Scenario Adverse Scenario (with policy response) (without policy response) 2014 2015 2016 2017 2018 2019 2015 2016 2017 2018 2019 2015 2016 2017 2018 2019 GDP, mainland Norway 2.5 1.5 2.0 2.3 2.5 2.5 0.1 −2.8 −1.4 −0.4 0.2 −0.6 −3.4 −2.0 −0.8 0.0 Nominal house prices 2.3 6.6 3.5 2.6 2.6 2.6 −3.0 −10.8 −9.6 −5.4 −3.9 −4.5 −11.6 −10.7 −6.6 −5.2
Nominal commercial real estate prices
9.8 6.6 3.5 2.6 2.6 2.6 −1.4 −10.8 −9.6 −5.4 −3.9 −2.9 −11.6 −10.7 −6.6 −5.2 Equity prices 0.0 0.0 0.0 0.0 0.0 0.0 −26.0 0.0 0.0 0.0 0.0 −26.0 0.0 0.0 0.0 0.0 Key policy rate 1.5 1.2 1.2 1.5 1.5 1.5 0.5 0.0 0.0 0.0 0.0 1.2 1.2 1.5 1.6 1.6 3-month NIBOR rate 1.7 1.4 1.4 1.7 1.7 1.7 2.5 2.0 2.0 2.0 2.0 3.2 3.2 3.5 3.6 3.6 Lending rates, households 4.3 3.8 3.8 4.0 4.0 4.0 5.1 4.6 4.6 4.6 4.6 5.8 5.8 6.1 6.2 6.2
Lending rates, non-financial enterprises
4.4 4.0 4.0 4.2 4.2 4.2 5.2 4.7 4.7 4.7 4.7 5.9 5.9 6.2 6.3 6.3 Sovereign yields 1.4 1.7 1.8 1.9 2.0 2.1 3.7 3.8 3.9 4.0 4.1 3.7 3.8 3.9 4.0 4.1
Sources: Norwegian Authorities; and IMF staff estimates.
View Table Table 7.
Bank Stress Test Assumptions
(Y-o-y percentage change in relevant factors; unless otherwise stated)
Baseline Scenario Adverse Scenario Adverse Scenario (with policy response) (without policy response) 2014 2015 2016 2017 2018 2019 2015 2016 2017 2018 2019 2015 2016 2017 2018 2019 GDP, mainland Norway 2.5 1.5 2.0 2.3 2.5 2.5 0.1 −2.8 −1.4 −0.4 0.2 −0.6 −3.4 −2.0 −0.8 0.0 Nominal house prices 2.3 6.6 3.5 2.6 2.6 2.6 −3.0 −10.8 −9.6 −5.4 −3.9 −4.5 −11.6 −10.7 −6.6 −5.2
Nominal commercial real estate prices
9.8 6.6 3.5 2.6 2.6 2.6 −1.4 −10.8 −9.6 −5.4 −3.9 −2.9 −11.6 −10.7 −6.6 −5.2 Equity prices 0.0 0.0 0.0 0.0 0.0 0.0 −26.0 0.0 0.0 0.0 0.0 −26.0 0.0 0.0 0.0 0.0 Key policy rate 1.5 1.2 1.2 1.5 1.5 1.5 0.5 0.0 0.0 0.0 0.0 1.2 1.2 1.5 1.6 1.6 3-month NIBOR rate 1.7 1.4 1.4 1.7 1.7 1.7 2.5 2.0 2.0 2.0 2.0 3.2 3.2 3.5 3.6 3.6 Lending rates, households 4.3 3.8 3.8 4.0 4.0 4.0 5.1 4.6 4.6 4.6 4.6 5.8 5.8 6.1 6.2 6.2
Lending rates, non-financial enterprises
4.4 4.0 4.0 4.2 4.2 4.2 5.2 4.7 4.7 4.7 4.7 5.9 5.9 6.2 6.3 6.3 Sovereign yields 1.4 1.7 1.8 1.9 2.0 2.1 3.7 3.8 3.9 4.0 4.1 3.7 3.8 3.9 4.0 4.1
Sources: Norwegian Authorities; and IMF staff estimates.
