ENVIRONMENT AND INSURANCE

André Gustavo Morandi da Silva

Estevão Kopschitz Xavier Bastos

José Gustavo Féres

ENVIRONMENT

AND INSURANCE

Research Paper 04November 2017

ã

André Gustavo Morandi da SilvaEstêvão Kopschitz Xavier Bastos


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RESEARCH PAPER

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André Gustavo Morandi da SilvaHas a bachelor degree in Economics from the Fluminense Federal University (1982). Fulfilled the Master’s credits in Production Engineering (COPPE/UFRJ, 1999). Has experience in the field of Economics, focusing on Statistical Methods and Models. Has experience in the areas of Finance and Investment Management, with emphasis in Project Finance and Structured Finance. Investment Analyst. CNPI/APIMEC – National Certificate of the Investment Professional/Analysts and Capital Market Professionals Association. Specialist in Regulation and Risk Management (Banks, Insurance Companies/Reinsurers and Pension Funds). Author and co-author of articles.

Estêvão Kopschitz Xavier BastosEconomist with Masters in Economics from PUC - Rio de Janeiro and MBA in Finances from COPPEAD/UFRJ. Chief economist and partner at Macrometrica Pesquisas Economicas Ltda (1991 to 2000), chief economist at Fundacao Petrobras de Seguridade Social – Petros (2000 to 2003), financial specialist at LLX Logistica S.A. - currently, Prumo Logistica Global S.A. (2007-2009). Economist of the Grupo de Acompanhamento Conjuntural and researcher of the Instituto de Pesquisa Economica Aplicada – Ipea (2004-2007 and 2009-present). Author of articles, book chapters and the book “Guia de Análise da Economia Brasileira” (Ed. Fundamento, 2015).

José Gustavo Féres Graduated in Economics from Pontificia Universidade Catolica do Rio de Janeiro (PUC-Rio), Master’s degree in Mathematical Economics and PhD in Economics from Universite de Toulouse 1. Works as a Technician at Planejamento e Pesquisa do Instituto de Pesquisa Economica Aplicada (IPEA). Also works as a professor at the Escola de Pos-Graduacao em Economia da Fundacao Getulio Vargas (EPGE/FGV). Has experiences in the field of enviromental economics, working mainly on the following topics: climate change, biofuels and application of economic instruments to environmental management.Participated as contributing author of the Quinto Relatorio de Avaliacao do Painel Intergovernamental de Mudancas Climatica and as the main author of the Primeiro Relatorio de Avaliacao Nacional do Painel Brasileiro de Mudancas Climaticas.

ENvIRoNMENt ANd INSuRANCE

4

Virginia Thome – CRB-7/3242

Responsible for the production of the cataloguing dataa

S578m Silva, Andre Gustavo Morandi da

Environment and Insurance / Andre Gustavo Morandi da Silva; Estevao Kopschitz Xavier Bastos;

Jose Gustavo Feres.

– Rio de Janeiro: BSI-CRIE, 2017.

115 pages; 21 cm (Research Text, number 4)

ISBN Nº 978-85-7052-627-4 (text in Portuguese).

ISBN Nº 978-85-7052-632-8 (text in English)

1. Environmental Insurance. 2. Environmental Risk – Insurance. 3. Environment – Risk –

Management. I.

Bastos, Estevao Kopschitz Xavier. II. Feres, Jose Gustavo. III. Series. IV. Title.

0017-1878 CDU 502:368


SuMMARY

Presentation ................................................................................................................................. 7

ChAptER 1ENvIRoNMENt ANd INSuRANCE: GENERAl INtRoduCtIoN ANd RElEvANCEoF thE thEME ......................................................................................................................... 8

1. Relevance of the subject in the world ............................................................................. 8 1.1. The growing importance of the environmental issue and the insertion of the insurance industry into the international climate convention ....................................... 8 BOX – Definitions (1) ................................................................................................... 10 1.2. Increase on frequency and on losses caused by disasters ............................................ 10

2. Relevance for Brazil .......................................................................................................... 12 BOX – Definitions (2) ............................................................................................................ 14

3. overview of the different stages of an environmental risk management plan, highlighting the role of insurance ................................................................................... 14 3.1. Freeman et al. (2001) Approach .................................................................................. 15 3.2. Defra Approach: Management of environmental risk in four stages............................. 17 BOX – Definitions (3) ................................................................................................... 19

4. Advantages and limitations of insurance for environmental risks .............................. 19 4.1. Advantages ................................................................................................................. 19 4.2. Limitations .................................................................................................................. 20

5. Case studies ....................................................................................................................... 20 5.1. Estimated costs of flood damage to agriculture ........................................................... 20 5.2. Japan and the United States ........................................................................................ 21 Bibliography ................................................................................................................ 23 Annex A – Major disasters in Brazil .............................................................................. 24

ChAptER 2 ENvIRoNMENtAl INSuRANCE: MICRoECoNoMIC ASpECtS ................................................. 28

1. Introduction ....................................................................................................................... 28


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2. Allocation of risks: the classic Arrow-Borch model ......................................................... 29

3. Environmental risks and market failures ......................................................................... 30 3.1 Ambiguity ................................................................................................................... 30 Box 1: Aversion to ambiguity ...................................................................................... 31 3.2 Asymmetry of information .......................................................................................... 34 Box 2: Case study - agricultural insurance and moral hazard in the North American Corn Belt .................................................................................................... 37 3.3 Limited liability ............................................................................................................ 41 Box 3: Case study – CERCLA ....................................................................................... 42 3.4 Solvency of insurers .................................................................................................... 43 Box 4: Case study – September 11, 2001 and the Terrorism Risk Insurance Act ........... 45 3.5 Assessment of environmental damage ........................................................................ 46 3.6 Dynamic aspects: realized risks .................................................................................... 47

4. Conclusions and policy recommendations ...................................................................... 49 Bibliography ......................................................................................................................... 52

ChAptER 3AlloCAtIoN oF ENvIRoNMENtAl RISKS IN INSuRANCE ANd REINSuRANCE:RISK MANAGEMENt, StRAtEGIES ANd pRotECtIoN GAp IN thE BRAzIlIAN MARKEt .... 54 Introduction ....................................................................................................................... 54

1. Characterization of Environmental Risks......................................................................... 56

2. Measurement of Environmental Risk and Solvency ....................................................... 70

3. Retention and Risk transfer Strategies in Insurance and Reinsurance in the light of Environmental Risks ........................................................................................... 85

4. Retention and transfer in the Great Risks in the Brazilian Market and the Mariana Case ....................................................................................................... 101

5. Conclusions and Recommendations ............................................................................... 110

Bibliography ......................................................................................................................... 114

André Gustavo Morandi da Silva • Estêvão Kopschitz Xavier Bastos • José Gustavo Féres

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Research Paper 04 November 2017

Introduction

This report aims to present the initial results of the project “Environment and insurance”, prepared for the Centre for Research on Insurance Economics of the Brazilian School of Insurance. The text is divided into three chapters.

Chapter 1 contextualizes the research theme. Firstly, we present stylized facts that suggest a global trend of more frequent environmental disasters with growing economic losses. The discrepancy between the total losses resulting from these disasters and the losses covered by insurance - the so-called coverage gap - is also highlighted. Next, the role of the insurance industry as a risk transfer and mitigation mechanism within an environmental risk management plan is discussed.

Chapter 2 investigates the reasons for this coverage gap. Despite the potential risk transfer and mitigation capabilities, the reach of the environmental insurance market is still limited. What are the reasons why agents make limited use of environmental insurance? Why environmental insurance, when offered, have such high premiums? What measures can be taken to correct eventual inefficiencies and expand this market? Several studies address these issues. The chapter summarizes the main findings of this literature.

Finally, chapter 3 contextualizes the protection gap identified in the previous chapter within the Brazilian insurance and reinsurance market. Specifically, the text discusses the following question: what factors explain, in the Brazilian insurance market, the protection gap in coverage of environmental risks above the international average? To answer this question, it is necessary to establish an understanding of the behavioral pattern and business strategies of the national insurance and reinsurance market with respect to its retention and transfer of large risks, particularly those related to the environment.


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The environmental issue has gained relevance in the last decades. The perception that the natural resources are finite and the strong increase of their consumption, resulting from the economic growth that accelerated from the Industrial Revolution, has strengthened the concern with the sustainability of the economic activities. Similarly, attention to social issues such as poverty, inequality and the impact on local communities of economic enterprises has also gained ground, so that these three dimensions - economic, social and environmental - are increasingly being treated in an integrated way.

Some typically economic notions are also favorable to the environment. Efficient allocation of resources and the pursuit of technological progress, in order to do more with the same amount of resources, or, equivalently, produce the same using less resources, naturally spares nature’s resources. Economists see pollution from productive activities as a non-internalized cost, such as the use of a resource - for example, a river in which untreated waste is dumped in - without paying for it. Society as a whole incurs the cost by having the river polluted, but the company that pollutes it has no incentive to spare that resource, since it does not pay for it. Some ways of internalizing this cost in company accounts is often well regarded by economists, such as government taxation of pollution. With the economic incentive, the company will reduce or eliminate

ENvIRoNMENt ANd INSuRANCE: GENERAl INtRoduCtIoN ANd RElEvANCE oF thE thEME

1. Relevance of the subject in the world 1.1. the growing importance of the environmental issue and the insertion of the

insurance industry into the international climate convention

ChAptER 1

André Gustavo Morandi da SilvaEstêvão Kopschitz Xavier Bastos


Research Paper 04Rio de Janeiro, February 2017


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pollution. These are small examples of the interaction between economic motivation and environmental results to introduce the idea that, similarly, the typical behaviors of economic agents in the insurance industry also affect environmental issues. For example, the greater care with which the policy holder deals with the insured property, generated by the existence of deductibles, can also lead to greater care in the prevention of man-made environmental accidents or more prevention and mitigation of risks related to natural disasters.

The environmental issue has been increasingly influenced by the concerns about climate change that human activity can cause. At the Rio-Summit, the United Nations Conference on Environment and Development, held in Rio de Janeiro in 1992, the final declaration included the adoption of the United Nations Framework Convention on Climate Change (UNFCCC). The UNFCCC established guidelines for actions focused on stabilizing the concentration of greenhouse gases in the atmosphere to avoid “dangerous anthropogenic interference with the climate system”. There is currently extensive international adherence to the UNFCCC, and the Conference of the Parties (COP) updates the implementation of the UNFCCC. In the third convention of the parties - COP3 - in Kyoto, Japan, a protocol was created obliging the signatory countries to commit themselves to greenhouse gas emission reduction. The detailed rules for the implementation of the Kyoto Protocol were adopted at COP7 in Marrakesh, Morocco, in 2001.1

COP21, held in Paris, in December 2015, formally included, in its final document, insurance as a relevant mechanism for environmental risk management. In the text “Adoption of the Paris Agreement”, subsection III, “Decisions to give effect to the agreement”, in dealing with losses and damages, says that there must be the “establishment of a clearinghouse for risk transfer that serves as a repository of insurance and risk transfer information, to facilitate the parties’ efforts in developing and implementing global risk management strategies.” The text of the Agreement itself, in its article 8, establishes that:

Parties recognize the importance of averting, minimizing and addressing loss and damage associated with the adverse effects of climate change, […] and the role of sustainable development in reducing the risk of loss and damage. […] areas of cooperation and facilitation to enhance understanding, action and support may include: (a) Early warning systems; (b) Emergency preparedness; (c) Slow onset events; (d) Events that may involve irreversible and

1 See http://www.cop21paris.org/about/cop21/ and http://unfccc.int/kyoto_protocol/items/2830.php, consulted in 22/12/2016.


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permanent loss and damage; (e) Comprehensive risk assessment and management; (f) Risk insurance facilities, climate risk pooling and other insurance solutions; (g) Non-economic losses; and (h) Resilience of communities, livelihoods and ecosystems.

The Geneva Association- “International Association for the Study of Insurance Economics” in a September 2016 document (Golnaraghi et al, 2016) makes reference to this inclusion of insurance in COP21:“... the explicit inclusion of insurance in the COP21 Paris Agreement, is a reflection that all countries recognize the importance of insurance as an integral component of national climate risk management strategies” and “it is evident that the (re)insurance sector’s key role in addressing extreme event and climate risks is increasingly recognized by governments, international development organizations, the UN, and non-governmental organizations (NGOs).” (p.4).

Environmental risk, in this work, refers to two different types: risk of environmental pollution (or man-made disaster) and risk of natural disaster. Both have common characteristics, such as low probability of occurrence, potential to generate large losses, and high-risk correlation.

The risk of a natural disaster is associated with the occurrence of natural phenomena such as earthquakes, floods, hurricanes, tsunamis and landslides. These events often cause loss of human lives, injuries, and material and economic losses of major proportions. The risk of environmental pollution is associated with economic activities that can adversely affect the environment, human health, damage properties, contaminate natural resources and affect biodiversity. It implies, for the owners and managers of these economic activities, the risk of legal liability for the consequences of pollution. (OECD, 2003, p.8-9).

Definitions (1)

1.2. Increase on frequency and on losses caused by disasters

Natural, and even man-made disasters, although rare, have increased in frequency and in value of loss. Graph 1 illustrates this increase between 1980 and 2015. The number of events recorded in the world, which was below 400 per year until 1986, exceeded 800 in every year since 2009.


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Graph 2 shows the evolution, over the same period, of global and insured losses. Trend lines indicate that global losses have been growing faster, which is to say that the gap in environmental risk coverage, measured by the difference between insured losses and total economic losses, is increasing.

Graph 1

Source: Munich Re NatCat Service

Graph 2

Source: Munich Re NatCat Service


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Graph 3, from another source, also shows the evolution (from 1970 to 2015) of the number of catastrophic events in the world, separately between man-made and natural events. Those caused by man were between 50 and 100 per year in the first half of the 1980s, grew in the following ten years and, from the second half of the 1990s to 2015, remained stable around 150, except from 2004 to 2008, when they surpassed 200 events per year. Natural disasters maintained a growth trend, with stabilization from approximately 1994 to 2009, to resume the upward trend from 2010.

Graph 3

Number of catastrophes (1970-2015)

It should also be noted that the growth trend in the frequency of catastrophic events and on the economic value of losses can be maintained - or even accentuated - in the coming decades. According to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, if CO2 emissions remain at current levels, the average temperature of the Earth’s surface may be warming between 2.6° and 4.8° C. Changes in these levels may increase the frequency and intensity of extreme weather events.

A 2013 study by two professors from the University of Würzburg, Germany2, suggests that emerging economies are most likely to benefit

Source: Swiss Re Economic Research & Consulting and Cat Perils.

2. Relevance for Brazil

2 F. Englmaier, T. Stowasser (2013). “The Effect of Insurance Markets on Countries’ Resilience to Disasters”, Mimeo, apud Munich Re Position paper 09october2013


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from an increase in insurance coverage against natural disasters, as they have medium-level insurance penetration, which is understood as the ratio of insurance premiums to GDP. In these countries, a relatively large number of economic assets are exposed to forces of nature with little protection. This means that a small increase in insurance coverage would bring major economic benefits in terms of reducing vulnerability. Poorer economies, with very low insurance penetration, also have few economic assets in total and countries that are already “saturated” in terms of penetration already benefit from comparatively large financial prevention and cushioning. This conclusion is illustrated in graph 4.

Graph 4

Brazil has a significant degree of exposure to environmental disasters. Annex A lists 14 natural and man-made disasters that occurred in Brazil from 1984 to 2015, which corresponds to a disaster every two years and three months, on average. The biggest and most emblematic of all was a dam burst at a mining waste site in the city of Mariana, in the state of Minas Gerais, on November 5, 2015, when there was the release of 62 million m3 of mud with tailings. The accident caused 19 deaths, left 1,265 homeless and triggered a halt to many economic activities, including those of the mining company. It is estimated that 3.5 million people were affected by lack of water. Vale, a shareholder of Samarco, owner of the dam, estimated a reduction of US $ 443 million over its result for the 2016 year. Lawsuits request compensation of R$ 20.2 billion to Samarco, with possible liability of Vale and BHP (another shareholder)


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and repair of environmental damages in a period of 10 years. Ibama’s3

preliminary fines were of R$ 250 million and the company will bear all the individual and collective indemnification costs and the environmental recovery of the impacted area. Samarco signed a Term of Adjustment of Conduct with the Public Ministry of Minas Gerais, for which it must maintain a fund in the amount of R$ 1 billion fully allocated to the recovery of the Rio Doce river. Terra Brasis Reinsurance estimated economic losses at R$ 26 billion, while the estimated insured amount was of R$ 2.3 billion, that is, less than 10%.

The terms hazard and risk are often used interchangeably, but it is important to establish the difference between them. A hazard is a potential source of harm; a risk is the probability of that damage materializing. Example: if there is a spill of water in an room, it represents a hazard to persons passing through it, that is, a potential source of injury for them. If access to that area is prevented by a physical barrier, the hazard (source of danger) will remain there, but the risk of injury will have been diminished.4 The assessment of a risk involves the analysis of the consequences and the probability of a hazard materializing.5

Definitions (2)

In light of the increasing frequency of environmental disasters and potential economic losses, several experts point to the need to formulate environmental risk management plans.

By proposing comprehensive and integrated strategies for addressing environmental disasters, management plans are revealed to be effective tools in reducing vulnerability to disasters and directly related economic costs. Two additional reasons justify the adoption of these plans. First, if disaster impacts are not anticipated, the allocation of resources to emergency actions generates high opportunity costs, since resources for projects that contribute to economic growth or poverty eradication need to be discontinued and redirected to the implementation of emergency post-disaster interventions. Second, the reallocation of resources for emergency

3 Brazilian Institute of the Environment and Renewable Natural Resources, linked to Brazilian Ministry of the Environment.

4 Defra (2011), caption of figure 1, p.7.

5 Health and Safety Authority of Ireland (http://www.hsa.ie/eng/Topics/Hazards/).

3. Overview of the different stages of an environmental risk management plan, highlighting the role of insurance


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disaster response creates difficulties in the planning and execution of the budget process. Budgetary reassignments are difficult political processes. The Mexican case of 1988 is illustrative: throughout the year, six changes in the federal budget were required to deal with natural disasters. These shifts jeopardized the fragile political agreements that underpinned the approved budget proposal, generating institutional frictions.

The insurance sector plays a relevant role in the different stages of an environmental risk management plan. In this section, two approaches are presented, in which insurance is inserted in the framework of these plans: the proposal by Freeman et al. (2001), working for the Inter-American Development Bank (IDB), and the proposal by the Department for Environment, Food & Rural Affairs of the UK Government (Defra).

In a paper developed for the Inter-American Development Bank (IDB), Freeman et al. (2001) outline an environmental risk management plan, summarized as follows: a) pre-disaster phase, comprising of a.i) risk identification; a.ii) risk mitigation; a.iii) risk transfer and a.iv) preparedness; b) post-disaster phase, divided into b.i) emergency response and b.ii) reconstruction and recovery.

In order to identify the risks, it is necessary to assess them, which, in the case of environmental risks, can be particularly difficult. The possibility of assigning value to a potential loss is directly linked to the possibility of working with insurance. Insurance can be a powerful incentive for mitigation of environmental risks, for instance, by means of deductibles or adjusted premiums. Risk transfer is a feature of insurance and reinsurance par excellence. Moreover, insurance also encourages preventive actions.

In the post-disaster phase, resources from insurance are important for reconstruction and also reduce the need to use public money, allowing the latter to be targeted to the poorest, who are typically not insured. In addition, the insurance allows the insured to know in advance the financial resources he/she would have after the disaster, while the value of the public bailout is uncertain.

The risk identification phase includes an assessment of potential threats, vulnerability studies and risk analysis. The threat assessment identifies the likely locations of occurrence and the severity of dangerous natural phenomena and its probability of occurrence within a specific period of time in a given area. These studies rely heavily on available scientific information, including geological, geomorphological and soil maps; climatic and hydrological data; topographic maps, aerial photos

3.1 Freeman et al. (2001) Approach


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and satellite images. Vulnerability studies estimate the damage that would result from the occurrence of a natural phenomenon of a given severity. They estimate physical, social and economic vulnerability. They include indirect losses, such as business interruption, and secondary losses, such as increased poverty, rising unemployment or rising external debt. The risk analysis integrates hazard assessment and vulnerability studies information to generate estimates of the probabilities of expected loss of certain threats.

Risk mitigation refers to policies and activities that reduce the vulnerability of an area to suffering damage from disasters that may occur. They consist of structural and non-structural measures that are taken before a disaster strikes. Structural mitigation projects can be highly successful from a cost-benefit perspective, but they have the potential to encourage a false sense of security if they are not united with population awareness programs. Structural measures reduce the impact of threats on the population and their properties through engineering measures. Non-structural measures are non-engineering activities and reduce the intensity of threats or vulnerability to them. Examples are land use management and planning, zoning and building codes legislation, education and training, reforestation. Non-structural measures can be encouraged by government and private incentives, such as tax codes and deductibles or adjusted premiums for insurance, which allow for private loss reduction measures.

In risk transfer, there is a significant difference between developed and developing countries. In some developed countries, the government commits to shift some of the risk of reconstruction financing after a disaster from the government to another party, usually an insurance company. A sophisticated financial system is necessary for insurance to be used as a significant tool. In many developing countries, the lack of institutionalized regulatory structures hinders the provision of insurance. Many countries are too small to allow adequate risk diversification and a national insurance scheme. The creation of regional insurance markets can increase risk diversification and the potential size of the market, making it more attractive to the insurance industry and reducing the cost of insurance. Other options for risk diversification include catastrophe bonds or access to the international reinsurance market. With small middle classes and few midsize companies - the most frequent insurance buyers in developed countries – the natural insurance clients are scarce in developing countries. Government policies need to be geared towards increasing the demand for insurance, so that an effective market is developed. Insurance for government buildings and legislation that requires families and small and medium-sized businesses to purchase insurance are possible tools to increase the demand for insurance against natural hazards. However, insurance is not an option for the very


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poor and it is possible to encourage informal and formal schemes of risk sharing by the poor outside the establishment of a formal insurance program.

Preparedness for the event involves the formation of disaster response and emergency management capacity before the occurrence of disasters, in order to facilitate an effective response when necessary. It includes warning systems, public awareness programs, development and testing of evacuation plans. In contrast to structural mitigation measures, which are often the result of major policy decisions at national levels, readiness projects tend to be directed towards the actions of individuals and organizations.

The emergency response consists of actions taken immediately before, during, and after the onset of a major disaster or large-scale emergency to minimize loss of life, injury and property damage, and increase the effectiveness of recovery. The best emergency responses are those that occur immediately after the event with sufficient resources to limit loss of life and property.

The reconstruction and recovery phase consists of programs that provide more lasting assistance to people who have suffered injuries or incurred losses. The most important recommendation for this phase is that your projects be designed to reduce future vulnerability and promote development goals.

The Department for Environment, Food & Rural Affairs of the UK Government (Defra) proposes a framework for the approach to environmental risk management composed of four phases: i) formulation of the problem; (ii) risk assessment; iii) identification and evaluation of possible management options and iv) approach to risk with the chosen strategy (Defra, 2011).

This structure is subdivided as follows:

phase 1: problem formulation

a. Identify, define, delimit the problem: risk of what, to whom, where and when

b. Develop conceptual modelc. Plan risk assessmentd. Screening and prioritizing the risks to be evaluated

3.2. defra Approach: Management of environmental risk in four stages


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phase 2: Risk assessment

e. Identify potential sources of risk, threatsf. Assess the possible consequencesg. Evaluate probabilitiesh. Characterize risk and uncertainty

phase 3: Identification and evaluation of possible management options

i. Eliminate riskj. Mitigate, with actions

i. Preventiveii. Correctiveiii. Advisory

k. Transfer, withiv. Insurancev. Contract transfer

vi. Hybrid instrumentsl. Explore opportunities in approaching riskm. Accept - make a conscious decision to tolerate risk

phase 4: Approach risk with chosen strategy

n. Eliminate, mitigate, transfer or accepto. Report the strategyp. Supervise, control, monitor residual riskq. Elaboration of contingency and continuity of activity plan

Insurance appears as an instrument to be used in the third option (transfer) of Phase 3 (Identification and evaluation of possible management options).

In choosing the strategy, the potential positive and negative effects of each should be considered in the following aspects (Defra, 2011, p.41):

i. technical factors: consider whether the options are likely to reduce the risk, how much this reduction will be and how difficult it would be to implement the option (for example, the extent of the previous research and development required);

ii. economic factors: the cost of implementing the option for the organization, affected enterprise, groups exposed to risk or society as a whole;

iii. environmental security: potential impacts of options on health and sustainability of environmental resources, including impact on existing habitats;


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iv. social issues: the social impacts of the risk, such as potential costs or other losses to the community, jobs or real estate prices, life expectancy and amenities;

v. organizational capabilities: consider the risk management capacity within the organization in question or that of the society or exposed groups.

disaster: serious disruption of the functioning of a society, community or project, causing serious or generalized human, material, economic or environmental losses that exceed the coping capacity of the affected using their own resources.

Natural hazard, risk or threat: natural processes or phenomena that affect the biosphere and can be a harmful event. These hazards include: earthquakes, windstorms, hurricanes, landslides, tsunamis, seaquakes, volcanic eruptions, floods, frosts, forest fires and droughts, risks arising from climatic variations, such as those related to the El Niño phenomenon or a combination thereof.

vulnerability: A condition determined by physical, social, economic, and environmental factors or processes that increase the susceptibility of a community to the impact of threats.

disaster risk management: the systematic process that integrates the identification, mitigation and transfer of risks, as well as the preparedness to reduce the impacts of possible disasters. It includes emergency response, rehabilitation and reconstruction to reduce the impacts of current disasters, while avoiding the resurgence of vulnerability. (IADB, 2007)

Definitions (3)

4. Advantages and limitations of insurance for environmental risks Smith (1996)6 lists advantages and limitations of insurance for environmental risks:

4.1. Advantages

• Guarantees the victims some foreseeable compensation after the losses;

• If owners in hazardous areas pay premiums that reflect their true risks and insurance payments fully compensate for victims, insurance offers equitable distribution of costs and benefits;

6 Apud Freeman et al (2001).


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• Although insurance is designed to redistribute losses, it can also be used to reduce the impacts of events by encouraging measures to minimize damages.

• In practice, owners in risk areas rarely pay premiums that actually reflect the true risk; one reason for this is that, for many environmental risks, the database is insufficient to calculate a realistic premium based on predicted annual average losses in a specific locality;

• in the residential real estate sector, many constructions are made by developers and not by future residents; these entrepreneurs would only be dissuaded from building in places of risk if insurance premiums were high enough for properties to become difficult to sell;

• private insurances may not be obtainable in very high risk areas, although this does not necessarily discourage construction;

• even when insurance is available, there is often low voluntary interest;

• even when insurance is purchased, a significant number of policy holders are underinsured and probably will not be fully refunded by the company in the event of a loss;

• although insurance may, in some circumstances, be used to reduce losses, it is believed that the existence of “moral hazard” may increase the damage; such hazard arises from the tendency of some people to, once insured, reduce their care and, thus, change the risk probabilities on the basis of which the premiums were calculated.

4.2. limitations

5. Case studies

5.1 Estimated costs of flood damage to agriculture7

Exceptional rainfall during the summer of 2007 has caused widespread flooding and economic damage in England. More than 42 thousand hectares of land were seriously affected, at the time of the year when crops were approaching and pastures were being used to feed herds or cut for storage and feeding in the winter. The 2007 floods provided a useful, albeit unfortunate, opportunity to assess the economic impact of large-scale flooding in agriculture. This is necessary to support flood

7 Defra (2011), p.48. Study conducted by the School of Applied Sciences, Cranfield University, Bedfordshire, UK.


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risk and investment options assessment, both to justify the protection of high-value agricultural land and to assess the cost of temporarily storing flood waters on agricultural land to alleviate urban damage downstream.

A survey of 78 farmers affected by floods was conducted in the West Midlands, Oxfordshire and Yorkshire, covering about 14% of the total flooded agricultural area. The average flood damage costs were estimated at £1.2 thousand per flooded hectare8, with the highest cost being observed in horticultural and vegetable crops and the lowest on pasture. More than 80% of flood damage costs were associated with production losses and additional production costs, the remainder related to damage to assets, such as machinery, property and infrastructure.

With a total of £ 50 million9, costs for agriculture were only about 2% of the estimated total economic cost of the summer floods in 2007 in England. At the farm level, flood damage costs (excluding household property) averaged about £80 thousand10, with a median of £43 thousand11. Only about 5% of agricultural losses were insured, compared to 80% in the urban sector.

A case study like this serves three main purposes: (i) provides evidence-based estimates of flood damage costs on agricultural land, (ii) helps refine methods of estimating costs of flood damage in agricultural areas and (iii) confirms the vulnerability of agriculture to extreme events and reveals how farmers can manage the flood risks associated with future climate change, including the possible use of insurance.

Although Japan and the United States are culturally diverse, the similarities in the evolution of their catastrophe management systems are impressive. Both countries have comprehensive programs at national level to manage the risks of catastrophes. An interesting parallel between the two countries can be done in the creation of public / private insurance systems to promote recovery. Japan and the US pioneered loss-sharing programs that involve governmental and private institutions in a national system, but in ways that reflect national culture.

5.2. Japan and the united States12

8 Corrected by the inflation of the Pound and converting to Reais, this value corresponds to approximately R$ 7.2 thousand, at 2015 prices.

9 R$ 300 million at 2015 prices approximately.

10 R$ 477 thousand at 2015 prices.

11 R$ 257 thousand at 2015 prices.

12 Freeman et al (2001), pag. 17.


22

In Japan, earthquake insurance is offered by private insurers included in fire insurance policies. Because premiums are set according to earthquake risk zones, they can be prohibitively expensive for many residents of high-risk areas. This is true even with substantial support given with taxpayer money into the system. In the case of large losses, the reinsurance system, which has a maximum commitment determined annually by the parliament, transfers part of the risks to the taxpayer, another part for the Japanese Earthquake Reinsurance Company and yet another part for the policyholders through pro rata payments. To transfer risks more widely, including out of Japan, some insurers issue catastrophe bonds.

A similar public-private partnership, but with significant differences, exists in the US to cover flood losses. The US government is generally reluctant to provide services that can be offered by the private sector, but in contrast to Japan, the partnership arose from the inability of the market to provide sufficient coverage. The National Flood Insurance Program (NFIP) is unique in that its policies are offered by the private sector, but the national government assumes the risks and automatically plays the role of reinsurer. An important feature of the NFIP is the effort to associate insurance with incentives to mitigate risks. To attract participants, in the past, premiums were subsidized and offered only to residents of communities that enforced land use regulations and fitted other mitigation measures. Once the community agreed to participate in the program, residences and commercial establishments located on plains with a 1% chance of flooding within a year would be required to purchase flood insurance as a condition of having a mortgage on their property insured by the federal government. In addition, the NFIP puts a lot of emphasis on deductibles as a way to encourage policyholders to take loss reduction and prevention measures.

Thus, a notable difference between public-private partnerships in insurance adopted in both countries is the greatest emphasis on incentives for individual responsibility found in the United States.


23


Bibliography

Defra (2011). Department for Environment, Food & Rural Affairs/ UK Government and Cranfield University Guidelines for Environmental Risk Assessment and Management. Green Leaves III.

Freeman, Paul; Martin, Leslie A.; Linnerooth-Bayer, Joanne; Warner, Koko; Lavell, Allan M.; Cardona, Omar D.; Kunreuther, Howard (2001). “National Systems and Institutional Mechanisms for the Comprehensive Management of Disaster Risk: Phase 1”. Inter-American Development Bank (IADB), Regional Policy Dialogue, Natural Disasters Dialogue First Meeting. Working Paper. Washington, D.C., November 15-16, 2001.

Golnaraghi, Maryam; Swenja Surminski, and Kai-Uwe Schanz (2016). “An Integrated Approach to Managing Extreme Events and Climate Risks: Towards a Concerted Public-Private Approach” (With recommendations to harness potential contributions of the insurance industry). The Geneva Association—‘International Association for the Study of Insurance Economics’, Zurich. September 2016.

IADB (2007). “Disaster risk management policy”. Inter-American Development Bank, 23 February 2007.

Munich Re (2013). “Economic consequences of natural catastrophes: Emerging and developing economies particularly affected - Insurance cover is essential”. Munich Re Economic Research Position paper, 09 October 2013.

OECD (2003). “Environmental risks and insurance: a comparative analysis of the role of insurance in the management of environment-related risks”. Policy Issues in Insurance, nº 6. Paris.

Smith (1996). “Adjustment to Hazard: Sharing the Loss” in Environmental Hazards apud IADB/Freeman et al, 2001

Terra Brasis (2016). “Terra Report – Edição especial Mariana”. Terra Brasis Resseguros S.A. São Paulo, May, 2016.


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1. 1984, fire in Vila Socó (Cubatão - SP): Petrobras underground pipelines, 93 dead.

2. 1987, Caesium 137 in Goiânia: garbage collectors broke a radiological device in the debris of a former hospital. In 1996, the court convicted three partners and one employee of the abandoned hospital for manslaughter.

3. 2000, oil leak in Guanabara Bay: Petrobras - accident with oil tanker; 1.3 million liters of oil; fines (Ibama): R$ 51.5 million

4. 2000, oil leak (4 million liters) in Araucária (PR): Petrobras refinery. Fine of R$ 168 million.

5. 2001, Petroleum Platform P-36: submerged at a depth of 1,200 meters, with an estimated 1,500 tons of oil on board, in the Campos/RJ basin. 11 deaths; insured loss of US$ 500 million; total financial impact for Petrobras of US$ 700 million, considering the loss of revenue and the value of the platform itself.

6. 2003, leak of cellulose dam in Cataguases (MG): Florestal Cataguases and Indústria Cataguases paper industry; leak of 520 thousand m³ of wastes composed of organic residues and caustic soda; Ibama: fine of R$ 50 million.

7. 2003, train derailment in Uberaba-MG: in destination to Paulínia-SP, with 18 wagons, it carried octanol, methanol, isobutanol and potassium chloride; tipping followed by explosions; 1 thousand meters of riparian forest were devastated, several animals were killed and the Alegria stream, one of the tributaries of the Uberaba River, which supplies almost 250 thousand people, was contaminated with 670 tons of chemical products; at the time, a behavior adjustment agreement (TAC) was signed with the company that owned the train in the amount of R$ 13 million, in addition to several improvement works in the city; after more than 10 years of the accident, the contaminated area is still isolated, monitored 24 hours a day and to enter, the use of protective equipment is mandatory; chemical substances are still found in the river area; a tributary stream of the

Annex A – Major disasters in Brazil13

13 Sources: Items 1 to 4, 6, 9 to 11 and 14: "http://www.ebc.com.br/noticias/meio-ambiente/2015/11/conheca-os-principais-desastres-ambientais-ocorridos-no-brasil"; items 5,7,8 and 12 to 14: Terra Brasis (2016); item 14: http://g1.globo.com/minas-gerais/desastre-ambiental-em-mariana/noticia/2016/10/mpf-denuncia-26-pessoas-por-rompimento-da-barragem-da-samarco.html


25


Uberaba River and 2.5 hectares of land are still contaminated today, causing damage to the environment and the population.

8. 2004, Tropical Cyclone Catarina (SC): winds of up to 155 km/h; “Insurance penetration, both residential and agricultural, is very low at the point of occurrence. We estimate the insured value at about 5% of economic damages (R$ 30 million).” (Terra Brasis, 2016).

9. 2007, dam disruption in Miraí (MG): Rio Pomba Cataguases Mining Company - 2,280,000 m³ of water and clay (bauxite washing); government body: fine of R$ 75 million.

10. 2008, flood in the region of the Itajaí Valley, in Santa Catarina: more than 100 deaths.

11. 2011, oil leak in the Campos Basin (RJ): Chevron; leak of 3.7 thousand barrels of oil; it is estimated that the stain caused by the spill at sea reached 162 km², the equivalent to half of the Guanabara Bay; IBAMA fines of R$ 60 million; indemnification to the Brazilian government of R$ 95 million.

12. 2011, rains in the mountainous region of Rio de Janeiro: landslides and floods destroyed houses in hillside regions; 916 deaths, 350 missing, 300 thousand people directly affected; estimated economic losses: R$ 4.8 billion; estimated insured value: R$ 92 million.

13. 2015, fire at the Alemoa Terminal, in Santos (SP): Ultracargo Company; discharge of liquid and gaseous effluents; fine of R$ 22.5 million by the government environmental agency. “There is published information that the company has an insurance policy whose limit reaches US$ 550 million, in addition to a Civil Liability policy. We estimate that the extent of the economic damage may have reached about twice the insured amount, that is, around US$ 1.1 billion “(Terra Brasis, 2016).


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14. Dam rupture in Mariana - MG (05 / Nov / 2015):

◦ • Release of 62 million m³ of sludge with tailings

◦ • 19 deaths, 1,265 homeless

◦ • Paralysis of many economic activities, including mining company’s

◦ • EMATER-MG: farmers lost R$ 23 million

◦ • Self-employed workers, among them at least 1,249 fishermen, depended on the water of the Rio Doce

◦ • Paralysis in milk production, losses in the order of 21,000 liters per day

◦ • Candonga, Baguari, Aimorés and Mascarenhas hydroelectric plants had their activities interrupted

◦ • Increase in unemployment

◦ • Reduction of tax collection due to the paralysis of mining activities

◦ • It is estimated that 3.5 million people were affected by lack of water

◦ • Vale, a shareholder of Samarco, estimated a reduction of US$ 443 million over its results for the year 2016

◦ Actions in Justice:

indemnification of R$ 20.2 billion requested to Samarco, with possible liability of Vale and BHP,

repair of environmental damage over a period of 10 years,

class action lawsuit filed by an American law firm against Vale to guarantee compensation to shareholders for company omission on damages related to its relationship with Samarco and suspension of Samarco’s activities.

• Preliminary IBAMA fines of R$ 250 million.

• Company will bear all the individual and collective indemnification costs and the environmental recovery of the impacted area.

• Signed a Term of Adjustment of Conduct with the MP-MG14, for which it must maintain a fund in the amount of R$ 1 billion fully allocated to the recovery of the Rio Doce river.

14 Minas Gerais State's Government agency for law enforcement and prosecution of crimes.


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• 20/10/2016 - The MP-MG denounced 22 people and the companies Samarco, Vale, BHP Billiton and VogBR.

21 people are charged with homicide of the first degree with eventual dole (when one assumes the risk of killing).

will also be responsible for flood, collapse, personal injury and environmental crimes

Includes Samarco’s chief-executives, managers, and members of the board of directors


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The classic economic model of the insurance market predicts that, provided certain assumptions are met, market competition leads to an efficient allocation of risks in the economy. Diversifiable risks can be eliminated through the conclusion of risk-sharing contracts. Residual risks, on the other hand, are allocated to agents with greater risk tolerance, such as insurance companies and high-income investors. In sum, the theory predicts that all risks are insurable and that the insurance market will do so efficiently, maximizing social welfare.

A rapid analysis of the environmental risk segment contradicts the predictions of the model. There is ample evidence of low take-up rates of environmental insurance products. On the supply side, insurance companies are reluctant to offer coverage for catastrophic risks. Several examples may illustrate the inefficiency of risk sharing in the segment.

What are the reasons why agents make limited use of environmental insurance? Why environmental insurance, when offered, have such high premiums? What measures can be taken to correct inefficiencies and expand this market? There are several studies addressing these issues (Kunreuther, Hogarth and Meszaros, 1993, Kunreuther, 1996, Freeman and Kunreuther, 1997, Richardson, 2002 and Gollier, 2005). This chapter aims to synthesize the main findings of this literature.

There is no single explanation for the limited use of environmental insurance. Several market failures contribute to this under-provision of coverage and the high value of premiums. All failures are associated with violations of the hypotheses underlying the classic economic model of risk allocation. On the other hand, correction measures are directly associated with interventions aimed at correcting these market failures.

ENvIRoNMENtAl INSuRANCE: MICRoECoNoMIC ASpECtS

1. Introduction

ChAptER 2


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The chapter is divided into four sections. After this introduction, the second section briefly presents the classic model of risk allocation in competitive insurance markets, highlighting its basic results and assumptions that ensure its validity. The third section identifies the market failures present in the environmental risk segment and discusses their implications. Finally, the fourth and last section presents some policy recommendations that can reduce inefficiencies and expand the environmental insurance market.

It should be noted that this chapter focuses on the supply side. Demand-related issues are also relevant to understanding the limited use of these markets. The demand for insurance will be analyzed in the next stage of the research.

The classic model of risk sharing in insurance markets was developed by the pioneering contributions of Kenneth Arrow and Karl Borch (Arrow, 1953; Borch, 1962). Basically, the model predicts that, given certain assumptions, market competition leads to an efficient allocation of risks in the economy, maximizing social welfare.

The assumptions required for efficient risk allocation are listed below:

(i) Absence of transaction costs.

(ii) The probability of the risk is known to all the agents, as well as the value of potential losses.

(iii) The distribution of risk probability may be affected by agents’ prevention efforts. These efforts can be perfectly monitored at zero cost.

(iv) Agents are solvents in any contingency. That is, agents have the necessary financial resources to make payments in any market contingency.

(v) There are future markets for all contingencies.

If these assumptions are met, market negotiations that are advantageous to both sides of the transaction - buyers and sellers – lead to an efficient allocation of risks. In other words, competitive equilibrium leads to an efficient sharing of risks. Economic agents are fully insured in the case of diversifiable risks, thus eliminating this type of risk. Residual risks are transferred via market transactions to agents with greater risk tolerance, such as insurance companies and high-income investors. As

2. Allocation of risks: the classic Arrow-Borch model


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risks are either eliminated or transferred to agents who charge the lowest premium to retain them, competitive equilibrium leads to minimization of the total risk retention cost. In addition, agents have incentives to invest in the socially optimal level of prevention. In sum, the theory predicts that all risks are insurable and that the insurance market will do so efficiently, maximizing social welfare. In this context, there is no need for public interventions in the insurance market.

Environmental risks have a number of characteristics that violate the hypotheses underlying the canonical risk insurance model. The proba-bility distribution of risks is in most cases unknown or ambiguous, and the losses associated to the risk are difficult to measure. The threat of insolvency of insurance companies, which have limited resources, may make them reluctant to cover catastrophic risks such as natural disasters. Problems of asymmetry of information can lead to the exclusion of the market from consumers with low vulnerability to environmental risks and/or an underinvestment in risk prevention measures.

Each of these characteristics represents a violation of the hypotheses of the classic model. These violations are generally referred to as market failures.

Market failures leads to inefficiency in the functioning of insurance markets. In this section, different market failures in the environmental risk segment are identified and the implications of these failures are dis-cussed.

Knowledge of the distribution of risk probability by economic agents is one of the requirements for the efficient functioning of insurance markets. However, it is possible to identify several contexts where there is uncertainty about this distribution.

This uncertainty may be due to a lack of historical records or gaps in scientific knowledge. How likely is it that the average temperature of the planet will rise by 3° C by the end of the century? The current level of scientific knowledge on climate change does not allow us to clearly establish the probability distribution of possible elevations of the average temperature. What is the correct probability of a nuclear power plant leak due to an earthquake? For most environmental catastrophes, it is necessary to rely on risk assessment studies carried out by meteorologists, climatologists, hydrologists and other specialists. Despite advances in

3. Environmental risks and market failures

3.1 Ambiguity


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the modeling and simulations of environmental disasters, scientific evidence suggests that there is considerable uncertainty and ambiguity in estimating the likelihood of a given environmental disaster occurring in a specific region.

In addition to the uncertainty in the distribution of risk probability, the value of losses resulting from environmental damage is difficult to measure. These values cover not only injury and property damage, but also damage to the environment. There is much uncertainty as to the magnitude of the losses involved in environmental disasters. The lack of consensus around a methodology for assessing environmental damage makes environmental risk pricing an even more complex task15.

There is an extensive literature that investigates decision-making in ambiguous scenarios. In general, results indicate that individuals present aversion to ambiguity (Heath and Tversky, 1991). In the case of the insurance industry, this aversion manifests itself in the positive relationship between uncertainties about risks and/or losses with premiums: the greater the uncertainty about the likelihood of a loss and its potential magnitude, the higher the premium charged by insurance (Box 1).

Consider a manager of an insurance company that needs to set premiums for two risks, both with a known loss of L = - 1,000. Risk 1 has a loss probability of p = 0.2. For Risk 2, there are two distinct expert opinions about the loss probability. Expert A estimates this probability at pα◦ = 0.1, while the expert B attributes to this risk a probability pβ = 0.3. The manager assigns the same weight to the experts’ opinion (that is, wi = 0.5, i = ◦α, β◦), in such a way that his estimate of the ambiguous probability is given by Ap = (0.5). , 1) + (0.5). (0.3) = 0.2.

Figure 1 shows the tree diagram representing the two risks. It is said that the manager presents aversion to ambiguity if the premium charged for risk 2 is greater than the premium for risk 1, even though he knows that p = Ap.