28. These assumptions are similar to the authorities’ own stress tests and represent very severe shocks
. The combined shock under the first two scenarios is somewhat milder than that of the authorities’ own stress tests (Stresstest I), while the third FSAP scenario represents a stronger shock (than assumed by the FSA stress tests).
FSAP Insurance Stress Test Results
29. Overall, the stress level in the solvency test was higher for insurers than under the macro-financial scenario used for the banking stress test
. This results from the conservativeness of the FSA’s own stress test specifications and the addition of further shocks in the FSAP stress test.
A. Life Insurance
30. Solvency indicators of life insurers drop substantially under all three scenarios
. In fact, the system’s capital buffer would be wiped out under all three (severe shock) scenarios: The system’s buffer capital utilization (BCU) ratio (reverse of the Solvency Coverage Ratio, SCR) would increase to 139 percent, 142 percent, and 180 percent under the first, second, and third scenarios, respectively.
13
The companies’ capital shortfall to fully cover all the risks (without restoring capital) would amount to NOK 32.7 billion, NOK 35.4 billion, and NOK 66.4 billion in the three scenarios, respectively, which corresponds to 39 percent, 42 percent, and 80 percent of the sample’s available capital before stress, respectively, or 1 percent, 1.1 percent, and 2.1 percent of 2014 GDP (1.3, 2.4, and 2.6 percent of mainland GDP), respectively.
31. The largest contribution to the deterioration in the life insurers’ solvency position comes from the shocks to equity prices, real estate prices, and credit spread
. The impact of equity price shock on the BCU varies between 39–60 percent. The credit spread risk, which is assumed to remain the same under all three scenarios, would be 48 percent of the buffer capital. The risk from a real estate price shock carried between 34–46 percent of the buffer capital. It should be noted that the interest rate shock has a substantial impact by increasing the value of liabilities, which affect the companies particularly adversely under the third scenario. Its net impact is much smaller, however, as the changes on the asset side and liability side partially offset each other. Using the “diversification matrix,” the overall market risks are estimated at between 126–167 percent (of the buffer capital), instead of 136–193 percent if the individual factors were just added up.
32. The estimated impact of the above risks on the companies’ regulatory capital needs is significantly reduced by the rules for the transition to Solvency II
. With the transition rules, the additional capital need under scenario 3 would decline to NOK 25 billion (0.8 percent of GDP) from NOK 66 billion (2.1 percent of GDP). The impact of the transition rules are minimal under the first and second scenarios where interest rates are assumed to increase (which would reduce insurance liabilities).
33. Furthermore, the companies may have other cushions to meet the capital needs
. First, the companies may be able to retain their profits. Second, the companies have higher levels of capital at the conglomerate level. This is in part because investments in subsidiaries have been fully deducted from own funds. In this context, the authorities should continue restricting the dividend distribution by the two companies with weaker capital adequacy until they have achieved a comfortable level of buffer capital.
Recommendations:
34. The authorities should ask the institutions with weak capital adequacy ratios to prepare a plan to rebuild capital
. This would likely be much easier in the current benign environment. Accordingly, the FSA should continue to restrict dividend distributions by these institutions until comfortable levels of capital adequacy have been achieved.
Figure 10.
Life Insurance Stress Tests: BCU After Shocks
Citation: IMF Staff Country Reports 2015, 255;
10.5089/9781513576497.002.A001
Sources: FSA/insurance companies; and IMF staff estimates.
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Life Insurance Stress Tests: BCU After Shocks
Citation: IMF Staff Country Reports 2015, 255;
10.5089/9781513576497.002.A001
Sources: FSA/insurance companies; and IMF staff estimates.
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Figure 10.
Life Insurance Stress Tests: BCU After Shocks
Citation: IMF Staff Country Reports 2015, 255;
10.5089/9781513576497.002.A001
Sources: FSA/insurance companies; and IMF staff estimates.