Box 1: Aversion to ambiguity

15 The issue of environmental damages assessment is elaborated with in detail in section 3.5.


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Figure 1: two risks with known loss of l = - 1,000

Empirical studies show that risk underwriters are extremely ambiguity-averse and tend to set fairly high premiums when compared to situations where risks are well defined. A field study of 896 underwriters from 190 American insurance companies sought to assess the effect of ambiguity aversion on insurance premiums (Kunreuther, Hogarth and Meszaros, 1993). Underwriters were asked to determine the premium for insuring a factory against property damage due to a severe earthquake. Different scenarios were constructed to analyze how underwriters reacted to the ambiguity of risks and value of losses.

In the construction of the scenarios, the probability is considered to be well-specified (p) when there is enough historical data and/or scientific information to establish a consensus about this probability. In cases with uncertainty about the earthquake risk, ambiguity about the probability of loss is called Ap. In relation to the value of the loss, it is represented by L when there is consensus about the magnitude of the losses. Uncertainty in the magnitude of the losses is represented by UL and, in this case, loss estimates are considered to vary within a range defined by Lmin and Lmax.

Four possible combinations were considered in relation to the ambiguity of probability and the uncertainty of the value of losses: (p, L) = well-specified probability and known loss value; (Ap, L) = ambiguous earthquake probability and known loss value; (P, UL) = well-specified probability and uncertain loss value; and (Ap, UL) = ambiguous probability and uncertain loss value. As Table 1 shows, the four categories provide

Risk 1 Risk 2

Source: adapted from Kunreuther, Hogarth and Meszaros, 1993.


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a good taxonomy for the classification of insurance products. The (p, L) case refers to situations where the value of losses can be well determined and there is enough historical data or scientific evidence to correctly specify the probability of the risk. This category includes, for example, car and life insurance. Other events, such as accidents in leisure areas, can be classified in the (p, UL) category: the probability of occurrence is well known, but the loss value, uncertain. Risks associated with new technologies (for example, launching satellites) or launching new products can be classified in the (Ap, L) category: there are uncertainties about the risk of failure, but economic losses are well known. Finally, the (Ap, UL) category covers catastrophic risks. Most of the environmental risks are classified in this last category.

Table 2 presents the behavior of underwriters in the calculation of the premium for the different cases. When the risk is well specified, situations where p = 0.01 and p = 0.005 were considered; the loss, if the earthquake does occur, was estimated at USD 1 million or USD 10 million. For comparison purposes, the premium for the unambiguous case (p, L) was used as a benchmark and normalized to 1. Thus, the entries in the table represent the ratio between the premium of the cases with ambiguity and the reference case (p , L).

For the case with greater ambiguity (Ap, UL), the calculated premiums were between 43% and 77% higher than the scenario with no ambiguity. The other scenarios with ambiguity also presented ratios higher than 1. Thus, the study confirms the positive relationship between uncertainties about risks and/or losses with the value of the premiums. It should also be noted that a considerable number of the underwriters commented that they would prefer not to offer insurance in situations with a high degree of ambiguity and uncertainty.

Table 1:Risk classification

PROBABIlITylOss vAluE

KnOwn unKnOwn

Well specified p,LCars, Life

p,ULAccidents in leisure areas

Ambiguous Ap,LNew technologies, new products

Ap,ULEnvironmental disasters, terrorism

Source: Kunreuther, 1996 (adapted).


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In practice, in the presence of ambiguity, many underwriters adopt a “safety-first” restriction criterion when calculating premiums. This criterion represents an effort to adopt a simple pricing rule. It establishes a level of probability p* which represents a maximum likelihood of insolvency that the insurer would tolerate. When deciding whether to add a new risk to the portfolio, the insurer will set a premium in such a way that the new portfolio has a probability of insolvency less than p*. By adopting this insolvency restriction, it can be shown that the insurer establishes premiums above the values it would adopt if it did not explicitly use the p* probability as reference (Roy, 1952; Berger and Kunreuther, 1991).

Finally, the results analyzed here suggest that the high degree of ambiguity of environmental risks can result in very high premiums and a reduced supply in the insurance market.

The allocation of environmental risks through the insurance market may also have its efficiency impaired by information asymmetry issues. Insurance claimants are better informed than insurers. This informational advantage results in potential inefficiencies associated with adverse selection and moral hazard problems.

3.2 Asymmetry of information

Table 2:Ratio of insurance premiums for ambiguous risk/loss in relation

o well-specified risk premiums

PARAMETERsCAsEs

p,l Ap,l p,ul Ap,ul

p =0.005L = USD 1 million

1 1.28 1.19 1.77

P=0.005L = USD 10 million

1 1.31 1.29 1.59

p =0.01L = USD 1 million

1 1.19 1.21 1.50

P=0.01L = USD 10 million

1 1.38 1.15 1.43

Source: Kunreuther, 1996.


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Adverse selection

In general, individual risks are heterogeneous: different individuals have different degrees of risk. The problem of adverse selection arises from the fact that insurance claimants, in most cases, have more information about their specific risk profile when compared to insurance companies. The latter need to incur large costs to distinguish the type of risk from potential insured profiles. If the insurer cannot distinguish the different risk profiles and defines the insurance premium based on the average probability of loss occurring in the population, the insurance contract tends to attract the most risky agents. In the extreme case, only high-risk agents will buy insurance.

For purposes of illustration, suppose that the residences of a given region can be divided into two groups. The first group has a low probability of being harmed (low risk group), while the second group has a higher probability (high-risk group). The probability of harm to the low risk profile is of 10%, while for the high-risk group this probability is of 30%. The two groups are considered to be the same size (i.e., have the same number of residences) and that the value of loss in case of casualty is the same for the two groups. The value of loss is calculated at $100.

Since both groups have the same size, the expected loss of a randomly selected residence is $20. If the insurer covers this average value of the entire population, probably only the high risk group would be interested in the contract. The expected loss for the high-risk group is of (.30) x $100 = $30, which would therefore be willing to pay $20 for insurance. On the other hand, residents in the low risk group, who have an expected loss of (0.10) x $100 = $10, would demand insurance at a $20 price only if they were extremely risk averse.

In case there is demand only from the high-risk group, the insurer would have an expected loss of $10 in each sold policy. Anticipating this result, the insurer may be led to focus exclusively on the high-risk group, increasing the value of the premium so as to have a positive return by attending this group. Thus, the existence of the high-risk group creates a negative externality over low risk individuals in a way that the low risk group is unable to demand an insurance contract at a value that is in accordance with their willingness to pay.

One possible way to reduce problems of adverse selection would be by offering specific contracts for each group (Rothschild and Stiglitz, 1976). The contracts would have different premiums and levels of coverage. A contract with high premium and high level of coverage would be destined to individuals with high environmental risk. For the low risk group, a contract with a lower premium and a lower degree


36

of coverage would be proposed. Provided the premium and coverage values are adequately defined for each contract, individuals would have the incentive to select the proposed contract for their type themselves. In this way, the two groups could be served by the market while the insurer would achieve a positive return16.

However, a policy of price/coverage discrimination according to the degree of risk exposure of potential insured people may raise questions about their distributional impacts. In many cases, individuals with greater exposure to environmental risks are also those with lower income. In Brazil, for example, the majority of households located in areas at risk of natural disasters belong to low income families. In view of the degree of risk of low-income people, the higher priced contract would be offered to individuals of lower ability to pay.

To avoid these potential negative distributional impacts, some countries prohibit price discrimination by risk profile for certain types of insurance. On the other hand, the potential problem of adverse selection resulting from this policy of non-discrimination can be solved by making the acquisition of insurance compulsory. This is the case in France, which made insurance against natural disasters mandatory.

Moral hazard

The heterogeneity of risks may be due not only to the different intrinsic risk profiles, but also because agents do not invest the same amount of resources in risk prevention. In particular, a well-established result in the theoretical and empirical literature is the presence of moral hazard in the insurance market: individuals who are covered by insurance tend to invest less in risk prevention or make riskier decisions if the insurance premium is not associated with the adoption of preventive measures.

The existence of moral hazard stems from the inability of the insurer to observe the risk prevention actions adopted by policyholders. Because of this information asymmetry, the level of risk prevention adopted by those who are insured is below the efficient level and a negative correlation is established between the level of coverage of the insured person and the level of prevention. The moral hazard problem is particularly critical when the degree of risk greatly depends on the decisions taken by the insured.

16 For example, the insurer could offer two contracts: contract 1 at the price of $30 and with coverage of $100; contract 2 at the price of $10 and coverage of $40. If the high-risk group prefers contract 1 to contract 2, and the low risk group prefers contract 2 to contract 1, both types of individuals may be served by the market and the insurer will not incur losses.


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Recent works have evaluated the relationship between public agricultural insurance policies and moral hazard. Governmental programs of agricultural insurance against climate risks have as main objective to protect rural producers from negative impacts due to extreme climatic events such as prolonged droughts. These programs are widely used in the United States and other developing countries (Smith and Goodwin, 2010). However, these policies may distort producers’ decisions regarding risk prevention. Empirical evidence suggests that the United States government’s agricultural insurance program generates moral hazard problems (Justin, Calvin and Quiggin, 1999, Goodwin and Smith 2003, Annan and Schlenker, 2015). Box 2 presents a study that seeks to verify the existence of moral hazard due to the agricultural insurance policy in the Corn Belt region of the United States.

Box 2: Case study - agricultural insurance and moral

hazard in the north American Corn Belt

In the US states located in the western region of the Corn Belt, precipitation conditions are generally adequate for planting this crop without the need for irrigation. However, corn is particularly vulnerable to water stress when compared to other products usually planted in the region, such as soybean and alfalfa. Thus, in periods of drought, farmers in the region substitute corn for other crops (Anderson et al, 2012). This pattern of adaptation to climatic shocks presented changes from 2008 on, when changes occurred in the North American agricultural insurance policy.

The US federal agricultural insurance program was established in 1938. The program was intended to provide insurance at subsidized prices against climate risks, and has been modified over time to make it more accessible to producers. Despite the gradual increase in participation rates, a significant portion of rural producers still did not have coverage. As a result, in years of adverse weather, the government was forced to spend large amounts on compensation assistance programs for crop failure. Between 1987 and 2007, there were thirty-nine governmental decrees establishing this type of compensation (Chite, 2010).

Policymakers see the use of agricultural insurance as a cheaper alternative to costly ad hoc financial compensation policies for crop failure. Thus, in an attempt to reduce ad hoc expenditures on emergency programs, the government introduced the Supplemental Revenue Assistance Program (SURE) in 2008. SURE basically extended agricultural insurance coverage by compensating producers for a portion of production that was not covered by the conventional agricultural insurance program. The standard federal agricultural insurance covered a portion of 75% to 85% of the expected output. In practice, the combination of the SURE program with standard federal insurance enabled 100% coverage of the production of farmers affected by climatic disasters.


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By abolishing the coverage limit for potential losses from climate disasters, the SURE program introduced a moral hazard problem. Fully covered farmers were not provided with incentives to invest in risk-prevention measures. In particular, corn farmers stopped substituting corn for less hydro intensive crops during periods of drought.

Figure 1 shows the evolution of corn area in North Dakota in the 2000-2011 period. It can be observed that, as of 2007, the planted area of maize has a significant increase in relation to the period 2000-2006. Econometric studies also show that the introduction of SURE reduced the replacement of maize areas by other crops during periods of water stress, even taking into account other determinants, such as the price of agricultural commodities (Huang, 2016).

Figure 1:Area with Corn plantation in North dakota in the 2000-2011 period (in acres)

data: United States Department of Agriculture.

There are several ways to minimize moral hazard problems. One possibility is conditioning insurance concession to the adoption of risk prevention measures. This is the case, for example, of environmental risks associated with the maritime transport of chemicals: cargo insurance is subject to compliance with all requirements imposed by regulatory authorities.

A second way would be to make policyholders partially liable for the losses resulting from their behavior. For example, deductibles can generate incentives for policyholders to take preventive action, as they will be required to internalize part of the costs incurred in the event of casualties. Alternatively, insurers may mitigate moral hazard problems by reducing the premium of agents who take preventive measures or have a history of low-risk behavior. The granting of bonuses for good


39


behavior and the application of punishments for risky conduct is common in the various branches of insurance, and are widely applied in the case of environmental risks.

Another way to stimulate risk prevention behaviors is to set limits on the amount of coverage that an individual or a company can acquire. If the insurer only covers a maximum of $500 for an asset worth $1000, the policyholder knows that they will have to bear any cost that exceeds the coverage limit.

Compulsory environmental insurance, index-based insurance and information asymmetry

As already discussed, a possible solution to problems of adverse selection would be the offer of contracts destined to different risk profiles. However, often non-discrimination regulatory rules prohibit the application of this segregation mechanism. At other times, even if segregation by risk groups is allowed, in practice it cannot be implemented: under certain market conditions, it is not possible to define premium/ coverage parameters that encourage agents to select the contract for their risk group themselves. In view of these difficulties, some analysts advocate the adoption of compulsory insurance as a solution to problems of information asymmetry.

Making insurance compulsory by all agents minimizes the problem of adverse selection. Compulsory insurance may also reduce moral hazard problems: companies considered to be at high risk would be required to take the necessary preventive measures to avoid the threat of business interruption due to absence of an insurance contract. Another advantage associated with compulsory insurance is the reduction of monitoring costs. In general, insurance companies have lower costs to evaluate the environmental performance of companies when compared to investors and other financial institutions.

However, compulsory insurance presents some implementation challenges. Highly vulnerable firms may have their insurance applications rejected. These firms may resort to judicial actions and lobbying activities in order to revert the situation. Transaction costs related to judicial litigation can be extremely high. In addition, insurance can have a high cost, jeopardizing the competitiveness of companies. The economic impact can be particularly critical in small and medium-sized companies, which have less ability to pay. Thus, despite the benefits associated with reducing the problems of information asymmetry, implementation of compulsory insurance may encounter barriers due to its high economic


40

costs and significant transaction costs. Another instrument that has been identified as a possible solution to problems of information asymmetry in the agricultural sector is index-based insurance products.

The logic of index-based insurance is quite attractive. In traditional agricultural insurance, the indemnities are directly related to the individual productivity of the producer who contracted the insurance. Insurance based on indexes, on the other hand, condition payment of indemnities to an independently observed indicator, but correlated with agricultural productivity, such as local precipitation. The implementation of index-based insurance could solve cost and information asymmetry problems that are generally found in the case of traditional agricultural insurance. Insurers would no longer need to monitor hundreds or thousands of farms individually. It would be sufficient to keep track of local rainfall indications. This significant reduction in cost could be passed on to policyholders in the form of reduced premiums, allowing the inclusion of small-scale, low-income producers and contributing to the insurance market expansion. In addition, since indemnities are paid from an index that is independent of the level of individual farmers’ effort, index insurance does not suffer from moral hazard problems faced by traditional insurance contracts: producers with insurance have no incentive to reduce their level of prevention. In addition, since there is no longer need to check individual losses to pay damages, these payments could occur much more quickly. Rain and other climatic variables can be observed almost in real time, which allows disbursements to be made as soon rainfall levels exceed the parameters determined in the contracts.

Despite the advantages associated with the adoption of index-based insurance, these products have been facing difficulties in enlarging their market possibilities. Low take-up rates may be attributed to both supply and demand factors. On the supply side, insurers face difficulties in collecting the necessary data to develop index-based insurance. For example, many regions in developing countries lack rainfall stations and do not have historical rainfall series. However, the main barriers to the expansion of this product seem to be associated with the demand side. Rural producers are credit constrained and/or are reluctant to adopt products with which they are unfamiliar. Supply and demand constraints have limited private sector investment in this type of product as well as the adoption by rural producers (by Janvry and Quitero, 2010).

This discrepancy between the attractiveness of index-based insurance and the low rates of adoption has generated an intense research agenda that seeks to identify the errors and successes of the experiences imple-mented to date, as well as to develop mechanisms that overcome the current supply and demand barriers for the expansion of this market.


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Many countries adopt the polluter-pays principle in their environmental legislation. Companies identified as liable for certain environmental damage are generally required to pay damages to affected parties and also to bear the costs of remediation. The application of this principle aims to make companies internalize all the costs associated with their decisions. However, the payment of indemnities is limited by the financial capacity of the firms. In this way, it is said that the companies have limited liability, since they do not honor the indemnifications whose values exceed their financial capacity.

One result already established in the insurance literature is that limited liability tends to distort the decisions of economic agents. A company with solvency problems can only benefit from making higher risk decisions, since it will not have to bear any losses. One possible implication of limited liability is that companies will have incentives to buy insufficient insurance coverage against potential environmental damage, or to invest less in environmental risk prevention. This poses a moral hazard problem: the incentive of companies to buy insurance declines as the value of environmental liabilities exceeds the value of their assets (Schwartz, 1985).

Limited liability raises a number of issues. How to guarantee the payment of compensation to those affected by the environmental externalities resulting from the action of companies with limited financial resources? How to build mechanisms that actually encourage companies to invest in risk prevention? How to prevent companies from under-capitalizing their subsidiaries involved in activities of greater environmental risk?

Two answers have been given to this problem. The first is compulsory insurance. The obligation to purchase insurance solves the problem of poor risk allocation, and also allows for organization of a system that effectively guarantees compensation payments to affected parties. However, in most cases, mandatory insurance premiums are set without discriminating by degree of risk. Premiums are often set with low values, since policyholders themselves claim that these can have a high impact on their budgets. Moreover, due to the high costs of monitoring or the lack of incentive from insurers to do so, investments of the policyholders in risk prevention are not observed by the insurers responsible for the management of the compulsory contracts. The combination of these factors results in moral hazard problems, with policyholders investing below the efficient level in environmental control.

3.3 limited liability


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The second option to the problem of limited liability has been to extend liability for damages to other agents with ability to pay. The search for deep pockets, that can pay compensations for the externalities generated by an insolvent company, is the basic proposal of the North-American Comprehensive Environmental Response, Compensation and Liability Act (CERCLA). This law extended liability for environmental damages to the banks that finance companies that generated damages. The CERCLA case is discussed in detail in Box 3.

Since the mid-1980s, many North-American court rulings have shifted responsibility for environmental damage to the banking sector. Such decisions are supported by the Comprehensive Environmental Response, Compensation and Liability Act (CERCLA), a law issued in 1980.

CERCLA allows plaintiffs to file lawsuits against “owners” and “operators” of companies responsible for environmental accidents. Commercial banks that have a close relationship with companies – and, therefore, ability to monitor and influence their decisions - are considered as “operators”. In this way, banks can be held liable for environmental damage caused by companies. The aim of the legislator in designing CERCLA was to avoid problems arising from limited liability by allowing courts to find a party who can pay compensation for environmental damage when the company is insolvent. The law also avoids that, in the event of the bankruptcy of the company responsible for environmental damage, the costs of environmental compensation do not fall on public safes.

CERCLA also incorporates an incentive component in forcing risk takers to internalize the total costs of potential damages. This internalization of costs is carried out through financial institutions: banks will raise the cost of lending to companies with a high-risk profile. In addition, because of the possibility of being held accountable for environmental damage, banks are encouraged to monitor the environmental risk of companies in their loan portfolio.

However, there is no reason to believe that monitoring by banks is a simple or low-cost activity. In this way, CERCLA can introduce an additional component of information asymmetry in the credit market. The result of this new component of information asymmetry may be the increase in the cost of capital and the rationing of credit. Thus, in assessing CERCLA, the benefits in terms of reducing the problems associated with limited liability should be contrasted with the potential inefficiencies introduced in the credit market.

It should also be noted that the concept of liability of “owners” and “operators” is a complex subject both in theoretical and practical terms. There is no consensus in the jurisprudence on the liability of parties who have had an indirect connection with environmental damage. There are both favorable and unfavorable decisions to bank accountability in cases of damages associated with insolvent companies (Boyer and Laffont, 1995). This legal uncertainty over CERCLA results in costly litigation.

Box 3: Case study – CERClA


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The solvency of insurance firms is a necessary condition for the insur-ance market to be able to efficiently allocate environmental risks. Insur-ers need to have the necessary resources to handle disbursements in the event of an environmental accident.

The risks associated with natural disasters such as earthquakes and floods are strongly correlated. Simultaneous occurrence of several casualties arising from a natural disaster can cause severe financial impacts and even the insolvency of insurers. In addition to the high correlation, the losses resulting from natural disasters can reach extremely high values. Table 3 shows that nine of the ten largest losses covered by insurance recorded in the period of 1970 to 2014 are associated with natural disasters.

3.4 Solvency of insurers

Table 3:10 largest losses covered by insurance in the period 1970-2014

DATE EvEnT lOCAl

vAluE OF lOssEs COvERED By

InsuRAnCE (usD BIllIOns)

27 July 2011 Flood Thailand 15,783

2 September 2004 Hurricane Ivan United States, Caribbean 16,157

22 February 2011 Earthquake New Zealand 16,836

6 September 2008 Hurricane Ike United States, Gulf of Mexico 22,258

17 January 1994 Earthquake Northridge United States 22,355

11 September 2001 World Trade Center Attack United States 25,104

23 Augusto 1992 Hurricane Andrew United States 26,990

24 October 2012 Hurricane Sandy United States 36,079

11 March 2011 Tsunami Japan 36,828

25 August 2005 Hurricane Katrina United States, Gulf of Mexico 78,638

Source: Insurance Information Institute


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Although regulatory rules determine minimum capital requirements, insurance companies are not immune to the risk of insolvency. Nine insurance companies became insolvent as a result of losses associated with Hurricane Andrew, forcing the industry to use the guaranteed fund to honor the contracts of these companies. Simulations also show that, should the San Francisco earthquake of 1906 occur again in the current period, more than half of the small insurers that provide earthquake insurance in California would be insolvent. Moreover, all large companies would have to raise new capital, since they would not be able to meet regulatory requirements after payment of their obligations (Kunreuther, 1996).

It is said that insurers are reluctant to offer products associated with catastrophic risks because of the limited financial resources to address these risks. This argument ignores the reinsurance industry, which could share catastrophic risks at the global level. After all, even in the scenario where the “Big One” earthquake occurs in downtown San Francisco, the estimated losses would be in the order of 100 billion dollars. This means a loss of US $ 400 per inhabitant in the United States if the risk were perfectly diversified at the national level. International diversification could further diminish these values.

A more convincing argument would be the transaction costs faced by the reinsurance industry. These costs would limit the efficiency of the reinsurance business and, thus, the possibility of sharing risk in the insurance markets. The nature of these transaction costs is still unclear and is the subject of research among insurance economists (Gollier, 2005).

Recognizing the financial constraints on retention of catastrophe risks by insurance and reinsurance companies through its own resources, financial engineers have been developing new products such as climate derivatives and catastrophe bonds (also known as cat bonds). This process of “securitization” through capital markets allows the insurance industry to share the catastrophic risks with investors.

One of the main instruments of catastrophe risk securitization is cat bonds. Catastrophic bonds typically specify that, if the issuer of the bond is struck by a catastrophe (such as a hurricane or earthquake) over a given time horizon, the invested money is used to pay the damages. If there are no catastrophes in the period, the investor receives the main value plus the interest agreed in the contract. These assets emerged in the mid-1990s as a response to losses from Hurricane Andrew’s passage through states in the southern United States. Cat bonds are gaining market share, as shown in Figure 2.


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Although promising, the initiative to use capital markets as a means of expanding the capacity to provide coverage for catastrophic risks still lacks scale. The total value of cat bonds in circulation is modest, as well as the value of other insurance-related derivatives.

Due to the need to cover catastrophic risks and avoid the high costs from insolvency of companies in the sector, the public sector plays a relevant role as “reinsurer of last resort”. The so-called “excess of loss contracts” (or XOL contracts) are a government initiative that seeks to complement the work of reinsurers and the capital market in the provision of funds for catastrophic risks. These contracts would cover insurance industry losses resulting from disasters with excessively high loss values, in the range of US$25- 50 billion. This range is not currently served by bonds traded on capital markets (Lewis and Murdoch, 1996).

The role of the government as a reinsurer of last resort is an essential element in enabling insurance against natural disasters in France or insurance against terrorist acts in the United States (Box 4).

Figure 2 total value of cat bonds in circulation in 2005 - 2015

(uSd billions)

Source: Swiss Re.

Prior to the September 11 attacks, the insurance industry did not charge a specific premium for terrorist acts, nor did it explicitly exclude these acts from contract coverage. This situation changed dramatically after the attack on the towers of the World Trade Center.

Most of the value of economic costs fell on reinsurers. Unable to model the risk associated with terrorist attacks and consequently to price it, reinsurers withdrew from the market for

Box 4: Case study – september 11, 2001 and theTerrorism Risk Insurance Act


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Another necessary condition for the good functioning of the insurance market is that losses can be well measured. However, assessment of environmental damage involves components whose monetization is practically unfeasible with the degree of current scientific knowledge. And without a monetary counterpart, the insurance industry is unable to compensate for any eventual damage suffered.

Initially, the discussion on compensation for environmental damage was restricted to its impacts on property and people. The natural environment was traditionally seen as a public good, whose responsibility for the damage was collective, not of the individual agent’s. With the growth of the environmental movement and society’s greater concern with the environmental issue, we began to discuss responsibility for the damage caused directly to nature.

While damages to economic activities and property can be relatively straightforward to calculate, the same cannot be said of the damage to ecosystem services. In the event of an oil spill on shorelines, it is possible to calculate the economic losses associated with the fishing industry or tourist activities. But how does one calculate the potential damage attached to biodiversity loss? Similarly, how to monetize the impacts of illegal deforestation in terms of the loss of ecological functions provided by the forest cover (regularization of the water regime, erosion control,

risks associated with terrorist attacks. Insurance companies were forced to exclude terrorist attacks from the coverage of their contracts.

Several sectors were unable to acquire insurance against terrorist acts. This situation posed a serious threat to real estate and infrastructure companies. Investors and funders required protection for their investments and lack of coverage against terrorist acts could lead to a collapse of investments.

The government responded to this threat by approving the TRIA (Terrorist Risk Insurance Act) in November 2002. This law defined the guidelines for supporting reinsurance in the case of large-scale terrorist attacks. Government support could reach losses of up to USD 100 billion. On the other hand, the government required contracts to cover the risks of attacks.TRIA expired at the end of 2014 but was renewed shortly after the beginning of 2015. The risk of an eventual non-renewal has led several analysts to warn that credit for construction could collapse. The National Football League (NFL) was forced to deny rumors that it would cancel the final of its championship - the famous Super Bowl - because of a possible non-renewal of TRIA.

3.5. Assessment of environmental damage


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etc.)? Environmental economists disagree on the most appropriate way to assess ecological damage. Even the very possibility of monetizing these damages is controversial.

During the discussions on the EU’s environmental liability guidelines (White Paper on Environmental Liability), representatives of the insurance industry expressed their concerns over the difficulties of attributing a precise value to the losses of natural resources. It is important to remember that risk underwriters are averse to the ambiguity of loss values. As this ambiguity is quite present in the calculation of damage to ecosystems, a significant impact on the premiums can be expected. The European industrial sector, on the other hand, questioned the impact on competitiveness as a result of the increase in environmental insurance premiums.

Given the difficulties of measuring and valuing ecological losses, in practice, damages are calculated from the cost of restoring affected ecosystems. This was the methodology adopted in the European Union White Paper. Damage estimation based on remediation costs was also the approach used in the case of the dam accident in the city of Mariana, in Minas Gerais.

However, there is no guarantee that the restoration of the original ecosystem, even if possible, will be able to restore the stock of natural resources and the provision of ecosystem services identical to the period prior to the damage. There are also damages that are irreversible, such as the extinction of species. In view of this, despite avoiding problems associated with the ambiguity of the value of losses, the approach to valuation of remediation costs can be seen as a second best solution to the issue of ecological damage.

In many circumstances, individual risk is correlated in time. For example, a person’s current health conditions influence his health conditions in future periods. On the other hand, places with a history of earthquakes are more likely to suffer further earthquakes in the future.

In a more extreme version of this correlation, we may face the so-called “realized risk”, in which the future evolution of the random variable becomes deterministic in the current situation. In these cases, there is no risk-sharing agreement that is beneficial to policyholders and insurers. Realized risk represents the closing of future markets for contingent risks. This violates one of the assumptions of the efficient functioning of the insurance market. It is not possible to insure a risk that is no longer contingent to acquire an ex-post character.

3.6. dynamic aspects: realized risks


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External information about the degree of risk may produce realized risk situations. In the health sector, genetic testing increasingly tells more accurately about the future evolution of people’s health. Thus, the evolution of health conditions - which before the advent of tests could be considered an ex-ante risk - is deprived of its characteristic of contingent risk and becomes a risk with realized character. If information on genetic testing results is made available to the insurance industry, there is a threat of genetic discrimination: individuals with a pre-disposition for certain diseases could be excluded from the health insurance market. The fact that additional information can bring social welfare losses is known as “Hirshleifer effect”.

The situation described above is an illustration of the so-called Hirshleifer effect, which points to paradoxical situations in which additional information can bring losses of social welfare (Hirschleifer, 1971). One way to deal with the Hirschleifer effect would be to carry out the insurance contract in a period prior to the disclosure of the information. Another possible solution in the case of genetic testing would be to prohibit discrimination on the part of insurers based on test results. In 2008, the US government issued the Genetic Information Nondiscrimination Act. Its purpose was to defend the American citizen from genetic discrimination by health insurers or employers. However, the law does not apply to life insurance, which can use the information on the genetic profile to deny coverage.

It should be emphasized that, despite the strong ethical appeal of the genetic non-discrimination policy, it would introduce a large amount of adverse selection. Demand for insurance would be concentrated on individuals with a high-risk genetic profile (i.e., predisposed to serious illnesses), raising the price of the charged premium and excluding people with a low-risk profile, who would have a low willingness to pay for insurance.

In any case, both discriminatory practice and non-discriminatory policy could potentially exclude groups: while discriminatory practice would leave high-risk individuals out of the market, adverse selection generated by non-discrimination could potentially alienate low-risk individuals of the market. In general, the preference of policy makers has been for the application of the non-discrimination policy.

Similar issues associated with the “Hirschleifer effect” pervades environmental issues. Improvements in earthquake prediction models, bringing more information about the degree of risk of different cities, may imply significant increases in insurance premiums in the most vulnerable cities or even in refusal to offer insurance contracts. Similarly, an international agreement on climate change is more likely to be


49


implemented as long as scientific knowledge does not allow accurate predictions about which countries can benefit from global warming and which ones will suffer the most damage. If scientific advances make the risk no longer contingent, acquiring a realized risk profile, the possibilities of agreement become more difficult.

The discussion above points to the importance of establishing long-term relationships between the parties in the insurance market. Environmental risk insurance would be less valuable if, at any time, one of the parties could renegotiate its terms based on new information on the risk exposure of insured parties.

The environmental insurance segment has a series of failures that hinder the efficient risk allocation by the market. Difficulties in estimating the probability of risk and the value of losses, information asymmetries, transaction costs and insolvency risk of the companies in the sector mean that the premiums charged by the insurance industry are high and that many environmental risks are not covered or have limited coverage. In what follows we provide some recommendations that may lead to a decrease in the value of premiums and the expansion of the market in this segment.

• Enhancement and dissemination of risk assessments areimportant for the expansion of the environmental insurance market

Ambiguity regarding the likelihood of environmental risk and uncertainty about the value of losses are decisive for the high premiums. They also explain the industry’s reluctance to offer insurance for some environmental risks. For many natural disasters, there is a limited information base to calculate premiums accurately.

The wider use of risk assessments can be an effective means of reducing the degree of uncertainty. A better understanding of the nature of the risk can lead to significant reductions in premiums. The case of the North American Earthquake Project illustrates the positive impact of reducing ambiguity. Risk assessments conducted jointly by the insurance industry and the Federal Emergency Management Agency have led to a better understanding of the likelihood of earthquake risk in the United States, which in practice has resulted in reductions of premiums and in an increase of the coverage of this risk (Earthquake Project, 1990).

4. Conclusions and policy recommendations


50

As risk characterization is very sensitive to local conditions, the results of risk assessments are often not generalizable. Regulators and companies operating in the Brazilian insurance market must invest in evaluations with methodologies that are adapted to the country context. A better understanding of local risks will reduce the degree of ambiguity, with consequential drop in premiums and market expansion.

• Capital markets should be used to enable the provision of insurance for catastrophic risks

Catastrophic risks can generate losses of great magnitude, to the point of compromising the solvency of insurance companies. The magnitude of the losses can make companies reluctant to act in this segment. Funds raised through the capital market can be a means of expanding the ability to provide coverage for catastrophic risks. In addition to being an additional resource mechanism, securitization of environmental risks allows these risks to be shared with a large number of investors.

Securitization of environmental risk via climate derivatives, cat bonds and other bonds is not yet carried out on a large scale. The potential demand for these bonds should not be a limitation, since the return of these securities is not correlated with the return of other investments such as fixed income and shares. The purchase of cat bonds would thus be a good strategy of risk diversification.

However, most cat bonds do not reach the investment grade of rating agencies. Rating agencies use catastrophe models to analyze the likelihood of default of these bonds (for example, the likelihood of a disaster involving the non-payment to investors). The models suggest that the probability of default of an individual event is relatively high, which compromises the rating of the bonds. Many agencies have recommended that cat bonds should cover multiple events as a way to reduce the likelihood of default.

The discussion above illustrates one of the difficulties for the securitization of environmental risks. There are also patent pending issues and other regulatory issues that need to be addressed to expand this market. In any case, securitization is a promising strategy and should be encouraged by regulators.

• Government action is important for the consolidation ofthe catastrophic risks market.

The existence of market failures in the environmental risk segment justifies governmental intervention in the sector. In addition to its regulatory function, by establishing rules and regulations that correct


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any eventual inefficiencies in the functioning of the market, more direct government action is necessary in the case of catastrophic risks.

Institutional arrangements in which the government acts as a “reinsurer of last resort” are necessary and effective to expand the catastrophic risk market. An interesting proposal is tripartite risk-sharing arrangements, which include the insured party, the insurance industry and the federal government (Doherty et al., 1990). In a first level of protection is the insured himself, who through a system of payment of deductibles can be encouraged to respond appropriately to mitigate environmental risks. Reducing premiums that are contingent on the adoption of risk prevention measures may be another way of reducing problems of moral hazard on the part of policyholders. The second level of protection would be provided by the insurance industry through the formation of consortia. A consortium of insurance companies could use the amount of their premiums to form a reserve fund to cover specific catastrophic risk. Finally, the third level of protection would be provided by the government as a “reinsurer of last resort”. Government participation would be triggered when the value of the losses exceeded a predetermined limit. From this limit, the liability for loss coverage would pass from the insurance industry to a government agency.

This tripartite model of risk sharing is widely adopted by developed countries, with very satisfactory results in the case of natural disasters. The direct action of the government enables the reduction of the uncertainties of the value of the losses and of the bankruptcy risks of the insurance companies that operate in the sector, thus, providing incentives for these companies to offer risk coverage at more reasonable premiums.

• Innovative products such as index-based insurance arestill scarcely used in Brazil. It is necessary to stimulate its adoption.

The implementation of index-based insurance could solve problems of monitoring costs and information asymmetry that are generally found in the case of traditional agricultural insurance. The significant reduction in monitoring costs could be passed on to policyholders in the form of reduced premiums, allowing the inclusion of small, low-income producers and contributing to the insurance market expansion. In addition, because indemnities are paid from an index that is independent of individual farmers’ level of effort, index insurance does not suffer from moral hazard problems.

Brazil has a good network of meteorological information, so there are no data availability problems for the implementation of this type of product. The main barriers to adoption seem to be determined by the


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demand side. Rural producers have a credit constraint and are reluctant to adopting instruments and relying on institutions with which they are unfamiliar. The spread of index-based insurance will require the support of public policies and product innovation. Some experimental initiatives with microinsurance and the development of collective contracts with cooperatives have been promising.

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Based on the information and the theoretical-conceptual structure presented in the first two chapters, this chapter 3 aims to establish an understanding of the behavioral pattern and business strategies of the national insurance and reinsurance markets with respect to their retention and transfer of large risks strategies, in particular those related to the environment.

The objective is also to discuss factors explaining the existence, in Brazil, of a significant protection gap17 in the coverage of environmental risks - relatively large when compared to international statistics -, which point to the expansion of this gap, at the global level, in the last decades18,19.

In addition to this Introduction, this chapter is composed of five more sections, including the conclusion and the bibliography of this part.

Section 1 presents a summary (a “taxonomy” attempt) of environmental risks - understood as a subset of the so-called large risks generally, non-life risks), in which their essential and differentiating

AlloCAtIoN oF ENvIRoNMENtAl RISKS IN INSuRANCE ANd REINSuR-ANCE: RISK MANAGEMENt, StRAtE-GIES ANd pRotECtIoN GAp IN thE BRAzIlIAN MARKEt

Introduction

ChAptER 3

17 It is also used, in the measurement of the catastrophic risk protection gap, the complement of the coverage index (= 1 - protection gap given by the ratio of insured losses/total losses, used here). In both measures, an increase (decrease) in the gap means the widening (narrowing) of the difference between the total economic losses and the insured losses.

18 http://www.gccapitalideas.com/2016/03/03/insured-versus-uninsured-loss/: “There are a number of factors that contribute to the gap between economic loss and insured loss and as new risks emerge such as climate change and political risk, this gap will only continue to widen. The cost of uninsured events frequently falls on governments through disaster relief, welfare payments or in the form of government bailouts.”

19 The publications dedicated to the specialized coverage of catastrophic risks from Swiss RE (Sigma series, several editions) and Munich RE stand out internationally. At the national level, CNseg (National Confederation of General Insurance Com-panies, Private Pension and Life, Supplementary Health and Capitalization) and SUSEP (Superintendence of Private Insur-ance) studies and database are highlighted.


55


characteristics in relation to other risks (ordinary) are highlighted, and from which some fundamentals for their strategic management will be inferred by the insurance and capital markets20.

In section 2, once the risk is conceptually characterized, we will discuss the international state of the art regarding its measurement: both from the point of view of the extraction and modeling of primary information (catastrophe models and quantification of probabilities and impacts of risk events); and in the feeding – by the models of catastrophe – of pricing and calculation models of capital requirements (expected and unexpected losses) and Risk-Adjusted Return on Capital (RAROC), in the regulatory and economic aspects, as well as in the concepts and measures of risk appetite and tolerance that underlie capital adequacy models.

In section 3, considering both the classification and quantification presented in the first two parts, the market organization structure of the environmental risk allocation will be evaluated, based on the characteristic roles played by the economic agents, at national and international levels, to the subscription and retention of these risks, be it in the closest environment to the insurance economy (such as policyholders, insurers, reinsurers, governmental bodies); or in the context of solutions and products provided by the non-insurance financial market (such as the ones of Insurance-Linked Securities - ILS and Cat Bonds).

The important role played by regulators and rating agencies is also addressed in this section, including the current state of the main regulatory changes under way in Brazil and abroad.

In section 4, always having as a guideline the framework set forth in the previous sections, the international and national trends with respect to the retention and transfer of environmental risks will be respectively presented.

At international level, emphasis is placed on the ongoing process of consolidation of the insurance and reinsurance market at global level and the possible impact (in the light of basic parameters of environmental risk taxonomy) of climate change in the calculation and management of these risks.

At the national level, emphasis is placed on the effects of the recent regulatory changes sponsored by the National Council of Private Insurance (CNSP), as well as the combined effect of these changes and the transformations at the international level on strategies for retention and

20 The main risks considered here are, essentially, the so-called non-life, including those treated in the segmentation of SUSEP as property & casualty, special, and hulls. Other risks are classified as ordinary for the purpose of this chapter.


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transfer of environmental risks by the national insurance and reinsurance market (focusing on the protection gap and the penetration coefficient, as quantification metrics).

An example, based on the event of the city of Mariana (MG), is specially studied in light of this dynamic21.

Finally, the last section presents the conclusions and also makes some recommendations for possible lines of action aiming at reducing the coverage gap and increasing the penetration coefficient in the segment of insurance and reinsurance of environmental risks.

In the technical literature on this subject, it is known, essentially, that the environmental risks, whether man-made or arising from natural disasters22, are in a broader category, known as “large risks”23, which has specific characteristics that differentiate it from the risks commonly dealt with by the insurance and reinsurance markets (risks which will be referred to here as ordinary)24.

Typically, risks ordinarily addressed by the insurance segment are characterized by compliance with the Law of Large Numbers (LLN), the implication of which is the property of diversification, where the risks of concentration (for example, those due to large exposures and/or exposure to correlated events of small value) are diluted (for example,

1. Characterization of Environmental Risks

21 This is the environmental disaster that occurred in the municipality of Mariana, in the State of Minas Gerais, Brazil, on 11/11/2015, which impacted a large geographic area of influence of the Rio Doce Basin, also affecting the municipalities of the State of Espírito Santo, because of the collapse of a mining tailings storage dam (Fundão), owned by the company Samarco, and that, “according to a report by the Brazilian Institute of the Environment and Renewable Natural Resources (IBAMA), would have released about 62 million m³ of mud “(cf. Terra Brasis Reinsurance. Terra Report. Special Edition. Mariana. May 2016).

22 Monti, A. (2002): man-made and natural disasters are also called environmental liability and natural catastrophe risk, re-spectively: “environmental liability (i.e. the financial risk associated with environmental pollution and contamination) and the natural catastrophe risk (i.e. the risk of major damages in connection with the occurrence of natural disasters, such as earthquakes, floods or other extreme environmental conditions). Both these environment-related risks, as mentioned, are characterized by the potential for catastrophic consequence.”

23 Great risk, in this chapter, refers to Patrimonial Risks (thefts, fires, lost profits, engineering risks), Special (nuclear, petro-leum, satellites) and Hulls (maritime and aeronautical), according to the branches classification of SUSEP - Superintendence of Private Insurance, and those included in the definitions herein referred to the environmental risks resulting from human action and to nature events are also included.

24 http://www.gccapitalideas.com/2009/04/17/cat-risk-in-a-solvency-ii-environment/.“[...] Non-life catastrophe (cat) risks are low frequency, high-severity events that are often not captured adequately by the premium and reserve risk charge. Solven-cy II regulation tries to mitigate this effect through the introduction of a cat risk sub-module, which is combined with the premium and reserve risks sub-module to comprise the non-life underwriting risk module. For non-life companies, cat risk contributes substantially to the overall Solvency Capital Requirement (SCR), as currently discussed under Solvency II[…].”


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the application of LLN results in the compensation of losses within an exposure portfolio subject to risks)25,26.

On the other hand, environmental risks have as a characteristic a smaller possibility of diversification, since, in essence, they present constitutive elements of properties typical of the concentration risks27.

Continuing the comparison between environmental risks and the so-called ordinary risks, the latter are also schematically characterized by higher probability of occurrence and less impact when losses materialize (due to greater diversification, via lower exposure values and/or lower

25 In probability theory, the law of large numbers (LLN) is a theorem that describes the result of performing the same exper-iment a large number of times. According to the law, the average of the results obtained from a large number of trials should be close to the expected value, and will tend to become closer as more trials are performed.

26 Monti, A. (2002). “[...]Economic actors have different attitudes towards risks. It depends on several factors, including the nature of the risk, the probability of loss, the potential magnitude of the loss and the ability to absorb its economic con-sequences. Assuming rationality and perfect information, economic actors are able to calculate the actual value of a given risk by discounting the magnitude of the loss by the probability of its occurrence (PxL). Once the risk is properly identified and evaluated, however, risk management decisions still need to be taken. In this perspective, economic actors may be:

- risk averse: if they are willing to pay even more than the actual value of the risk in order to transfer its harmful conse-quences to someone else [...];

- risk preferring: if they prefer to retain the risk of loss, rather than transferring it by paying upfront an amount equal to its actual value.

- risk neutral: if they are indifferent with respect to the alternative between (a) retaining the risk and (b) transferring it to someone else by paying upfront an amount equal to its actual value.

Risk aversion, therefore, generates demand for insurance. Insurance companies, in turn, are willing to undertake the risk in exchange for an amount of money relatively close to its actual value (the premium), because the law of large numbers makes them able to manage such risks effectively, by making predictable, with reasonable accuracy, the claims they will pay from year to year. According to this mathematical law, the larger the number of exposures considered, the more closely the losses reported will match the underlying probability of loss. This means that insurance companies need to pool together a rather large number of homogeneous but independent risks in order to become risk neutral.

The traditional insurance mechanism can be divided into four phases:

- risk assessment (the evaluation of risk, which is usually performed through statistical and probabilistic analyses)

- risk transfer (the shifting of its harmful consequences by way of the insurance contract)

- risk pooling (the placement of the risk in a pool of homogeneous but independent risks allows the insurer to spread the risk and to benefit from the law of large numbers)

- risk allocation (the pricing of the risk though premium setting)

As the magnitude of expected losses increases, the insurers’ financial ability to absorb them can be severely jeopardized. In other words, over and above certain levels of financial exposure, insurers themselves tend to be risk averse. In this context, coinsurance and reinsurance are viable options for primary carriers who are willing to cede part of the risk they undertook, in exchange for the payment of a fraction of the premiums they collected.