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B. Non-Life Insurance
36. Non-life insurers show a much higher degree of resilience in the stressed scenarios
. This reflects non-life insurers’ smaller asset-liability duration mismatches and current high capital adequacy ratios, which makes them less sensitive to the shocks applied. Furthermore, the impact of the regulatory changes under Solvency II will be more benign for non-life insurers (as the current regulatory requirements are stricter than the Solvency II requirements). The system BCU increases to 77 percent, 78 percent, and 85 percent under the three scenarios, with all companies at or below 100 percent
37. For the non-life insurers, the underwriting (non-life and health) shocks and market shocks are the main contributors to the decline in solvency ratios
. Overall, the scenarios affect the non-life sector adversely via the reduced value in assets, and subsequently via lower available capital. The value of liabilities is also affected as technical provisions will be discounted in the Solvency II framework, but this would improve the capital adequacy.
14
38. The analysis with regard to catastrophe risks revealed a limited effect
. This is because the large non-life companies have wide-ranging coverage through the Norwegian Natural Perils Pool and its associated foreign reinsurers.
C. Aggregating Banking and Insurance Stresses
39. At a conglomerate level, financial institutions could weather the combined losses from their banking and insurance operations
. Recapitalizing their insurance companies would be within the capacity of the corresponding conglomerates, owing to the small size of the capital required as compared to the level of aggregate capital in the group. On the other hand, raising capital would be a challenge for the conglomerates with their core activity in the insurance business.
Recommendations
40. The insurance business of conglomerates should be adequately capitalized on a solo basis
. Under a crisis scenario, there would be competing claims on the capital of the conglomerates and it may not be easy for the insurance companies to get the needed capital. In this context, the authorities should identify systemically important insurance companies, ask them to prepare a resolution plan as advised in the Financial Stability Board’s Key Attributes (see also the accompanying FSAP technical note on crisis preparedness and bank resolution), and conduct their resolvability assessment.
Figure 11.
Non-Life Insurance Stress Tests: BCU After Shocks
Citation: IMF Staff Country Reports 2015, 255;
10.5089/9781513576497.002.A001
Sources: FSA/insurance companies; and IMF staff estimates.
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View Full Size Figure 11.
Non-Life Insurance Stress Tests: BCU After Shocks
Citation: IMF Staff Country Reports 2015, 255;
10.5089/9781513576497.002.A001
Sources: FSA/insurance companies; and IMF staff estimates.
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Figure 11.
Non-Life Insurance Stress Tests: BCU After Shocks
Citation: IMF Staff Country Reports 2015, 255;
10.5089/9781513576497.002.A001
Sources: FSA/insurance companies; and IMF staff estimates.
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Appendix I. Short Description of the Methodology for Insurance Stress Tests
Following EIOPA (2014), the solvency capital requirements were estimated as follows:
15
1. Market risks were estimated as the sum of the below risks, using the so-called “correlation matrix” as in EIOPA (2014)
. Capital requirements for interest rate risk
were estimated as the change in net value of assets minus liabilities due to re-valuation of interest rate sensitive items using parallel shifts in the term structure. The stress causing the revaluations was assumed to be instantaneous. The underlying methodology is the duration analysis.
Capital requirement for equity risk
were assessed as the change in the net value of assets minus liabilities after the applied shocks to equity prices. Two types of assets are differentiated: the so-called Type 1 equities include equities listed in regulated markets in countries which are members of the EEA or the OECD. Type 2 equities comprise equities listed in stock exchanges in countries which are not members of the EEA or OECD, equities which are not listed, hedge funds, commodities and other alternative investments. Shocks for Type 2 assets were assumed to be stronger. Then, the capital requirement for equity risk was estimated using the so-called correlation matrix as in EIOPA (2014).
Capital requirements for property risk
were estimated as the change in the net value of assets minus liabilities due to price shocks, applied to the stock of real estate investments.
Capital requirements for currency risk were estimated as the change in the net value of assets minus liabilities due to exchange rate movements, applied to the stock of FX positions, and taking into account derivative positions.