Traditional reinsurance agreements may be of different types, among which:

- quota share (proportional) treaties (by which the reinsurer undertakes a quota of the risk transferred to the primary carrier)

- excess of loss (stop loss) treaties (by which the reinsurer undertakes the upper layer of the risk, after a certain attachment point) [...]”

27 Tasche D. (2005): “[...] Sources of concentration risk in credit portfolios: (i) Large single exposures; (ii) Groups of highly correlated small- and medium-sized exposures. Worst case: deterministic dependence, i.e. if one exposures defaults then also all others default (extreme concentration). In practice, dependence will be weaker in most cases. Worst case should be judged most risky, i.e. should require most economic capital... [...]”


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risk correlation), while environmental risks have lower probabilities of incidence, but present a greater impact (severity) in the case of occurrence of casualties (by incidence of higher concentration risk, via higher correlation and/or higher values in exposure to risks)28.

The greater relative impact of environmental risks is associated with greater uncertainty (for example, difficulty in stochastic calculation of ex ante losses, either of their probabilities or of their casualties), greater volatility (variability of probabilities and also the magnitude of losses) and greater correlation between losses.

From a technically stricter point of view, environmental risks typically have a higher coefficient of variation than that the typical one of ordinary risks.

Still in the technical sphere, it can be said that the environmental risks fall within the group of those whose functions of distribution of losses are asymmetrical, presenting fat tails29.

The above-mentioned environmental risk characteristics have direct implications on the way in which the insurance/reinsurance market treats their retention and transfer, which we will explore in section 2.

With the differentiating properties of environmental risks briefly highlighting, it is necessary to ask what the explanatory factors of this differentiation would be in relation to ordinary risks.

A first explanation would be supported by what we will call “informational asymmetries”: environmental risks, especially those resulting from human action, are subject to what is called moral hazard in the Theory of Contracts, which is discussed in Chapter 1, which implies, from the strict point of view of the calculation of risk premiums and of capital requirements by insurance/reinsurance agents, incomplete information (or even absence thereof) for underwriting the risk.

28 Nguyen, T. (2013): “[...] Catastrophic risks are typically characterized by two features. First, many natural catastrophes, from earthquakes to hurricanes, have been shown to be ‘‘fat-tailed’’ [...] ‘‘Fat-tailed’’ loss distribution means that the probability of an event declines slowly relative to its severity. This implies that the premium must be much higher than the expected loss because the insurer has to provide a large amount of capital in case of catastrophic events. The second feature of cat-astrophic risks is that losses are correlated in space. This means that a large number of buildings and other assets in close proximity are simultaneously affected upon the occurrence of the catastrophe. Due to this high correlation between insured risks there is no or too little risk diversification among the insurance pool. Both these features of catastrophic risks (fat tails and spatially correlated losses) make them difficult to insure since they imply a larger risk of insolvency for the insurer deductible [...]”.

29 Asymmetric distributions are, generally, those that deviate from the parameters of the Normal distribution: “A fat-tailed distribution is a probability distribution that has the property, along with the other heavy-tailed distributions that it exhibits large skewness or kurtosis...a fat tail occurs when there is an unexpectedly thick end or “tail” toward the edges of a distri-bution curve, indicating an irregularly high likelihood of catastrophic events”.


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This brings us to the concept of uncertainty, that is, the lack of information for the probabilistic calculation inherent to the risk underwriting activity, resulting in a market failure due to informational asymmetry from this uncertainty.

A second explanation would be the uncertainty (and volatility) associated (both in the risk events associated with human action and in those associated with nature) to the performance of regulatory and legal bodies in the State sphere, be it in the exercise of an “insurance function”, through agencies, funds and state insurers; or in the absorption of losses (in the name of society and taxpayers) after the realization of claims.

The performance of the State as a complementary layer to the market, aiming to supplement its failure to address environmental risks is a striking feature in the absorption and transfer of these risks.

Whether in the ex-ante regulation of incentives (like environmental legislation); or in the provision of insurance solutions by the public power; or in the arbitration and reparation of ex post losses to casualties events, an asymmetric and inefficient action of the State (or failure of government) can aggregate additional elements of uncertainty to the calculation of insurance/reinsurance, exponentiating market failure, when signaling and encouraging opportunistic behavior and arbitration of economic agents30.

Such an inefficient allocation of risks can be exemplified in the public offer of insurance products with risk-adjusted pricing; and also, ex post materialization of losses, in the absorption, by society, of losses not covered by insurance products31.

30 Monti, A. (2002): “[...] At present, however, it can be empirically observed that environmental insurance is not widespread at all. Gradual pollution coverage is still perceived as too costly by the industry and most firms do not decide to insure against these environmental risks spontaneously. The cost of environmental insurance policies is affected by the complexity of the new techniques outlined, by the factual features of the risk itself and by the level of legal uncertainty. An explana-tion of the difficulties experienced by most insurers in marketing Environmental liability policies (EIL) and other environ-mental coverages can be found in the fact that gradual pollution risk is a so-called low probability/high consequences risk and, generally, such risks are not rationally faced by economic actors: they can be easily underestimated or even ignored. Moreover, even from a pure rational choice theory point of view, the limited liability structure of corporations introduces significant distortions in the picture, altering the correct incentives mechanism. Given the magnitude of losses in the envi-ronmental field, in fact, it will often be the case that the amount of potential ecological damage is much greater than the measure of potential liability of the polluter. [...]”

31 Nguyen, T. (2013): “[...] By design [...] insurance schemes in the US and in France subsidise property insurance in high risk areas and crowd out private insurance participation. The main purpose of these state programs is to provide affordable property insurance coverage for citizens. Therefore, the required premiums are in general too low and not risk-adequate. This fact leads false allocations of risks in society because policyholders do not take fully account of the risks. The Govern-ment Accountability Office (GAO), an auditing unit of the US federal government, highlighted this inefficient risk alloca-tion in a recent report to the US Congress on state natural catastrophe insurance programs. The GAO recommended not providing federal support for these programs unless they charge risk-adequate premiums. In the report’s main findings: “most state programs in our review had grown since 2005, and […] most … charged rates that do not fully reflect risk of loss, potentially discouraging private market involvement and mitigation…while [federal natural catastrophe] proposals could lower premium rates for and increase public participation in state natural catastrophe programs, they could discour


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In the case of environmental risks associated with nature events, our understanding is that the weight of informational asymmetries has been significantly reduced in the last decades due to advances in quantitative information extraction and treatment techniques, which implied in a gradual change of subjective assessments towards robust predictive models of disaster risk, which we will address in more detail in section 3.

The role of incomplete ex ante state regulation, however, contributes with a concentration risk component that exponentiates capital requirements required to underwrite environmental risks, thus fitting them into the typology of large risks.

Therefore, we have the lowest probability, greater uncertainty/volatility (together, generating greater “ambiguity”, which we consider correspond to a higher coefficient of variation), together with a higher concentration risk (via correlation and/or big values of exposures), are essentially at the root of the differentiation of environmental risks in particular (and of large risks in general) relative to the ordinary risks of insurance/reinsurance.

The reader should be asking whether such intrinsic characteristics to environmental risks would not differentiate them from the risks most commonly covered by the insurance/reinsurance market to the point where it would imply the necessary manifestation of a market failure.

The answer to this question is, in essence, a positive one: let us report to the properties that define the risks addressed by the insurance market.

In fact, the ability of a risk to be insured (insurability) and of an agent subject to risk and without tolerance to retain it (by transferring it via insurance to a third party), bear the costs (premium) of that insurance (affordability), when dealing with risks with the characteristics of environmental risks (low diversification/low independence, high correlation, non-fractional exposures and high values, and informational

age private market participation and mitigation efforts and increase taxpayer exposure to potential costs. In particular, a federal guarantee of state bonds could give state programs access to capital at reduced or below-market costs, allowing state programs to continue to charge premium rates that do not fully reflect risks or even to lower their premium rates. Furthermore, it could result in decreased reinsurance purchases by some state programs and increased reliance on post-event funding, which could increase taxpayers’ exposure to the potential costs in the event of state financial difficulties. In addition, a federal reinsurance program could reduce costs for state programs, but unless the federal program charged premiums that fully reflect the risk of loss, it could inadvertently encourage further development and population growth in areas with high natural catastrophe risk.[...]. ”The central problem of any government participation in insurance solutions is that governments are in general not able or willing to charge risk-adequate premiums. This results in crowding out private insurance participation and discouraging mitigation efforts [...].


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and legal/regulatory asymmetries), are properties that significantly violate those that characterize insurable risks in ordinary branches32.

The commitment, in the case of environmental risks, of the properties of affordability and insurability characterizing the ordinary branches of insurance entails, as a consequence, the exponentiation, in the solvency equation of the private insurance/reinsurance market, of a dominance of capital requirements in relation to the calculation of risk premiums, which leads to the manifestation of a market failure associated with the coverage of these risks33.

That is, it can be said that environmental risks, on account of their greater “capital intensity” in relation to ordinary branches, due to the violation, as discussed above, of the basic properties to cover these risks in the market, demand, in order to reduce the market failure (protection gap), the incorporation of a non-(re)insurance coverage layer in order to absorb such risks.

The coverage gap is fulfilled, in terms of international experience, through capacity sources within the noninsurance financial market (for example, in the capital market, of securities backed by environmental risks such as ILS and Cat Bonds); or through the provision of insurance by public funds.

For the portion of the coverage gap not addressed by the insurance and also noninsurance financial market, there remains the partial or total absorption by government bodies (that is, throughout society, including, therefore, even those not directly affected by a given environmental disaster), of the losses incurred when environmental risks materialize.

The coverage gap of environmental risks (measured by the ratio between insured losses and total economic losses), according to international statistics, has averaged 32% globally in the last 10 years (up to 2015) 34.

32 The allocation of risks between economic agents who are averse to them and agents who tolerate them involves some classic trade-offs. One of the best-known concerns deductibles (a common risk mitigation strategy for insurance providers), which relate to the portion of residual risk retained (not transferred), by agents with risk aversion, to insurers. If, on the one hand, the deductibles aim to address moral hazard (and the incidence of casualties) related to opportunistic behavior of policyholders (also increasing insurability, by reducing insurers’ exposure); on the other hand, imply reduction on insurance affordability by reducing risk transfer: the lower insurance premium associated with the lower risk cession corresponds to the cost, to risk-averse agents, of retaining more risks. In the case of the large risks discussed here, the impact of deduct-ibles on impairment of insurance affordability is even more relevant than in the case of ordinary risks.

33 Nguyen, T. (2013): “[...] In general, it is difficult to estimate the loss distribution of catastrophe risks (the so-called low-fre-quency but high-severity risks). Consequently, the insurers require higher risk premiums so that in the end the total premi-ums (expected loss + risk premiums) may be much larger than the expected loss. In some cases, insurance cover does exist but it is just unaffordable for the insured [...]”.

34 Swiss RE (Sigma), 2016.


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Such a gap, as we shall see in the last section of this chapter, is not homogeneous when compared to continents and countries, and this dispersion is a relevant indicator for the mapping and understanding of the explanatory factors of the geographically verified coverage gap, and strategic input for the formulation of strategies and regulatory incentives aimed at reducing them35.

In its temporal evolution, the gap has widened, as illustrated in Graph 1, below (already presented in Chapter 1 and repeated here for convenience)36:

Graph 1Evolution of Coverage Gap - total losses and Insured losses - 1980-2014

Source: http://www.gccapitalideas.com/2016/03/03/insured-versus-uninsured-loss/

35 An alternative measure of the level of risk coverage by the insurance market in relation to the economy of a country, in a given sector or activity segment of a market, is given by the penetration rate, which corresponds to the ratio between the amount of direct insurance premiums collected, over a given period of time, and the value of GDP. Comparing the two measures of protection gap, we have the insurance premium as a function of a probability and of a recovery rate, estimated ex ante. In disasters, the recovery rate, given the materialization of the event of catastrophe, is typically low. The premium is a measure of expected losses and may be underestimated in relation to actual losses (ex post). In both cases, gap protection and penetration coefficient, refer to measures of losses: the former, to materialized insured losses (ex post); the latter, to expected losses (the insurance premiums, ex ante), therefore. Comparisons with GDP can also generate short-term discrep-ancies, as there are portions of GDP that could have no direct (or lower) correlation to insurance at a given point in time (and vice-versa), not demanding this product, but both measures are, in principle, reconcilable with each other if observed over longer time series, which better capture the structural aspects.

36 http://www.swissre.com/media/news_releases/preliminary_sigma_estimates_total_losses_from_disaster_events_rise_to_USD_158_billion_in_2016.html?mobile=iphone. Preliminary sigma estimates (15/12/2016): “Total losses from disaster events rise to USD 158 billion in 2016. Total economic losses from natural catastrophes and man-made disaster are estimated to be USD 158 billion in 2016. Insured losses from disaster events were around USD 49 billion”. That is, 31% protection gap.


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The existence of such a gap and market failure at global level, as well as its geographical differentiation, is, in our view, associated with the peculiar characteristics of environmental risks, differentiating them from ordinary risks, and their consequent non-typical properties of insurable risks.

It is never too much to emphasize that, for the purposes of the present analysis, this differentiation is anchored in a simplified statistical vector characterized by:

- low probability;- high volatility and uncertainty;- high relative dispersion (“ambiguity”);- high correlation of events; and- exposure to high levels at risk.

Table 1, below, systematizes different reasons for the existence of the protection gap, essentially in line with what we have here pointed out37.

Table 1 Contributing Factors for the protection Gap

37 In Table 1, in group 1 (Low Insurance Penetration), the moral risk and arbitrage aspects associated with the public offering of insurance with risk-adjusted pricing and the provision of unconditional indemnities by the State, ex-claims, seem to result in asymmetries of signaling that compromise a perception of risk with greater alignment of interests between the public sector and private agents.

Source: http://www.gccapitalideas.com/2016/03/03/insured-versus-uninsured-loss/


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The high volatility of the distribution of losses in risk events related to environmental disasters is statistically directly associated with low probability, and implies a higher coefficient of variation (or “ambiguity”, in line with a greater relative dispersion when comparing environmental risks to ordinary risks).38

Uncertainty (informational and regulatory-legal) implies in a precariousness in the calculation of the frequencies and probabilities of occurrence of losses, as well as the calculation of their value, when they materialize.

The high correlation of events and/or exposure to high values at risk imp jeopardizing the effectiveness of LLN and the impossibility of effective risk mitigation through diversification.

Viewed otherwise, symmetrically, the validity (in the ordinary branches) of the basic insurance properties corresponds to set-ups of the risk component vector, so that the benefits of spraying on independent and small-value exposures (that is, diversification) converge the value of the maximum loss of the portfolio to the value of its expected loss (risk premium),39 applying to LLN.

As a result of the above-mentioned statistical vector, the financial variable that best summarizes and explains the existence of the environmental risk protection gap is in the highest capital intensity required for the retention of these risks.

And this capacity requirement (for the retention of environmental risks) is limited even by the most capitalized agents in the insurance market, such as reinsurers, resulting in the need for capacity-building by the capital market and/or by government entities (ex-ante, via insurance provision, or ex post, by the absorption, from society, of losses)40.

38 Statistically, a distribution that exhibits a lower frequency of values close to its average will consequently have greater dispersion (for example, volatility or standard deviation). Distributions with this characteristic have a higher coefficient of variation (or relative deviation).

39 Statistically, by the application of the LLN in a portfolio of infinite independent exposures of small value (thus emulating the spraying of a large risk into scattered risks in several baskets), the expected loss resulting from the diversification benefit will converge to that relating to exposure to a single risk of small value. Non-application of the LLN implies that, even if risks are spread, their correlation emulates the exposure to a single risk factor of great value and impact (definition of systematic or non-diversifiable risk).

40 Muir-Wood, R (2009):” [...] Insurance is based on the ability to transfer potential unforeseen, “accidental◦ costs to a counterparty in exchange for an ex-ante fee. Counterparty requires less capital gearing to support a payout if the risk can be diversified. Diversification assumption breaks down under risk correlation = catastrophe – which is why insurers buy insurance (from reinsurers). The insurance food-chain is driven by the need to transfer risk onto an entity who can achieve further diversification – Insured to Insurer to Reinsurer (to Capital Markets) [...]”.


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Still, our working hypothesis is that the distinct configuration of the environmental risk vector allows to explain the different penetration coefficients and protection gaps when comparing:

- large risks from ordinary risks, regardless of geographical region; and

- different geographic regions, the weight of each component of the vector being a function of the idiosyncratic characteristics of each one, be it in relation to the nature, frequency and impact of environmental disasters (for example, due to nature or resulting from human action); and the role of regulatory-legal uncertainty in each national or continental jurisdiction.

Also, still exploring the potential of this analytical perspective to understand the requirements and strategies of retention and transfer of environmental risks by insurers and reinsurers, it is possible to apply the same theoretical framework for the mapping and differentiation of the effects of climate changes now in international evidence, without going into merit or judgment on whether we are going (or not) through a period of global warming.

Climate change can be seen as a relevant change in the set-up of the configuration of our vector of basic risk components, that is, it implies the material change of one or more factors, for example, frequency and volatility of occurrences (which result in different averages and standard deviations), and/or their impact and correlations.

Each configuration of the vector at the state of nature will correspond to a certain capital requirement, and climate changes can be understood, from the perspective of insurance and reinsurance provision, as a spectrum of different set-ups of this vector with respect to its ordinary parameters.

An interesting consequence of this approach is that, for example, the increased frequency of a particular modality of environmental risk may correspond to a greater adherence to the properties that make insurance feasible, the lower capital requirement (which increases insurability) and the corresponding establishment of a risk premium that is bearable to the risk-averse economic agents (affordability).

Graphs 2, 3 and 4, below, illustrate, schematically, the effect of climate changes in light of the conceptual framework discussed above, taking into account changes in the frequency and/or volatility of the occurrence of environmental disasters as factors for investigating the effects changes on the required level of capital41.

41 The Chartered Insurance Institute (2009). Climate change research Report.


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Another interesting example to illustrate the analytical capacity of the conceptual framework in discussion is the evaluation of a particular risk event, such as Hurricane Matthew, which, in October 2016, affected a large area from the Caribbean to the southern United States42.

The same natural catastrophe has generated more than 800 deaths and total destruction in Haiti; and, while causing serious damage and fatalities in the US, its impact was far less.

Different preparations (resilience is being currently discussed quite often, the capacity for adaptation and flexibility in the face of

GRAPHs 2, 3 and 4Climate Change and Changes in Frequency and volatility

in Environmental Risk

Source: The Chartered Insurance Institute (2009). Climate Change Research Report.

42 http://mobile.lemonde.fr/planete/article/2016/10/08/haiti-apres-l-ouragan-matthew-je-vois-surtout-un-pays-affaibli-de-laisse-ignore-estime-raoul-peck_5010509_3244.html e http://www.swissre.com/media/news_releases/preliminary_sigma_estimates_total_losses_from_disaster_events_rise_to_USD_158_billion_in_2016.html?mobile=iphone (15/12/2016)


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adverse events); and mitigation mechanisms43. Different societies and accountabilities44.

Insurance pricing and capital calculation for risk underwriting will reflect these different situations.

In the case of Haiti, the appetite of insurers and reinsurers to cover this risk will be lower and the price higher45. Why?

Relatively more capital than the risk premium will be required for the provision of the coverage: the loss is more expected than unexpected, due to, ex ante, the factors generating the concentration risk underlying the natural catastrophe being at a critical level. Here are classic elements of absence of insurability and affordability for the provision of insurance.

In the case of the US, there will be, on the part of the insurance/reinsurance market, greater appetite/lower price. The loss is less expected than unexpected, as ex ante mitigation measures of concentration risk factors are relatively more present than in Haiti, resulting in different underwriting, retention and risk sharing/transfer strategies, by the insurance market, therefore.

Another way of saying the same thing about insurers’ strategies for underwriting risks in Haiti and the US, for the same risk event, but with different impacts (loss or casualty, given the same event in the two countries):

43 The concept of resilience in the addressing catastrophic events is associated with preventive measures and the revision of building codes and techniques in regions affected by natural disasters. http://www.gccapitalideas.com/2016/10/24/from-public-to-private/ “[...] An integrated and coordinated approach to collaboration between the insurance industry, governments and other public bodies is increasingly recognized as an effective method of creating sustainable risk-transfer mechanisms. More strategic discussions among governments, non-governmental organizations, the scientific and academ-ic communities and the insurance industry will help to promote better disaster risk management and the implementation of pre-event insurance solutions. The protection gap presents opportunities for the (re)insurance industry far beyond the catastrophe segment. New risks in areas such as technology, science, medicine, climate change, population growth, food security and urbanization offer challenges and provide opportunities for profitable growth. Some of the risks are very com-plex or were previously little understood, yet today we better understand risk than at any time in history. We have better science, data and analytics, and tools to understand, measure price risk. Concurrently, significant market capacity exists due to the inflow of large amounts of capital looking for opportunities to transfer risk[...]”.http://www.gccapitalideas.com/2016/10/23/baden-baden-reinsurance-symposium-explores-ways-of-bridging-protection-gap/ “[...] He added: “The key to resilience - which is not simply about insuring against and recovering after losses, but is also about protecting and mitigating against those losses - is to recognize that information, and the transfer of that information down to the local level, is central to our ability to respond to this change. We need to empower local actors - be they policyholders, munici-palities or brokers - with better information to be able to respond. This is how we can work together to close the gap. [...]”.

44 https://openminds.swissre.com/stories/1152/ (05/12/2016). “We can´t stop Mother Nature - but we can prepare”.

45 In a simplified form, risk tolerance of an insurance and reinsurance provider will be the function of the ratio between its Own Funds (OF) and the capital requirement (K) associated with the retention of a particular portfolio of exposures to risk. Such a ratio is generically, in its various forms, called the Solvency Ratio, that is, a measure of the solvency of an insurer/reinsurer. The higher the OF/K ratio, the greater the risk tolerance.


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- In Haiti, the loss is so expected that, in order to retain risk, the insurance premium has to be so high that there is no way to be paid by the policyholder (low affordability). Either you do not underwrite to the risk or you underwrite only if you find a pool of other agents (other insurers, coinsurance, or reinsurers) to dilute the risk in small pieces; and

- In the US, relatively higher risk retention (and lower transfer) will be the strategy for underwriting. The pool may involve fewer agents, due to the possibility of better addressing by the insurance market, the trade-off insurability x affordability.

On the basis of the above, the large risk vector has its well captured and defined materialization, in the form of a higher capital requirement (in relation to ordinary risks) to deal with non-diversifiable risks (or systematic risks, associated with events correlated to the same occurrence), of high value and unexpected losses of low probability and significantly higher impact than the average of the distribution of losses.

The capital requirement, therefore, appears as the measure of standardization of the statistical-financial quantum (a measure of equivalence, homogenization of the risk quantum) associated to different configurations of the risk vector as to its individual components.

Capital emerges as an objective and uncontroversial measure of risk. In addition, the strategies of retention and transfer of environmental risks by insurers and reinsurers, from this perspective, can be mapped and understood as an exercise of optimization of returns subject to a capital constraint (that is, maximization of RAROC).

More capital implies pressure for lower risk-adjusted returns. Greater capital intensity for the retention of these risks will, in turn, be linked to maintaining the intertemporal solvency of insurance and reinsurance product providers.

Returns x Solvency, a new trade-off. In fact, the most important one in driving business strategies in the insurance market.

At the root of the strategies for retention and cession of environmental risks in insurance and reinsurance, we will have a crucial trade-off between returns and risks that is particularly critical, due to the relatively higher capital requirement associated with large risks, in order to ensure the solvency of risk tolerant agents, insurance providers for those who are risk averse.


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But what does the guarantee of that solvency mean in time?

Briefly, that, in the case of the provision of insurance for environmental risks, the existence of a capital layer materially superior to the expected losses (to risk premiums) is necessary to ensure that, once the risks are insured, an insurer or reinsurer will not go bankrupt (that is, they will lose more than what is defined as Value-at-Risk, metric that we will visit in the next section)46.

In other words, in the event of a casualty, insurers/reinsurers will not become insolvent if they have a level of capital (net worth, in accounting language) equivalent to the sum of expected and unexpected losses, parametrically associated with risk (that is, for a given vector configuration), with a probability given by a predetermined level of significance (tolerance to risk)47.

Symmetrically, the solvency probability is given by the confidence level defined by 100% minus the level of significance arbitrated, corresponding to a level of risk tolerance48.

We then synthesize our strategic vector in light of which we will analyze the dynamics of retention and sharing/transfer of risks associated with environmental disasters:

- non-compliance with ordinary properties of affordability and insurability;

- achievement of intertemporal solvency levels (regulatory and economic) by the insurance/reinsurance market;

- complementation of capital capacity by the noninsurance financial market (capital markets) and/or by public insurance offering vehicles; and

- apportionment of uninsured losses throughout society.

46 This layer of capital is called Solvency Capital Requirement (SCR), in the solvency regulation developed under the most advanced international benchmarks (like EIOPA - European Insurance and Occupational Pensions Authority), set for a confidence interval of 99.5% (that is, a probability of 0.5% of ruin in a given year; or, equivalently, that of not surviving a catastrophic event every 200 years).

47 http://www.gccapitalideas.com/2016/09/22/increasing-confidence-and-transparency-in-your-catastrophe-risk-deci-sions-part-i/ “[...] These are questions of risk appetite and risk tolerance. The Institute of Risk Management defines risk appetite as “the amount and type of risk that an organization is willing to take in order to meet their strategic objectives.” Conversely, risk tolerance is often expressed as a quantitative measure of the maximum amount of each type of risk one is willing to take. In the context of insurance and catastrophe modeling risk appetite is about how much risk you are willing to take and risk tolerance is about how wrong you can afford to be when volatile loss experience rears its ugly head. Insurance executives and risk managers use catastrophe models to help inform these decisions, but how good are the models and how well do they represent your specific risks?[...]”

48 Credit Suisse (2016). Behavioral Insights: Loss Hurts. “[...] Humans hate to lose: the pain of losing is psychologically about twice as strong as the pleasure of making profit. Fear of losing has an unquestionable impact on investment decisions [...]”.


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In section 2, we will cover how regulation and the market treat capital quantification and measurement, and how the solvency equation and insurance market returns is in line with a strategy of insurance provision and retention of risks compatible with the verified finding, of the existence, at global level, of a protection gap of the environmental risks, in light of this requirement.

In the previous section, we have established a significant differentiation between large risks in general (and environmental risks, in particular) and ordinary risks as regards the non-adequacy of the first to the basic properties of affordability and insurability that characterize the latter and define the own logic of the business of insurance and reinsurance of risks.

It was pointed out that the non-application of the LLN, where it allows the fractionation and diversification of risks, jeopardizes the strategies of retention of risk of the insurance/reinsurance market due to the high capital intensity associated to the nonconformity of large risks to the type of ordinary risks.

Non-diversification, whether by exposure to high-value risks or exposure to smaller, but highly correlated (or non-independent) values, which, by definition, is equivalent to exposure to concentration risk, implies that, for an insurer/reinsurer, the value of the expected loss (that is, the value of the risk premium) is:

- on the one hand, insufficient to guarantee the solvency of the insurance provider in the event of risk materialization (which compromises the insurability of the risk from the perspective of the insurance market); and,

- on the other hand, too high for a risk-averse agent to transfer it to an insurer and then for an insurer to dispose of it to a reinsurer (which affects the affordability of the risk from the policyholder’s perspective).

The environmental risk protection gap at global level indicates that even the reinsurance layer (the most capitalized market instance) is subject to capital constraints that are intrinsic to the requirements for risk retention of this type, which generates a market failure occupied by insurance instruments with state provision and, to a lesser extent, by instruments available in the capital market.

2. Measurement of Environmental Risk and solvency


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The loss gap not covered by insurance/reinsurance financial market, capital markets and public vehicles products (funds, pools, programs and insurers) is absorbed by society in the form of repairs and transfers of resources at the expense of the State49.

In technical terms, the calculation of risk premiums in insurance activity follows the same logic observed in banking activity, both anchored in the stochastic calculation based on basic risk components, generally applicable to the different types mapped by financial theory and incorporated into the banking and insurance regulations, of which we exemplify below some that are traditionally better known50:

- market risk: risk associated with the change in value of an asset associated with changes in interest rates, exchange rate, GDP growth, etc.

- credit risk: the risk of a counterparty in a credit agreement does not pay the interest and/or principal installments of the same contract;

- operational risk: risk associated with human failure, processes and (dis)governance;

- Underwriting risk: typical of the insurance market, risk retained by the offer of an insurance product that may imply indemnification in case of materialization;

- liquidity risk: risk of financial loss in the conversion, from an asset, into currency, at fair price, in non-forced negotiation.

49 Nguyen, T. (2013). “[...] Catastrophic events have increased enormously during the last decades. Our analysis of insurability concepts shows that catastrophic event as low frequency/high severity risks do have some characteristics that make them uninsurable. Most of the actuarial and market determined criteria for insurability are not fulfilled by catastrophe risks to a certain degree. This explains the fact that private insurers are reluctant to give insurance coverage for catastrophe risks. In some cases, there is no private insurance solution for catastrophe risks or even if insurance does exist, its premium is too high and therefore unaffordable for the insured. Due to this market failure, governments around the world have participat-ed in insurance programs in order to make insurance available and affordable.

A key question that needs to be addressed is the circumstances where a state’s participation in insurance solutions can be justified. The majority of state catastrophe insurance programs were established following an extreme event that severely taxed the private insurance market. In some extreme situations (for example, directly after a hurricane with extreme losses) the government should give state guarantees or participate in private-state insurance solutions in order to avoid a col-lapse of insurance markets. Premiums can be kept more affordable if the government covers part of the extreme damage because in a private market, premiums often considerably exceed “actuarially fair” values. But government risk sharing must not be used to subsidise certain enterprises or branches. Subsidised low premiums remove important incentives for preventative measures and directing building activity toward less risky areas. Lax prevention and building in high-risk areas ultimately leads to higher losses that in the end all taxpayers are forced to bear. This results in an inefficient allocation of risks in the society.

Insurance is a means of providing compensation for financial losses in case of an adverse event. In some cases, it seems to be better to prevent losses before they can happen. The optimal solution is usually a combination of the two, implement-ing preventative measures to reduce the loss frequency and the severity of damages, and then insuring against rarer and more costly events. Government preventative infrastructure spending can reduce future losses and the need for subsidised property insurance schemes. Providing financial incentives to prevent damage can be regarded as a public good that is likely to be undersupplied by private insurers, because the benefits of prevention, in terms of lower flood or earthquake damage and hazard to human lives accrue to the broader community that is protected, while such benefits cannot be completely captured by an insurer in a competitive market [...]”.

50 For an exhaustive listing of all risks covered in the international and national banking solvency and insurance/reinsurance platforms, Solvency 2 (EIOPA), Basel 2 & 3 (BCBS), and CNSP 321/2015 (CNSP).


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What would the basic components associated with such a diverse spectrum of risks be?

The translation of risks into well-defined conceptual parameters has been, especially in the last three decades, the object of countless studies and recommendations developed in the academic field, by international regulatory bodies of the banking and insurance sectors, and, not least important, in research developed by practitioners and specialists from these industries.

Although, given the specificities of each segment, the technical-regulatory framework of banks (Basel Committee - BCBS)51 and insurance companies (EIOPA)52,53 presents differentiations, in essence, the translation of risk into basic components is essentially equivalent and is anchored in the evolution of statistical theory applied to risk management.

The following are the ordinary risk components, more or less common to the different relevant conceptual frameworks54:

- the probability of risk materialization (PRM): is a value between zero and 100%;

- the loss, given the materialization of the risk (LGM, the impact): also a value between zero and 100%. It complements the recovery of the insured amounts;

- exposure at risk (EAR): the exposure value, in monetary units.

51 BCBS. Basel Committee on Banking Supervision.

52 EIOPA (European Insurance and Occupational Pensions Authority). Solvency II - Solvency II reviews the prudential regime for insurance and reinsurance undertakings in the European Union. Regulatory framework. The Solvency II Directive (Directive 2009/138/EC) was adopted in November 2009, and amended by Directive 2014/51/EU of the European Parliament and of the Council of 16 April 2014 (the so-called “Omnibus II Directive»). 31 December 2015 – termination of the preparatory phase; 1 January 2016 – Application of the Solvency II regime. For details of the state of the art of the international regu-latory overview in the article, see Guy Carpenter (2015): “Regulation: a World View”.

53 http://www.gccapitalideas.com/2016/09/15/solvency-ii-equivalence-in-the-international-reinsurance-landscape/ “[...] The ob-jectives of Solvency II include improved consumer protection and modernized supervision that shifts supervisors’ focus from compliance and capital monitoring to evaluating insurers’ risk profiles and the quality of risk management processes. While Europe initiated the ideas embodied in Solvency II, other jurisdictions have taken this example and implemented their own risk driven regulatory regimes. As a result, Solvency II has led to a new global solvency standard. The Own Risk and Solvency Assessment (ORSA) principle has created a framework for the risk and risk mitigation environment, which is now accepted globally, from the United States and Bermuda and extending to Asian countries. The European Commission (EC) has adopted a number of equivalence decisions for third countries under Solvency II, which set out rules to develop a single market for the insurance sector. After receiving equivalence, third country insurers are able to operate in the European Union (EU) in compliance with all EU rules. The United States, in addition to Australia, Brazil, Canada, Japan and Mexico, has been granted provisional equivalence regarding group solvency calculations for ten years. Switzerland and Bermuda have been granted full equivalency, while Japan has received equivalence for reinsurance. Equivalence status has both strategic and capital manage-ment implications. For firms operating inside non-equivalent countries, these firms may be required to change or alter their strategies. Non-equivalent firms may face higher capital requirements, which could deter their expansion into new territories, or their ability to offer and write new products, or even delay the payment of dividends.[...]”

54 PRM, LGM and EAR are acronyms created for specific use within the scope of this article.


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These parameters are related to individual exposures, and their aggregation in a portfolio of exposures demands the consideration of their independence and correlation, in order to evaluate the application or not of the diversification benefit/LLN.

The use of the basic risk elements in the calculation of risk premiums and capital requirements is straightforward, and, schematically, the following formulation is applicable:

- Risk premiums: correspond to the Expected Losses (EL) in a given exposure, corresponding to the product:

El = pRM x lGM x EAR

- Capital (K): corresponds to the value that an insurer/reinsurer must have in net worth (NW) to absorb losses that exceed expected losses. The formulation, schematically, corresponds to the setting of a number of standard deviations corresponding to the confidence interval of a solvency measure.

In technically more rigorous terms, capital corresponds to the buffer of resources to cover the Unexpected Losses (UL), that is, those that exceed the EL.

ULs are associated with the standard deviation (the volatility and uncertainty) of the distribution of losses (that is, the deviation from the mean), as well as the correlation of these deviations, are relevant in large risks, as we have already studied, will be greater as the volatility, uncertainty and correlation associated with the distribution of losses increase.

Some stylized facts can be extracted from these ordinary definitions and contribute to the understanding of the protection gap and the resulting market failure with regard to environmental risks:

- in the hypothetical case of totally correlated exposures, the implication is that the diversification effect is zero, being equivalent to exposure to a single high value exposure;

- in the case above, the non-application of the LLN results in an insurer, even considering the low PRM associated with environmental risks, taking a chance at risk of insolvency if these manifest, since, typically, LGM is close to 100% In this type of risk (that is, the recovery of insured amounts is close to zero).


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- it is clear that a risk premium that minimizes the risk of insolvency of the insurer/reinsurer would have to correspond to the value of the exposure itself to be insured (which compromises its affordability)

- the capital needed to withhold this risk may be above the capacity of the insurers/reinsurers’ shareholders to provide resources in these vehicles, even considering the possibility of reducing this requirement by applying classic mitigation strategies, such as the use of deductibles and coverage percentages below 100% of the risk exposure55.

In other words (simply put), the non-conformance (violation), of environmental risks, of the intrinsic properties of the insurance business entails a set-up of ordinary risk parameters (PRM, LGM, EAR), which is equivalent to exposure to a single risk event of great value and high impact.

This “single risk event”, even with a low probability of occurrence, may imply the insolvency of an insurer/reinsurer if it does not have a NW greater than or equal to a certain minimum value that absorbs the losses (in excess of the expected losses) , if they materialize.

This capital requirement leads us to the concept of VaR (Value-at-Risk), the measure of maximum loss that a given agent can suffer in a given time interval, with a certain level of significance56.

The use of VaR as a risk measure by banks and insurance companies has been the subject of development over the last decades, corresponding to the application, in these business lines, of the evolution of financial theory.

55 Recalling what we have already observed about the commitment of insurance affordability when applying these mitigants, by insurers and reinsurers.

56 The strategic decisions of insurers, reinsurers and banks in risk management and capital requirements scaling fit into a broader conceptual framework and tools, called ERM – Enterprise Risk Management [GC Capital Ideas (2009)]: “[...] Prior to the recent turbulence in the financial markets, insurers and reinsurers were increasing their use of Enterprise Risk Management (ERM) to make risk and capital management decisions. While this was driven in part by rating agencies and regulators, many carriers began to recognize the value of metric-based frameworks and capital models in evaluating their portfolios [...]. As the financial crisis continues to unfold – and explanations are offered – it is clear that more robust en-terprise-wide risk management will be the result. Many industry participants and observers anticipate that regulatory and rating agency scrutiny will accelerate at an unprecedented rate. Further, insurer and reinsurer shareholders and Boards of Directors are likely to demand that risk be measured and managed as it relates directly to capital on an enterprise-wide basis, particularly as an integral part of the corporate governance process. Advancing the ERM dialogue can help insur-ers make value-accretive decisions through the improved deployment of capital. A thorough understanding of the basic concepts of enterprise-wide risk is fundamental to the implementation of ERM disciplines, establishing risk management parameters, and integrating this knowledge into the process of making strategic business decisions. As a result, insurance and reinsurance firms will not only be better prepared to respond to the internal and external questions relating to risk and capital, but (perhaps more importantly), they could benefit by establishing hedging or reinsurance strategies to drive capital efficiencies and maximize stable risk-adjusted returns [...]”.


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Excluding VaR limitations (such as its non-subadditivity, tail imperfection, etc.) and more consistent measures (such as T-VaR), this essentially defines a risk tolerance measure for an insurer/reinsurer to underwrite and retain risks. The probability of insolvency will correspond to the level of significance established for the VaR (or for the VaR).

More strictly, the definitions of these two risk tolerance measures are as follows 57:

- vaR (value-at-Risk): the maximum value of the loss to be incurred in a given period of time (typically one year), with a certain probability (which is equivalent to a level of significance corresponding to the risk tolerance of an economic agent);

- t-var (tail Risk)58: weighted average of the possible losses of occurrence beyond the level of significance, that is, losses higher than VaR, concentrated in the tail of the distribution of losses.

Schematically, Graphs 5 and 6 below exemplify, in a hypothetical asymmetric distribution of losses (such as those related to environmental risks), the relationships between PRM, LGM, EAR, Expected Losses, Non- Expected Losses and VaR:

57 On the properties required for a coherent risk measure, see Tasche, D. (2005). Risk contributions in an asymptotic multi-fac-tor framework. Workshop “Concentration risk in credit portfolios”.

58 Also called C-VaR (Conditional VaR) or ES (Expected Shortfall). It is said that T-VaR is a coherent measure of risk. [Lachowicz, P. (2016)]. Conditional Value-at-Risk in the Normal and Student t Linear VaR Model: “[...] Conditional Value-at-Risk (CVaR), also referred to as the Expected Shortfall (ES) or the Expected Tail Loss (ETL), has an interpretation of the expected loss (in present value terms) given that the loss exceeds the VaR. For many risk analysts, CVaR makes more sense: if VaR is a “magical” threshold, the CVaR provides us with more intuitive expectation of how much we will lose if the asset drops in trading (over next hh days) below a pre-calculated VaR. The underlying model for VaR is directly linked to the daily return distribution for the asset (or portfolio) by the best fit [...]”.

Graph 5Expected, unexpected and vaR losses

Source: BCBS (2005)


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In terms of mathematical formulation, simplified, by simple verification of Charts 5 and 6, we have:

Capital = vaR – El.

This relationship is of particular importance for the understanding of the coverage gap of the insurance and reinsurance market with regard to environmental risks.

As we have seen, the non-observance of the basic properties for the operation of the insurance activity, both from the point of view of affordability for risk-averse agents (seeking coverage/transfer of risk); and from the perspective of risk-tolerant agents (insurers and reinsurers), entails a market failure, to be occupied (ex-ante) by private and/or public insurance provision vehicles; or by apportioning the costs of environmental disasters throughout society (ex post, through repairs supported by government bodies, with public resources).

But what would the relationship between the parameters presented in Graph 5 and this configuration of imperfection of the insurance and reinsurance market in addressing the risks associated with environmental disasters be?

The relationship is, as stated in section 1, in the capital requirement. The typology of environmental risks requires, as we have seen in that section, the formation of a layer of capital to deal with unexpected losses, of a systemic nature, associated with the impossibility of diversification.

This capital layer (net worth), when we confronted with the risk weighting of exposures subject to insurance coverage, should, as we have

Graph 6Expected, unexpected and vaR losses

Source: BCBS (2005)


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seen, be sufficient for, in a given level of risk tolerance (corresponding to a certain level of significance) ensure the intertemporal solvency of the insurance provider59.

The relation between the capital layer and the volatility and uncertainty of the distribution of losses has an essential nature even when various continuous and discrete possibilities with which such functions may present themselves are considered.

The discussion of the various distributions that allow the modeling of losses associated with the materialization of environmental risks is not the subject of this chapter.

But within this diversity, it is possible to establish a relationship of essence in which, typically, the calibration of the level of confidence (the symmetrical level of significance) associated with a given risk tolerance will be related to volatility (or, simply put, to a number of standard deviations) of the losses around their expected value.

Schematically, the following general formulation applies:

K = f (pRM, lGM, EAR) @ C.I.

Where PRM, LGM, EAR were defined earlier in this section and C.I. corresponds to the Confidence Interval corresponding to the level of risk tolerance arbitrated.

The probability of insolvency is given by 100% - C.I. and corresponds to the level of significance arbitrated.

Alternatively, we have:

[email protected]. = f(pRM, lGM, EAR) and vaR = El + ul

This conceptual framework represents, synthetically, the heart of the solvency approaches constituting national and international benchmarks in banking and insurance/reinsurance activities.

The calculation, whether is of Minimum Capital Requirement

59 In a schematic way, it can be said that an objective measure of the risk tolerance of an insurer/reinsurer is related to the sufficiency of its net worth in relation to the capital requirement necessary to retain a certain exposure to risks.


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(MCR) or Solvency Capital Requirement (SCR) will be associated with a confidence interval of typically 99.5% in insurance regulation, and 99.9% in banking regulation (Basel), to which they will correspond, by complement in relation to the 100 maximum likelihood of insolvency (or ruin) will correspond, of the risk underwriter60.

The state of the art of the international reference for regulatory developments in the field of insurance and reinsurance is well represented by Directive 2009/138/EC, which establishes requirements and deadlines for compliance with requirements61,62.

In Brazil, CNSP Resolution 321/2015 establishes the regulatory adequacy requirements for MCR and the SCR, taking into account, among others, market, underwriting, operational, liquidity and credit risks63,64.

60 EIOPA The SolvencyIIDirective(Directive2009/138/EC)was adopted in November 2009, and amended by Directive 2014/51/EU of the European Parliament and of the Council of 16 April 2014 (the socalled “Omnibus II Directive”).On 10 Octo-ber 2014, the European Commission (EC) adopted the Delegated Regulation (Delegated Regulation(EU)2015/35)con-taining implementing rules for Solvency II. The Delegated Regulation was published in the Official Journal on 17 Janu-ary 2015. In February 2015, EIOPA published the first set of Solvency II Guidelines in all the EU official languages. 1 January 2016–Application of the Solvency II regime; Mid April2 016 First prudential reporting by undertakings under Sol-vency II with reference to the first day of application (for undertakings with financial year-end on 31 December).

61 http://www.gccapitalideas.com/2016/09/12/solvency-ii-greater-risk-driven-management/ “[...] On January 1, 2016, the Solvency II regulatory regime took effect. Some celebrated; others were weary from the months and years of preparation. However, to borrow a turn of phrase from Winston Churchill, this is not the end of Solvency II, it is not even the beginning of the end, but it is the end of the beginning. The impact of Solvency II goes well beyond its strict regulatory assessment. Solvency II creates an environment for greater risk-driven management of the (re)insurance companies doing business in and with Europe. While the solvency capital requirement (SCR) and minimum capital requirement are the thresholds used by regulators to trigger action on specific entities, the solvency ratio (own funds over SCR) is fast becoming an important metric for comparing companies. Today, many companies publish their solvency ratios without being required to do so, and some others actually specify target solvency ratio ranges as part of their risk appetite and financial targets [...]”.