Capital requirement for spread risk
was estimated using the EIOPA suggested spread risk factors, based on the rating and duration of assets. This risk applies to the following classes of bonds: corporate bonds; subordinated debt investments, depending on the contractual terms; investment instruments with equity and bond features; covered bonds; loans other than retail loans secured by a residential mortgage; securitization positions; and credit derivatives other than for hedging purposes. A risk factor of zero percent applies to certain exposures such as exposures to EEA States’ central government and central banks and instruments issued by a multilateral development bank.
Capital requirement for risk concentrations
was calculated in three steps:
(1) The relative excess exposure per single name exposure is calculated as:
XS i = max ( 0 , E i / Assets xi − CT ) .
where the relative excess exposure threshold CT, depending on the credit quality step of single name i, is set as follows:
Credit quality step Relative excess exposure threshhold (CT) 0 3.0% 1 3.0% 2 3.0% 3 1.5% 4 1.5% 5 1.5% 6 or unrated 1.5% View Table Credit quality step Relative excess exposure threshhold (CT) 0 3.0% 1 3.0% 2 3.0% 3 1.5% 4 1.5% 5 1.5% 6 or unrated 1.5%
(2) The capital requirement for market risk concentration on a single name exposure was equal to the loss in the basic own funds that would result from an instantaneous relative decrease in the value of the assets corresponding to the single name exposure i equal to: XSi*gi, where the parameter
gi
, depending on the credit quality step of the counterparty, is determined as follows:
Credit quality step 0 1 2 3 4 5 6 Unrated Risk factor, gi 12 12 21 27 73 73 73 73 View Table Credit quality step 0 1 2 3 4 5 6 Unrated Risk factor, gi 12 12 21 27 73 73 73 73
(c) Single name exposures were aggregated.
2. Life underwriting risk
, 16
health underwriting risk, non-life underwriting risks, non-life catastrophe risk, and counterparty default risks were estimated as in EIOPA (2014), with some simplifications used in the FSA’s stress tests)
. The calculations had been carried out by insurance companies independent of the FSAP exercise. The FSAP team used these estimations as given.
3. The total capital needs for the above risks before operational risks were estimated using a correlation matrix as in EIOPA (2014)
.
4. Then, to derive the total solvency capital need, operational risks were estimated as follows
: SCR op = min ( 0.3 * BSCR; Op ) + 0.25 * Exp ul ,
where BSCR stands for basic solvency capital ratio, Op stands for basic operational risk charge for all business other than life insurance where the investment risk is borne by the policyholders, and Expul is the amount of expenses incurred during the previous 12 months in respect of life insurance where the investment risk is borne by the policyholders, excluding acquisition expenses.
Finally, the
buffer capital utilization ratio
was estimated as the ratio of the companies’ buffer capital (under Solvency II) to the solvency capital need. The hurdle rate is 100 percent. Any ratio above this would mean that the capital would be depleted.