62 Prudential. Solvency II Update. “[...] Solvency II is framed to demonstrate ability to withstand severe stress. Solvency II uses a market consistent approach, where the Solvency Capital Requirement (SCR) measures the potential reduction in the value of Own Funds over 1 year, in an adverse 1/200 year event, taking into account all quantifiable risks (Confidence Interval of 99.5%) [...] “

63 The MCR is established, in Resolution CNSP 321/2015 between 25% and 75% of the SCR and the SCR is defined in the confidence interval of 99.5%.

64 In particular, the establishment, by regulators, of specific solvency capital requirement (SCR) for catastrophic risks represents a critical step in the process of reducing informational and cognitive asymmetries with the objective of reducing the pro-tection gap related to these risks. In Brazil’s case, where the quantification of such requirement (in a standard formula) still does not exist in the regulatory framework applicable to capital design by (re)insurers (CNSP Resolution 321/2015), a convergence with international regulatory structures that explicitly address the problem (EIOPA (2014 and 2016)) would be a rational strategy to be observed, especially within a possible scenario of lower real interest rates and ensuing need for greater risk retention (among which catastrophic ones) in the balance sheets of protection providers, aiming at the efficient management of RAROC. The recognition and validation, by regulators, of internal models for the capital dimensioning of catastrophic risks by insurers and reinsurers is also critical in order to give greater precision and economic rationality to the decisions to retain and transfer these risks.


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Figure 1, below, illustrates the balance of assets and liabilities related to the solvency of (re)insurers agents in light of the Solvency II regulatory platform.

65 In principle, standard capital requirements are conservatively set by the regulator at higher levels than requirements derived from internal models (which have an often high development cost). This same distinction is, in essence, what differentiates the concepts of regulatory capital (for example, the one dimensioned to meet the regulatory requirements of systemic sol-vency); and economic capital (for example, the one calculated individually by banks and insurance/reinsurance companies to optimize their RAROC strategy, balancing out the return and solvency trade-off).

Figure 1the Solvency II Balance Sheet

Source: Solvency II Update – KPMG (2016)

Both national and international regulation provide for a standard model for the calculation of capital requirements, as well as the possibility, through the validation by regulatory bodies, of the adoption of internal models65.

The establishment of a standardized calculation of minimum capital requirements by the regulator is associated with a conservative level derived from observance of systemic solvency, without prejudice to the fact that insurers and reinsurers, in analogy to what is verified in national banking regulation (BACEN) and international regulation (BCBS), can validate less conservative estimates based on internal models.


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We will see, in the next section, that the distinction between regulatory and economic capital has direct implications for the calculation of the risk-adjusted return of insurance and reinsurance companies (RAROC) and, consequently, on the configuration of their retention and risk transfer strategies66.

Also, nationally and internationally, the non-observance of minimum requirements, in time, provides for the initiation of control, compliance, and rectification of insufficient capital actions that, in the limit, may imply intervention and even liquidation of insurance and reinsurance providers67.

66 See footnote #44.

67 This is the case of the regulatory minimum limit for capital (MCR) in the Solvency 2/EIOPA reference. In the same lien, CNSP Resolution 321/2015 establishes that the non-compliance with minimum capital requirements entails the intervention of the regulator and, in the limit, may lead to liquidation. RC and SRP, in the citation correspond to Risk Capital and Solven-cy Recovery Plan, respectively: “[...] The supervised companies must present monthly, when closing the monthly balance sheets, ANW (Adjusted Net Worth)equal to or higher than MCR and liquidity in relation to RC.

Art. 67. In the event of insufficiency of ANW in relation to MCR of up to 50% (fifty percent) or liquidity insufficiency in relation to RC, the supervised party shall submit SRP in the manner provided in this Chapter, proposing an action plan to the recovery of the solvency situation.

§ 1st The SRP will only be required if insufficiency is determined for 3 (three) consecutive months or, specifically, in the months of June and December.

§ 2nd The worsening of the insufficiency of ANW to the levels established in articles 68 and 69 will leave the supervised ones subject to special regime, under the terms of the current legislation. Art. 68. Those supervised will be subject to the special fiscal-direction regime, according to the current legislation, when the ANW insufficiency, in relation to the MCR, is greater than 50% (fifty percent) and less than or equal to 70% (seventy per cent). [...] “

Figure 2 Solvency Ratios in the International Market

Source: Solvency II Update – KPMG (2016)


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Insurance and reinsurance risk rating agencies, such as AmBest, have revised their analysis methodologies in line with the progressive convergence between ratings and solvency, in the sense that they can more objectively reflect insolvency probabilities associated with a stochastic calculation (based on basic components of risks such as PRM, LGM, EAR and their correlations) of the capital adequacy to cover the risks of a certain portfolio of exposures.

For example, if we consider the complement of the confidence interval (or level of significance) of VaR, a given rating (AAA, AA, A, etc.) will correspond, based on a historical series of probabilities of insolvency pertaining to a database, to a certain solvency probability68.

A level of significance of 1% will correspond, hypothetically, to a probability of insolvency of the same percentage and to a rating, for example AA, while a significance level of 5% will correspond to an A rating.

Since, from the perspective of the risk-averse economic agents, who seek to give them to economic agents, such as insurers and reinsurers, with tolerance for them, the exchange of risk for insurance coverage aims at reducing risk exposure, those will be particularly attentive to the risk rating of insurers and reinsurers and, thus, to an objective measure of the solvency standard of insurance providers, such as regulatory and economic minimum capital requirements.69

Last but not least, it is important to highlight the advance, especially in the last two decades, of catastrophe risk modeling technology70.

68 About AMBest, BCAR (Best Capital Adequacy Model) and Stochastic Capital Models in the Insurance Industry, see http://www.gccapitalideas.com/2016/10/23/am-best%E2%80%99s-more-transparent-ratings-criteria-provide-benefits-to-insur-ers-that-proactively-%E2%80%9Cown-their-ratings%E2%80%9D/

69 In the case of insurers, these, in the same way, in the cession of risk for reinsurers, will observe the risk classification (and solvency) of those, so that there is a net benefit in terms of capital requirement; in the same way that reinsurers, in retro-cession operations, will have to consider the credit risk (and solvency) of the insurers.

70 Muir-Wood, R. (2009). “[...] before the early 1990s insurers and reinsurers would: (i) Use the concept of the “probable maximum loss◦ PML; (ii) Employ (recent) historical scenarios for looking at “expected losses◦; (iii) Measure their aggregate accumulations in zones. Catastrophe Modelling: (i) Replaced the PML with the exceedance probability EP curve; (ii) Rec-ognised that the next catastrophe will not be a repeat of a historical catastrophe; (iii) Recognised that aggregates can only be managed probabilistically; and (iv) Emerged through the 1990s to become mainstream for how insurers and reinsurers managed catastrophe risk [...] Cannot identify where best to invest in risk reduction, without first understanding the peaks in the „landscape◦ of risk. Cannot identify the best value for money in risk reduction (adaptation) without exploring alter-native mitigative options. Disaster Risk reduction may also have an insurance component to spread risk – example of the Caribbean Catastrophe Risk Insurance Facility; Commercial Cat models are expanding beyond the developed world; Open Source Cat models coming online – in particular for EQ; New models for drought, heatwave. The future of disaster risk reduction will be probabilistic! [...]”


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From an eminently qualitative approach, until the 1990s, the knowledge and application, from the 2000’s, of computational tools, together with the evolution of technologies for collecting and extracting data and information on environmental risks, allowed the development of loss estimation models for risk contingent events quite technically robust71,72.

Figure 3, below, illustrates the evolution of international technical knowledge, since the 1990s, in the modeling of risks of environmental catastrophes:

71 http://www.gccapitalideas.com/2016/09/22/increasing-confidence-and-transparency-in-your-catastrophe-risk-deci-sions-part-i/. “[...] Catastrophe models have evolved significantly since they were first introduced in the 1980s. They now cover most natural and some man-made perils in countries around the globe, both in developed insurance markets and emerging markets. The proliferation of data sources and improvement in risk-defining exposure data reporting and an un-derstanding of the underlying science and physical processes has enabled the creation of more sophisticated and detailed models. Their ubiquitous use throughout the industry has led to a greater dependence on catastrophe models for risk se-lection and management decisions. It follows then that there is a greater need for everyone from analysts, underwriters and risk managers to members of the C-suite, to understand the models - both for what they do well and where improvements could be realized [...]”.

72 http://www.gccapitalideas.com/2016/09/22/increasing-confidence-and-transparency-in-your-catastrophe-risk-deci-sions-part-i/. “[...] Catastrophe models have evolved significantly since they were first introduced in the 1980s. They now cover most natural and some man-made perils in countries around the globe, both in developed insurance markets and emerging markets. The proliferation of data sources and improvement in risk-defining exposure data reporting and an un-derstanding of the underlying science and physical processes has enabled the creation of more sophisticated and detailed models. Their ubiquitous use throughout the industry has led to a greater dependence on catastrophe models for risk se-lection and management decisions. It follows then that there is a greater need for everyone from analysts, underwriters and risk managers to members of the C-suite, to understand the models - both for what they do well and where improvements could be realized [...]”.

Source: Swiss RE. Natural Catastrophes – The Swiss RE Approach. April 2014.

Figure 3Evolution of Catastrophe Models


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These models are, essentially, based on the same statistical logic that permeates the calculation of capital, being data and information translated in terms of vulnerability, probabilities of occurrence, impact and losses, including their volatility and correlation, when they materialize73.

Figures 4 and 5, below, highlight some distinguishing features of the rational present in the catastrophe models.

Source: Morrison, D. (2012).

Figure 4Basic Elements of Catastrophe

Modeling

Figure 5Advantages of Catastrophic

Models

Source: Swiss RE. Natural Catastrophes – The Swiss RE Approach. April 2014

73 Guy Carpenter (2015): “[...] Catastrophe Modeling: the insurance industry relies to a large extent on catastrophe models to manage catastrophe risk. regulators and rating agencies recognize this fact by asking companies to justify their modeling approach [...] the underlying objective of such rules is to encourage companies to have a robust and consistent process to use modeling tools responsibly [...] this often entails: understanding the models and their uncertainty; validating the tools they adopt and invalidating the ones they choose not to adopt; Justifying any adjustments and variations made to com-mercially available models [...].”

GUY CARPENTER 36May 25, 2012

ModelsAdvantages

• Minimizes reliance on historical data

– Adding an additional historical event to a small historical database can provide

broad fluctuations in results

– Historical results are not representative of future events in many areas

– Exposures change over time (property values, population movement, building

codes and construction techniques, topography, etc.)

• Uses probabilistic distributions to properly address

– Low frequency but high severity events

– Geographical distributions of events

• Probabilistic distributions provide for robustness in the tail

– Compensate for little historical data

– Should this be influenced by future activity?

• Process large volumes of data and complex calculations quickly


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Figure 7, below, highlights the main foundations underlying the probabilistic modeling of disaster risks:

Figure 7Fundamentals of Stochastic Modeling

Source: Kumar, D. (2012).

Figure 6loss Frequency Curve

Source: Kumar, D. (2012).

Such analytical elements are synthesized in curves known as Exceedance Loss Curves (also known as Loss Frequency Curves).

Figure 6, below, illustrates a generic Exceedance Probability / Loss Frequency curve:


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74 Excellent references to the evolution and state of the art of catastrophe risk estimation models can be found in Muir-Wod, R. (2009), Swiss RE (2014), Morrison, D. (2012) e Kumar, D. (2012).

75 Also known as XL and, specifically, for catastrophic risks, as Cat XL.

Loss Frequency curves, based on constant similar events from a geographically and temporally extensive basis of data for a given hazard, such as a hurricane and a flood, in a given region with a given population density and constructional pattern, allow the supply of maximum estimated losses, with a given probability, in the occurrence of a risk event74.

No less relevant, the extractable risk parameters of these curves are, as can be inferred, proxies for the basic risk components (PRM, LGM and EAR) of the VaR equation and its corresponding regulatory and economic capital requirement.

These basic parameters will also typically be used by reinsurers in the provision of coverage to insurers, in the non-proportional cession of large risks via Excess of Loss (XoL)75.

In section 3, below, we will approach as insurers and reinsurers, based on the conceptual structure presented here, apply classic strategies of risk retention and sharing, adapting them to the specific requirements of large risks.

From the previous sections, we have drawn the conclusion that environmental risks require, in order to be underwritten and retained by insurers and reinsurers, the observance of properties that differentiate them from ordinary risks, being the critical variable of the equation the adoption of sustainability strategies subject to a strong restriction of capital requirement

A first consequence of this objective function and its restriction is that the binomial (indeed, a trade-off, as we have seen), affordability and insurability may not apply, resulting in the potential for a market failure in this market segment.

We have seen that the failure may be covered by insurance products offered by public vehicles and/or by solutions designed by the non (re)insurer capital market.

3. Risk Retention and Transfer strategies in Insurance and Reinsurance in light of Environmental Risks


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And that the surplus of coverage in relation to the total insurable losses is absorbed, ex post catastrophes, by society, through governmental-sponsored entities.

A first outcome of the market failure is the existence of Uninsurable Risks (RNS) and Non-Manageable Risks (RNG).

Generally speaking, RNS refer to risks that would typically be attributable to the insurance and reinsurance market as a layer of risk absorption for which risk-averse economic agents demand transfer (i.e., risk transfer to economic agents that are tolerant to it, such as insurance and reinsurance companies, as we also discussed).

Environmental risks are included in the subset of large risks that, as discussed in section 1, violate the typical insurable properties of ordinary risks, which results that this subset objectively exemplifies the existence of RNS.

These are the declinable risks (coverage exclusions), which are, essentially, associated with the restriction of capital related to the restriction of the applicability of the LLN.

The RNS materialize, for example, in an engineering work, by the additions to CAPEX due to risks incurred during the pre-completion phase, for which there is no coverage offered by insurers in general, under market conditions, due to lack of appetite and/or risk capacity/tolerance.

RNG are risks that, typically, are excluded from the scope of the insurance market, and are, by definition, attributable to governmental bodies, mainly regarding the indemnification of losses and economic and financial rebalancing of contracts entered into between private entities with the public concessionary power, by the materialization of risks entailed, by the latter, of its responsibility, therefore.

For example, infrastructure investment projects incur non-manageable risks (RNG), which represent increases in investment values (CAPEX) and/or delays in projects incurred in a given work, due to unforeseeable circumstances or force majeure (for example, for the delay in the issuance, by public agency, of environmental and construction licenses). Or because of a natural disaster.

Such risks are typically attributable, in the concession contracts, to the granting power, being the originators of claims for economic-financial rebalancing.

Non-manageable risks can be modeled (by analogy, as we will see in the case of Cat Bonds) as an emulation of credit risk methodology,


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but having, alternatively, as a triggering event, the occurrence of political/regulatory (force majeure) risks and natural facts that affect the fulfillment of the contractual obligations of concession contracts in the pre-completion phase (before the start-up).

This approach is based on the premise that non-manageable risks capture the sector’s regulatory risk.

But what would be the strategies and tools used by the insurance and reinsurance market to retain environmental risks and which, we already know, do not account for their complete absorption by the industry, since we have already anticipated, (based on the conceptual framework and the empirical evidence of statistics), the existence of a market failure, as measured by the environmental protection gap?

It is not the objective of this chapter to exhaustively discuss the classic strategies of risk sharing in the insurance market, but briefly, typically employed possibilities based on the international experience of the market in centuries of this activity will be discussed, in order to contextualize its applicability to environmental risks76.

Firstly, there is a need to distinguish between coverage structures where there is a “horizontal” sharing of risk (for example, coinsurance, where risk-takers are exposed pari passu to a third party, that is, without seniority or subordination) from “vertical” structures, such as reinsurance (where an insurer is exposed to the risk of a reinsurer and the reinsurer, to the risk of a third party).

Second, there is a need to distinguish between proportional structures of sharing/transfer of risk, and those that are not proportional.

It can be said that, typically, environmental risks, in which the insurance and reinsurance market have the appetite and capacity (tolerance) to retain them (that is, at the lower limit of the market failure given by the imperfect conformation to the properties of affordability and insurability of ordinary risks) are absorbed by reinsurance, according to non-proportional structures, the most common being the Excess of Loss (XoL) modality.

But how, before anything, does a proportional structure of risk-sharing work?

76 For an exhaustive review of the most common insurance, coinsurance and reinsurance modalities, see Munich RE (2010) and Fundación Mapfre (2013).


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In this type of modality, the transferee (for example, a reinsurer) of the risks provided by a particular economic agent (an insurer) absorbs the responsibility for the coverage of a certain risk in proportion to the premiums that were assigned to it.

This is typically the case in coinsurance and reinsurance operations in the ordinary risk sector.

The difference between coinsurance and reinsurance is that, in the first case, two or more economic agents (insurers) share a certain risk, at a predetermined proportion, on equal terms with that risk (that is, without seniority or subordination), considering the proportion.

In the case of reinsurance, an economic agent (insurer) assigns the risk to another economic agent (the reinsurer) so that, for the part transferred, the insurer becomes subject to the risk (of credit) of the reinsurer77.

That is, in the coinsurance, the original cedent of the risk is exposed only to the risk initially underwritten, now in a smaller proportion.

In reinsurance, the original cedent of the risk is exposed to two distinct risk environments, namely, the risk initially underwritten (in the portion that was retained); and that of the reinsurer (in the complement that was ceded).

In ordinary risks, coinsurance and reinsurance contracts will typically be proportionally signed, and the choice of one modality or another for risk cession will essentially depend on the appetite and capacity (tolerance) of retention of risks by the co-insurers initially, which, we know, will be related to the required capital intensity for the underwriting78.

From a perspective focused on risk assessment and capital requirements, coinsurance would be a less capital intensive choice, so that in the case of large risks, the feasibility of structuring a coinsurance package is now a function of the mobilization capacity of as many economic agents as necessary for the fractionation of a risk retention in line with the market’s absorption (or capital) capacity.

The exhaustion of the availability in the insurance market, at a given time and region, to offer retention capacity through proportional

77 In the composition of its economic and regulatory capital, the insurer, with reinsurance, will be reducing the share of cap-ital associated with the underwriting risk that was assigned; and should include capital corresponding to the credit risk, as it is exposed to the reinsurer, in the portion assigned to the risk.

78 We are restricting ourselves here to the aspects purely associated with risk in the definition of the strategy of hiring protec-tion. Obviously, such strategic decisions are also (very) determined by commercial and institutional issues in the insurance market.


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risk cession structures, considering the nature of the risks to be insured (such as ordinary risks or large risks), guides the strategic decision of the choice of the modality towards designs that involve greater intensity (and capacity of risk retention) of capital requirements.

Reinsurance has historically been the next step in the decision-making process. For ordinary risks, reinsurance solutions remain typically proportional.

On the other hand, in large risks, the most typical structure is the one of Excess of Loss (XoL or Cat XL, in the specific case of catastrophic risks).

XoL is a non-proportional contract between an insurer and a reinsurer79 in which, for a particular risk where the LLN does not apply (for example, where there are significant elements of concentration risks and, hence, extreme losses), a “cut-off point” (the so-called attachment point) is predefined, from which the insurer’s liability ends and the reinsurer’s liability for a particular risk is initiated80.

79 Typically, in ordinary risks, a contract between insurer and reinsurer is automatic (a Treaty), comprising a certain portfolio and not being able to refuse indemnification, by the term of validity. In the case of large risks, such as environmental ones, contracts are said to be optional, that is, they are ad hoc contracts, to cover a certain individual risk. See Munich RE (2010) and Fondación Mapfre (2013).

80 An XoL contract, although it may be of the automatic type (a Treaty, in the terminology of reinsurance), will usually be structured in the case of environmental risks, depending on the profile of the risks and capital requirements, in the optional case (case by case).

Figure 8Structure of an Xol

Source: Morrison, D. (2012).


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Thus, it is said that a given agent (for example, a reinsurer) will absorb x$ in excess of y$, that is, up to the limit of losses given by y$ the risk cedent will absorb the losses, being x$ above y$ on behalf of the transferee (for example, a reinsurer).

Based on the above characteristics, the reader will have already imagined that one of the risks typically addressed by XoL structures is environmental risks. Correct inference: environmental risks fit the profile of this design.

As we saw in section 2, this cut-off point will be directly related to a loss distribution (Loss Frequency or Exceedance Curve), obtained from a catastrophe model.

This curve allows for determination of the percentages of loss associated with a cumulative distribution of probabilities.

In the negotiation of a Facultative XoL for a certain environmental risk that it is intended to cover, an insurer and a reinsurer (or, which is also common in large risks, a consortium of insurers and reinsurers, each participant choosing a layer of the structure) will determine, on the basis of the nature of the risks, the total amount of capital required and the retention capacity (capital and tolerance) of each participant in the structure, the share of risk attributable to each one.

The definition of the risk to be retained by each participant will be, essentially, a pair, given by the cumulative probability and the loss associated with each probability level.

It is worth mentioning that the logic of an XoL structure is strongly similar to that of the VaR, each attachment point of loss can be interpreted as corresponding to a level of significance.

As the risk (in)tolerance, on the risks with the environmental properties, is associated with the capital intensity required to absorb high value and low probability losses, typically at higher attachment point levels (that is, of losses, in value) will correspond to probabilities in the tail of the distribution of losses, resulting in some logical inferences about the rationality of a reinsurance program built with an XoL structure. Let’s see.

On a Loss Frequency curve, the area under the curve up to the expected loss (EL) plus the insurer’s risk tolerance (given by a number of standard deviations from EL), represents the value of the risk premium retained by the cedent of risk.


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The area between the retention limit of the insurer and the risk tolerance of the transferee (the reinsurer), which will be demarcated by the level of significance of the VaR, may be a measure of the volume of premiums ceded to the reinsurer, which absorbed the loss layer above the insurer’s tolerance level. Mathematically, the areas correspond to the integral of the curves.

Source: Muir-Wood (2009)

The effectiveness of a structure (also called a program) of reinsurance for large risks based on the XoL modality is even greater when it is observed that, typically, risk absorption (retention) will be carried out through a consortium of reinsurers, each choosing a risk retention layer compatible with their capacity (capital).

Thus, by the slicing mechanism, in layers, of the risk, the capital restriction associated with the non-compliance with the basic properties of ordinary risks is circumvented.

As we know, the benefit of diversification, given the prevalence of concentration risk (such as exposure to high risks and/or small correlated risks) is not applied for large risks – which would allow for the retention of high risks by a few insurers.