Appendix II. Stress Test Matrix (STeM) for the Insurance Sector
Domain Assumptions
Bottom-Up by Insurance Corporations
Insurance Sector: Solvency Risk
1. Institutional Perimeter Institutions included
Three large life insurance companies
Three large non-life insurance companies
Market share
Life: 80 percent (assets)
Non-Life: 60 percent (premiums); 51 percent assets
Data and baseline date
Data provided by the FSA
Reference date: 31/12/2014 Solo-entity basis
2. Channels of Risk Propagation
Methodology
IMF&FSA staff estimates and companies’ internal models
Valuation
Market-consistent valuation of assets and liabilities
Stress test horizon
Applying cumulative changes in 2015-19 in bank stress testing scenarios
Instantaneous shocks in sensitivity analyses
3. Tail shocks
A combination of single factor analysis
Scenario 1 and 2. Severe declines in asset prices, increasing interest rates
Scenario 3: Severe declines in asset prices, and a sudden decline in interest rates
4. Risks and Buffers
Risks/factors assessed
Interest rates, equity, property, FX, credit spreads, lapses, concentration risks
Underwriting risks, counterparty risks, operational risks
Summation of risks within scenarios with diversification effects
Buffers
Absorption effect of technical provisions (profit sharing and policyholder buffer funds) for some products
Behavioral adjustments
Limited to rules in place at the reference date
5. Regulatory and Market-Based Standards and Parameters
Calibration of risk parameters
Interest rates: +250 bp parallel shift/-100 bp parallel shift
Equity: -26 percent;-45 percent for ordinary shares and -55 percent for others)
Real estate: -29 percent, -33 percent, and -40 percent
FX: 6.5/5.6/30 percent depreciation of NOK
Corporate spreads: ratings based
Default of largest banking counterparty: 45 percent LGD on obligations
Regulatory/Ac counting and Market-Based Standards
Solvency II
6. Reporting Format for Results
Output presentation
Impact on the buffer capital
Capital shortfall for companies with a BCU above 100 percent
Contribution of individual shocks
View Table Domain Assumptions
Bottom-Up by Insurance Corporations
Insurance Sector: Solvency Risk
1. Institutional Perimeter Institutions included
Three large life insurance companies
Three large non-life insurance companies
Market share
Life: 80 percent (assets)
Non-Life: 60 percent (premiums); 51 percent assets
Data and baseline date
Data provided by the FSA
Reference date: 31/12/2014 Solo-entity basis
2. Channels of Risk Propagation
Methodology
IMF&FSA staff estimates and companies’ internal models
Valuation
Market-consistent valuation of assets and liabilities
Stress test horizon
Applying cumulative changes in 2015-19 in bank stress testing scenarios
Instantaneous shocks in sensitivity analyses
3. Tail shocks
A combination of single factor analysis
Scenario 1 and 2. Severe declines in asset prices, increasing interest rates
Scenario 3: Severe declines in asset prices, and a sudden decline in interest rates
4. Risks and Buffers
Risks/factors assessed
Interest rates, equity, property, FX, credit spreads, lapses, concentration risks
Underwriting risks, counterparty risks, operational risks
Summation of risks within scenarios with diversification effects
Buffers
Absorption effect of technical provisions (profit sharing and policyholder buffer funds) for some products
Behavioral adjustments
Limited to rules in place at the reference date
5. Regulatory and Market-Based Standards and Parameters
Calibration of risk parameters
Interest rates: +250 bp parallel shift/-100 bp parallel shift
Equity: -26 percent;-45 percent for ordinary shares and -55 percent for others)
Real estate: -29 percent, -33 percent, and -40 percent
FX: 6.5/5.6/30 percent depreciation of NOK
Corporate spreads: ratings based
Default of largest banking counterparty: 45 percent LGD on obligations
Regulatory/Ac counting and Market-Based Standards
Solvency II
6. Reporting Format for Results
Output presentation
Impact on the buffer capital
Capital shortfall for companies with a BCU above 100 percent
Contribution of individual shocks
1
Prepared by Mr. Etibar Jafarov (MCM).
2
A unit-linked insurance plan is basically a combination of insurance and investment. A part of the premium paid is utilized to provide insurance cover to the policyholder while the remaining portion is invested in various equity and debt schemes. In other words, the money collected by the insurance provider is utilized to form a pool of funds that is used to invest in various market instruments (debt and equity) in varying proportions similar to mutual funds.
3
Generally, FX positions are hedged. Losses/gains related to these FX hedges as well as counterparty risks were estimated in the stress tests described in the next chapter. Rollover risks were not separately estimated.
4 http://www.FT.no/Global/Venstremeny/Brev_vedlegg/2013/New_mortality_table_for_collective_pension_insurance.pdf 5
Non-life insurers have large fluctuation provisions, which are included partly in the solvency margin capital. The Natural Perils Fund, which can only cover claims related to natural perils, is also partly included in the solvency margin capital.
6
Low interest rates heighten the reinvestment risk for new funds, and increase the present value of future claims (under Solvency II), which could give rise to reserve deficiencies. In this context, insurers have significant asset-liability maturity mismatch that affects their risk profile: life insurers’ liability duration is about 16 years while asset duration is about 4 years; non-life insurers’ liability duration is about 4 years compared with 2.5 years for asset duration.
7
The maximum guaranteed rate for new polices has been reduced several times, and will be reduced from 2.5 percent to 2 percent starting from January 2015. The new rate will be used in the valuation of only new liabilities and does not affect the valuation of existing liabilities.
8
Solvency II will not be implemented for Norwegian pension funds, but pension funds will need to conduct Solvency II stress tests and report their results.
9
There is also a possibility of spillover risks to banks from insurance companies’ selling their claims on banks.
10
This reflects the method used in Solvency II, where the interest rate shock is relative to the current interest rate.
11
The use of solo-based data allows better coverage of intra-group exposures and transactions. Given that the insurance operations of most conglomerates constitute a relatively small share of their total operations, using consolidated data would not allow full coverage of their insurance operations.
12
The assumption of a 100 bps decline in interest rates is more severe than assumed under the 2014 EIOPA stress tests, but is plausible given softening demand in Norway (in light of sharp declines in oil prices). Furthermore, declining (and sometimes negative) interest rates in Norway’s key trading partner countries may put downward pressure on interest rates in Norway.
13
While these results are similar to the results of the authorities’ Stresstest I (under Solvency II), the authorities’ Stresstest II (under Solvency I) and the companies’ own stress tests (performed on a consolidated level) suggest much less vulnerability to shocks.
14
Technical provisions in non-life insurance are not discounted under the Norwegian valuation framework which means that companies (and ultimately policyholders) have an additional buffer to withstand shocks under Solvency II.
15
The detailed methodology and technical specifications by the EIOPA (“Technical Specification for the Preparatory Phase (Part I)”) can be found here:
https://eiopa.europa.eu/Pages/SearchResults.aspx?k=Technical%20Specification%20for%20the%20Preparatory%20Phase%20%28Part%20I%29 .
Some simplifications have been made in the stress test. The stress test instructions (in Norwegian only) can be found here:
http://www.finanstilsynet.no/no/Forsikring-og-pensjon/Skadeforsikring/Tilsyn-og-overvakning/Rapportering/Stresstester/ . 16
Life underwriting risks consist of four sub-modules for mortality risk, longevity risk, disability/morbidity risk, and lapse risk. The life catastrophe sub-module is restricted to (re)insurance obligations contingent on mortality, where an increase in mortality leads to an increase in technical provisions.
Catastrophe risk stems from extreme or irregular events (e.g., a pandemic event) whose effects are not sufficiently captured in the other life underwriting risk sub-modules.
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Norway: Financial Sector Assessment Program-Technical Note-Insurance Sector Stress Tests
Author:
International Monetary Fund. Monetary and Capital Markets Department
Volume/Issue:
Volume 2015: Issue 255
Publisher: International Monetary Fund ISBN: 9781513576497 ISSN: 1934-7685 Pages: 37 DOI: https://doi.org/10.5089/9781513576497.002 Search Issue Journal Table of Contents Front Matter
Norway: Financial Sector Assessment Program-Technical Note-Insurance Sector Stress Tests
Headings Keywords Background Recent Performance Risks and Vulnerabilities
Stress Test Framework and Assumptions
A. The FSA’s Insurance Stress Testing Framework
B. FSAP Stress Test Assumptions
FSAP Insurance Stress Test Results
A. Life Insurance B. Non-Life Insurance
C. Aggregating Banking and Insurance Stresses
Appendix I. Short Description of the Methodology for Insurance Stress Tests
Appendix II. Stress Test Matrix (STeM) for the Insurance Sector
Figures Export Figures View in gallery Figure 1.
The Size of the Insurance Sector
View in gallery Figure 2.
Norway: Concentration in the Insurance Sector
View in gallery Figure 3.
Product Allocation in Life Insurance
View in gallery Figure 4.
Investment Portfolio Allocation: Life Insurers (2013)
View in gallery Figure 5.
Investment Portfolio Allocation: Non-life Insurers (2013)
View in gallery Figure 6.
Portfolio Allocation to Public and Private Sector Bonds (2013)
(In percent) View in gallery Figure 7.
Insurance Sector Performance Indicators Under Solvency I
View in gallery Figure 8.
Combined Ratio for the Non-life Segment in OECD Countries (2012–2013)
(In percent) View in gallery
Norway: Interest Rate Developments
(In percent) View in gallery Figure 9.
Life Expectancy At Birth in Norway and OECD Countries
View in gallery Figure 10.
Life Insurance Stress Tests: BCU After Shocks
View in gallery Figure 11.
Non-Life Insurance Stress Tests: BCU After Shocks
Close View raw image Figure 1.
The Size of the Insurance Sector
View raw image Figure 2.
Norway: Concentration in the Insurance Sector
View raw image Figure 3.
Product Allocation in Life Insurance
View raw image Figure 4.
Investment Portfolio Allocation: Life Insurers (2013)
View raw image Figure 5.
Investment Portfolio Allocation: Non-life Insurers (2013)
View raw image Figure 6.
Portfolio Allocation to Public and Private Sector Bonds (2013)
(In percent) View raw image Figure 7.
Insurance Sector Performance Indicators Under Solvency I
View raw image Figure 8.
Combined Ratio for the Non-life Segment in OECD Countries (2012–2013)
(In percent) View raw image
Norway: Interest Rate Developments
(In percent) View raw image Figure 9.
Life Expectancy At Birth in Norway and OECD Countries
View raw image Figure 10.
Life Insurance Stress Tests: BCU After Shocks
View raw image Figure 11.
Non-Life Insurance Stress Tests: BCU After Shocks
Metrics
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Bottom-Up by Insurance Corporations
Insurance Sector: Solvency Risk
1. Institutional Perimeter Institutions included
Three large life insurance companies
Three large non-life insurance companies
Market share
Life: 80 percent (assets)
Non-Life: 60 percent (premiums); 51 percent assets
Data and baseline date
Data provided by the FSA
Reference date: 31/12/2014 Solo-entity basis
2. Channels of Risk Propagation
Methodology
IMF&FSA staff estimates and companies’ internal models
Valuation
Market-consistent valuation of assets and liabilities
Stress test horizon
Applying cumulative changes in 2015-19 in bank stress testing scenarios
Instantaneous shocks in sensitivity analyses
3. Tail shocks
A combination of single factor analysis
Scenario 1 and 2. Severe declines in asset prices, increasing interest rates
Scenario 3: Severe declines in asset prices, and a sudden decline in interest rates
4. Risks and Buffers
Risks/factors assessed
Interest rates, equity, property, FX, credit spreads, lapses, concentration risks
Underwriting risks, counterparty risks, operational risks
Summation of risks within scenarios with diversification effects
Buffers
Absorption effect of technical provisions (profit sharing and policyholder buffer funds) for some products
Behavioral adjustments
Limited to rules in place at the reference date
5. Regulatory and Market-Based Standards and Parameters
Calibration of risk parameters
Interest rates: +250 bp parallel shift/-100 bp parallel shift
Equity: -26 percent;-45 percent for ordinary shares and -55 percent for others)
Real estate: -29 percent, -33 percent, and -40 percent
FX: 6.5/5.6/30 percent depreciation of NOK
Corporate spreads: ratings based
Default of largest banking counterparty: 45 percent LGD on obligations
Regulatory/Ac counting and Market-Based Standards
Solvency II
6. Reporting Format for Results
Output presentation
Impact on the buffer capital
Capital shortfall for companies with a BCU above 100 percent
Contribution of individual shocks
View Full Size Figure 11.
Non-Life Insurance Stress Tests: BCU After Shocks
Citation: IMF Staff Country Reports 2015, 255;
10.5089/9781513576497.002.A001
Sources: FSA/insurance companies; and IMF staff estimates.
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