Moreover, a proportional cession of those risks is not economically efficient for the cedent, in view of the low frequency of events, resulting in a greater rationality of the transfer taking place disproportionately.

If the cession had a very low probability as attachment point, then the cedent would probably be transferring revenue to the reinsurer, beyond a reasonable calculation of losses.

The transferee would have revenues with risk premiums beyond what would be reasonable by the nature of the environmental risks,

Exceedance Probability (EP) Output


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appropriating a surplus between (frequent) premiums and (infrequent) indemnities.

In other words, in the case of ordinary risk insurance, the use of Expected Loss is an effective risk-sharing criterion due to the low dispersion of losses around the average.

The proportional cession of risks implies that there is no asymmetry between retention and capital when comparing co-insurers or insurers and reinsurers.

The asymmetry of the losses, in their distribution in the large risks, implies that a non-proportional division of such risks is economically more fair, the layers of greater frequency and lower value being absorbed by the insurer.

That is, the structure of a reinsurance program in XoL defines a subset of the large risks, at this distribution layer (for example, higher probability and lower impact), with closer properties to those of ordinary risks.

Risks, in this case, are essentially absorbed against the retention of premiums, as in the ordinary risks.

On the other hand, the lower-frequency and higher-impact layers are transferred to the more capital-intensive economic agents (typically, reinsurers).

But what determines, in the first place, the choice between retention and cession of risks? That is, what determines the choice of a certain level of significance, in the Loss Frequency Curve, above which the risk is not retained?

What is the objective element that involves a strategy of accepting or not a risk by an insurer or reinsurer?

We have discussed this issue from the point of view of capital requirement as a key variable for measuring risk tolerance and guaranteeing the sustainability of the solvency of these economic agents over time.

However, capital provides understanding for only a part of the choice of the rational underlying retention and cession of risks. What would be the additional element for completing this logic? Let’s talk about RAROC.

RAROC (Risk-Adjusted Return on Capital) is the metric that combines tolerance and risk appetite.


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In the specific case of insurers and reinsurers, this metric is of particular importance because the focus of their managers’ performance measurement is typically focused on non-risk adjusted measures, such as the Loss Ratio, the Combined Ratio and the ROE.

Each of these measures, taken apart, says nothing about the financial effectiveness of management.

In the case of the Loss Ratio, it is only a measure of the profitability of the premiums.

The Extended Combined Ratio adds to this measure the contribution of the financial investment of reserves and administrative and operational costs.

And ROE, although it compares results with Net worth, does not capture risk (the capital requirement).

It is not uncommon for insurers and reinsurers to present positive figures for these measures and, if a large risk (of small probability, but high impact) materializes, they may face bankruptcy.

Why? Because they did not have an amount of capital compatible with the retained risk.

The application of RAROC allows the risk manager to map, stochastically, the adequacy of the capital structure to the standard of underwriting and retention of risks (which defines the expected revenues of the economic agent).

Capital in excess in relation to retained risks may result in a reduction in RAROC, that is, destruction of shareholders value. The prescription, in this case, is:

- to reduce capital; or

- to retain more risk.

Lack of capital may determine potential solvency shortfall in the face of unexpected losses. The strategic prescription in this case is:

- to increase capital; or

- to transfer risk.


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Capital calibration is one of the most strategic components in the modern management of financial institutions, such as banks and insurance/reinsurance companies.

In the case of large risks, the asymmetry of the distribution of losses associated with the low frequency and high impact properties implies that a proportional redistribution of risk would benefit the transferees (as in the case of reinsurers), since the highest impact losses are significantly higher than the average of the losses (which would imply in a higher probability of receiving risk premiums and not being triggered for indemnities).

Returning to the Cat XL Facultative model, these are the structures that, in the chain of capital intensity of the insurance market, represent the limit of the capacity to absorb large risks, such as environmental risks.

The process of risk underwriting in this modality will be closely associated with a RAROC assessment by the transferee.

The target for RAROC will typically be that one given by the industry benchmark, over a given period of time and geographic region.

Considering, at a given point in time, the profile of environmental risks (their occurrence and impact), a given capacity (capital and tolerance) of the insurance and reinsurance market in a given geographic region (a local market) and the ability to transfer (and absorb) these risks by

diagram 1, below, illustrates the concept of RAROC:

Source: Morandi, A. (2010)


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the international market, the exhaustion of the insurance capacity of the Facultative Cat XL Contracts defines the beginning of the market failure of the insurance and reinsurance market to address these risks.

Typically, as we have also discussed in previous sections, the risk layer not absorbed by the insurance market has historically been occupied by the provision of insurance by public vehicles (via funds and pools of government resources).

We have also seen that this government action, in many cases, provides asymmetric incentives in the form of an offer of insurance with non-adjusted pricing to risk and without foundations on ex-ante regulation that encourages greater resiliency and prudence (internalizing costs) of risk-averse agents (which may, on the contrary, encourage opportunistic behavior, risk appetite, depending on the guarantee of the coverage offered by the public insurance and/or certainty of compensation for ex post damages).

Such incentive asymmetry can occur, in addition to the regulatory (ex-ante) route, through asymmetric arbitration of justice (ex post).

In both cases, asymmetric incentives may result in non-prudential behavior of economic agents, ex ante.

Or by the expectation of punishment not proportional to the loss, in the case of judicial arbitration of the conflict, that is, as a polluting agent that, because of the value of the loss for society is astronomical, claims to have no financial capacity to repair the damage (judgment proof & liability rules)81.

That is, a public action, in the market failure, with inadequate incentives can lead to an increase of the market failure itself, which entails the phenomenon of crowding out by the State.

But would there be an alternative in the market to reduce the market failure otherwise filled by the State in the provision of insurance and reinsurance solutions for large risks?

The existence of such a layer, without detriment to society’s efforts to improve governance standards and reduce the asymmetries that today imply that government failures may be expanding rather than reducing market failure, would lead to the possibility of more efficient public resources allocation, ex ante and ex post catastrophes82.

81 See Monti, A. (2002).

82 OECD & The Geneva Association (2015). “[...](Re)insurance and capital markets play a critical role in the financial man-agement of disaster risks by absorbing the costs of damage and losses and supporting post-disaster economic recovery


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In the segment of coverage of large risks (Cat XL), in the evolution of financial markets and risk transfer instruments, vehicles have been developed over the last decades designed to address the issue, in which properties of large risks match the risk profile (appetite and tolerance) of the non-insurer capital market.

An example of such financial vehicles developed in the capital market for risk transfer outside the typical structure of insurance and reinsurance contracts are Cat Bonds (Catastrophe Bonds).

Cat Bonds are a particular case of the ILS (Insured-Linked Securities), that is, titles linked to insurance (also known as parametrized or indexed), providers of what is also referred to as “alternative capacity” (for example, of capital and of risk retention), in addition to that of the insurance and reinsurance market, thus reducing the market failure.83

by providing a source of funds for recovery and reconstruction. Countries with mature insurance markets recover much faster and more efficiently when struck by a disaster. When properly designed, insurance can also contribute to adapta-tion by reducing the overall losses from climate change related extreme events through the use of risk-based premiums, deductibles and premium discounts that encourage risk reduction. The insurance sector can also play a strong advocacy role in encouraging preventive measures such as land-use policies and building codes that improve resilience against the impacts of disaster events. This session explored the impact of climate change on the insurance sector from the perspective of direct insurance and reinsurance companies as well as the catastrophe modelling firms and actuaries that support the quantification of disaster risks. There is general agreement that climate change is occurring and leading to more significant losses. In Japan, for example, previously uncommon events such as winter storms, tornadoes and hailstorms have begun to emerge more frequently. The Inter-Governmental Panel on Climate Change’s (IPCC) special report on extreme events provided strong evidence of an increase in heat waves and a rise in sea level. New global temperature records are being set every year and the world has already reached a 1°C temperature rise over the pre-industrial era (50 per cent of the ceiling established by governments). A critical risk in terms of the occurrence of extreme events is warmer water, which leads to increased evaporation and fuels convective storms and cyclones and more intense precipitation events. The increased availability of data and improvements in scientific understanding have allowed for better forward predictions on weather activity with modelling firms now able to provide estimates of activity looking forward five years. The actuarial industry is also devoting increasing attention to the measurement of climate change, for example, with the development of a climate change index in North America. The insurance sector—as one of the sectors most impacted by climate change—has been examining these issues for many years. However, the expertise and capacity of the insurance sector has been underutilized. Only 30 per cent of total economic losses have been insured (with the proportion even lower in emerging markets). Insur-ance companies need to continue to work on designing products for lower-income clients, including products that lower administration, claims adjustment and distribution costs. The sector also needs to take the risk of investing in immature markets as a future opportunity for growth. While a significant “financial protection gap” remains for privately owned as-sets, the gap is even more significant for public sector assets and liabilities. Insurance companies need to invest significantly in raising awareness of the benefits of financial protection for governments. Progress has been made in a number of coun-tries, particularly where public-private partnerships have been established to address insurance supply and demand issues (e.g. Turkish Catastrophe Insurance Facility, Flood Re, etc.). In Germany, efforts by the insurance industry to raise awareness about flood risks —combined with a government commitment to not provide compensation for insurable damage—has led to a significant increase in insurance coverage for flood risk. A number of countries, including Mexico and countries in Africa and the Caribbean have also sought financial protection for public assets and liabilities. International fora such as the Asia Pacific Economic Cooperation (APEC) have also placed increasing attention on the financial management of disaster risks. In the context of increasing risk from climate change, the insurance sector also needs to play a more active role in providing advice on land-use planning, building codes and prevention measures—helping society manage risk using a forward-looking perspective. The sector also needs to get ahead of the potential for significant liability risks as litigation around climate change causation develops [...].”

83 http://www3.asiainsurancereview.com/Magazine/Magazine-Articles/mgid/323/cid/3. [...] Alternative capacity (AC) has grown strongly in the past decade, boosted by favorable circumstances: low catastrophe activity of recent years leading to attractive margins and comparatively low returns in other asset classes. After years of rapid expansion, AC and its global market share in the property catastrophe segment have largely stabilized in 2015/16. Estimates suggested that


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ILS are financial instruments developed in the capital market due to the market’s appetite for assets with a low or negative correlation with other fixed income and variable income assets, more typically present in their investment portfolios84.

These assets add diversification benefits to investment portfolios, in order to optimize their risk-return.

Typically, ILS are financial instruments structured in a parametric way, with remuneration and redemption (or triggering, as collateral to risks covered by them) due to the linkage to risk events whose materialization is regulated in an insurance contract.

AC accounts for around 16% of today’s global CAT XL market and 23% of the US market (excluding retrocessions). The inflow of new money is slowing as AC funds are also struggling to find attractive opportunities in the current soft market. At the same time, there are indications that the market has become more mature and sophisticated. Over the years, the investor base has broadened and many investors have recognized the attractiveness of catastrophe bonds as a truly diversifying asset class. New financial market technologies and modelling tools, as well as increased competition among various service providers, have resulted in reduced frictional expenses associated with issuing a catastrophe bond. Investors have also become more comfortable with indemnity-based triggers or structures. To date, alternative capital is mostly focusing on US property CAT risks, which accounts for approximately US$10 billion of premiums. This segment is short-tail in nature, fairly transparent with regards to the provided insurance cover, supported by a number of vendor risk models, and has low entry barriers. The rise of strategic reinsurance. Alternative capital is not well suited for the great majority of reinsured risks which are not peak risks, not supported by risk models and are long-tail business. The higher complexity of underwriting non-CAT risks and the cost of collateralizing makes AC uncompetitive in comparison with traditional reinsurance. This is particularly the case in Asia where traditional capacity remains abundant due to keen participation by both international and regional reinsurers. AC is short-term (except for multi-year ILS), opportunistic and transactional. By contrast, reinsurance programmes are increasingly customized to help insurers optimize their capital structure, improve capital returns and minimize capital costs. More often, reinsurance is integrated into insurers’ long-term strategy and growth plans. These structures are complex and often result from long-term relationships. The demand for structured and more strategically motivated (re)insurance programmes is growing across the region. The rationale for the use of such solutions has evolved into three broader motivation areas.1. Increasing the efficiency of risk transfer Structured (re)insurance programmes can increase the efficiency of risk transfer by combining multiple risks and/or interdependent triggers. As part of a more integrated risk management process, risk transfer is focused on the joint distribution of all risks, helping to expand the insurability of difficult-to-insure risks; 2. Optimizing capital structure, reducing cost-of-capital and improving capital efficiency. Reinsurance can also be used for corporate finance purposes, that is, to address capital management issues. Corporate finance-oriented solutions include non-life retrospective covers and life in-force monetization, with the goal of releasing “trapped” capital and monetizing future expected cash flows on long-term business.3. Enabling strategy and growth. The third motivation for the use of customised solutions is to enable the strategic and long-term growth objectives of a ceding insurer. In the life sector, reinsurance contracts can help an insurer finance the high first-year expenses and negative cash flows associated with the growth of new business. In the non-life insurance sector, support is more focused on flexible, on-demand capital relief and capital efficiency [...] Alternative capacity is here to stay. However, not all AC business models are equally resilient. Collateralized reinsurance, sidecars and hedge fund reinsurance are increasingly deployed in working layers and primary insurance. ILS is applied in higher layers and more based on modelled CAT risk, which is better understood by investors than the business risks of pricing and underwriting quality. CAT bonds have a proven track record through the years of financial market turmoil and record high CAT losses. There also had been few events where bonds were triggered so there is some collective experience for CAT bond investors. AC (particularly CAT bonds) is the main force behind the commoditization of property CAT reinsurance. It will continue to have an impact, although with less momentum, even as reinsurance rates soften further, catastrophe losses increase, and as rising rates make other investments more attractive. However, AC is unlikely to spread significantly beyond peak risk segments. [...]”

84 Artemis (2016,1). “[...] Insurance linked securities, or ILS, are essentially financial instruments which are sold to in-vestors whosevalue is affected by an insured loss event. As such the term insurance linked security encompasses ca-tastrophebonds and other forms of risk linked securitization.Insurance linked securities are generally thought to have lit-tle to no correlation with the wider financial marketsas their value is linked to non financial risks such as natural disas-ters, longevity risk or life insurance mortality.As securities, insurance linked securities can be and are traded among inves-tors and on the secondary market.They allow insurers to offload risk and raise capital, they also allow life insurers to re-lease the value in theirpolicies by packaging them up and issuing them as asset backed notes. [...]”


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Such events regulated by ILS may refer to the variation of parameters related to risks associated with human life (for example, longevity/aging), property (accidents) and nature (intensity of rains and floods), for example.

Cat Bonds are a particular version of ILS linked to the occurrence of catastrophic risks, typically to the unexpected ones, related to natural disasters85.

Natural disasters, as discussed in previous sections, present a vector of risk properties characterized by low frequency and high impact, that is, they typically comprise events located in the tail of the Loss Frequency Curve.

This characteristic, as also discussed in this section, determines that, in the insurance and reinsurance market, the absorption of these risks is typically done in the non-proportional mode called XoL (Excess of Loss) or Cat XL.

The same structure of risk sharing in the insurance market bases the design of the financial instrument by the capital market.

The low probability of occurrence of natural disasters and their low correlation with other risks (that is, low correlation with other financial assets) create attractive conditions for the retention of these risks by the capital market, in the form of an asset investment that emulates a security with a low credit risk.

85 Artemis 2016,2). ”[...] We’re regularly contacted by people asking us ‘What is a catastrophe bond?’ or ‘What is a cat bond?’ so wethought we’d provide a simple primer on the topic. Catastrophe bonds, also called cat bonds, are an exampleof in-surance securitization to create risk linked securities which transfer a specific set of risks (generally catastrophe and nat-ural disaster risks) from an issuer or sponsor to investors. In this way investors take on therisks of a specified catastrophe- or event occuring in return for attractive rates of investment. Should a qualifyingcatastrophe or event occur the inves-tors will lose the principal they invested and the issuer (often insurance orreinsurance companies) will receive that mon-ey to cover their losses.

Catastrophe bonds were first issued in the mid 1990’s, we have a comprehensive database containing the de-tailsof nearly every (over 280) catastrophe bond transaction. Major catastrophe events which hit the U.S. such as-the Northridge eartquake and Hurricane Andrew were seen as events of such magnitude that the insuranceindustry be-gan to look for alternative methods to hedge their risks and through collaboration with capitalmarkets companies catastro-phe bonds were born.

One of the key elements of any catastrophe bond is the terms under which the securities begin to experience aloss. Ca-tastrophe bonds utilise triggers with defined parameters which have to be met to start accumulatinglosses. Only when these spe-cific conditions are met do investors begin to lose their investment. Triggers can bestructured in many ways from a slid-ing scale of actual losses experienced by the issuer (indemnity) to a triggerwhich is activated when industry wide loss-es from an event hit a certain point (industry loss trigger) to an indexof weather or disaster conditions which means actual ca-tastrophe conditions above a certain severity trigger aloss (parametric index trigger).A catastrophe bond can be struc-tured to provide per occurrence cover, so exposure to a single major loss event,or to provide aggregate cover, exposure to mul-tiple events over the course of each annual risk period.Some catastrophe bond transactions work on a multiple loss ap-proach and so are only triggered (or portions ofthe deals are) by second and subsequent events. This means that spon-sors can issue a deal that will only betriggered by a second landfalling hurricane to hit a certain geographical location, for ex-ample [...]”.


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The low probability of occurrence of a natural disaster is, in a Cat Bond, the proxy for the credit risk of the security and, if low, a rating agency could confer an investment grade rating on the instrument based on its expected loss.

A Cat Bond can, therefore, be defined as a fixed income financial instrument with risk spread commanded by the probability of occurrence of a particular catastrophic event to which it is linked86.

But what would be the structure of this instrument?

diagram 2, below, illustrates the design of a Cat Bond:

Diagram 2 - structure of a Cat Bond

Source: Artemis (2016).

The basic model of a Cat Bond initially involves the assignment to a specific purpose vehicle (SPE bankruptcy remote), by an insurer, of a certain well-defined catastrophe risk in terms of its risk parameters (probability, impact, correlation)87.

86 This characteristic implies linking a given Cat Bond issue series to a regional and seasonally defined risk event. Since the recovery, given the loss (LGD - Loss Given Default) is, in this type of risk event, typically null, the rating will be essentially a function of the likelihood of risk materialization (PRM).

87 The link between the structuring of a Cat Bonds issue series and the mapping of its underlying risk by a catastrophic risk modeling tool is clear. These models, in order to reduce informational asymmetry, provide the feasible elements of the calculation of risk necessary for the design of financial instruments in the capital market.


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Such vehicle will acquire the risks from its cedents through the raising of funds from investors in the capital market (institutional investors and investment funds, typically).

These funds will be invested by the SPE in risk-free public securities with characteristics (term, interest payment profile, amortization and redemption) compatible with investors’ appetite and risk tolerance.

Typically, Cat Bonds are structured according to characteristics similar to those of government bonds, with periodic payment of an interest coupon and redemption of the principal at the end (for example, bullet bonds).

The funds invested by the capital market, in SPE, in public securities will be the principal to be redeemed at the end of the term of the security if there is no default (that is, if there is no risk of catastrophe materialization).

If the natural disaster to which a series of Cat Bond issues is linked materializes, the principal invested will be lost by the investor and will be used by the SPE to cover the losses of the insurer that ceded the risk.

The remuneration of the security will be composed by the payment of the coupon of interest of the Government security in which the Cat Bond funding was invested, plus a risk spread, given by the conversion of the ceded upfront premium fee, with the same periodicity of the Treasury coupon.

This structure has the additional advantage of not involving credit risk for the cedent of the risk (as there is, when the cession is made to a (re)insurer), since the resources to be used for a possible future indemnity of a casualty, by Cat Bond issuer SPE and risk coverage provider, are, as explained, pre-deposited in an Escrow Account bankruptcy remote, separated from the balance sheet of the issuer and the issuing SPE, under management by a Trustee.

Another advantage of this model of provision of capacity to the insurance market is the non-submission by the investing agents to minimum capital regulatory requirements, implying - for a same vector of covered risks - less cost and capital for their retention, when the instrument is compared with the conventional alternative of providing protection through the reinsurance market.

Put another way, the provision of protection for environmental risks associated with natural disasters by means of the capital market, structured in fixed income instruments indexed to such risks (Cat Bonds


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of the ILS type), which emulate credit risk by having as proxy the likelihood and impact of natural disasters, is not subject to a particular regulatory solvency and risk tolerance requirement regarding such risks.

The dynamics of the offer of the coverage is, in this case, guided by an assessment of investors’ appetite and tolerance for risk given a correlation calculation with the risk-return profile of financial asset portfolios.

This characteristic, as a trend, implies a potential reduction of market failure, reducing the layer not addressed by the insurance and reinsurance market, and historically occupied by government agencies (through the provision of official insurance); or, in the absence of an insurance solution, by the presence of the governments, via ex post catastrophe relief, with the resources of society.

In the next section, we will discuss how this conceptual framework is translated into the conduct of strategies for retention and cession of large risks from the Brazilian insurance/reinsurance perspective.

The translation of the objective function, of optimization of the risk-return binomial and the parameterization of risk tolerance to an intertemporal solvency requirement of insurance and reinsurance providers, in the form of retention strategies and transfer of large environmental risks, in the light of locally available information and its comparison with international statistics, allows to speculate whether the protection gap in Brazil, as in other emerging countries, is higher than in the more developed countries88,89,90.

4. Retention and Transfer in Major Risks in the Brazilian Market and the Mariana Case

88 Swiss Re. Sigma. Several issues.

89 http://www.gccapitalideas.com/2016/10/24/from-public-to-private/ “[...]The gap between insured losses and total eco-nomic losses remains stubbornly large - Swiss Re estimates that only 30 percent of global catastrophe losses in the ten years prior to 2015 were covered by insurance. Consequently, the remainder of the loss, USD 1.3 trillion, was borne by individuals, firms and governments, and this burden is increasing. Swiss Re estimates uninsured losses more than doubled from 0.08 percent of global gross domestic product (GDP) for the ten years from 1976 through 1985 to 0.17 percent for the years 2006 through 2015. Statistically, this may not appear to be a huge burden on GDP, but averages may not capture the full story and the impact can be substantial. For example, the April 16, 2016, Ecuador earthquake in which more than 650 people died, incurred losses estimated at USD 5 billion with no more than 10 percent covered by insurance. In an effort to finance the cost of recovery, the government of Ecuador increased the sales tax from 12 percent to 14 percent, imposed an immediate one-time wealth tax of 0.9 percent on net worth greater than USD 1 million and a one-time income tax charge of one day’s pay and five days’ pay on monthly incomes of more than USD 1,000 and USD 5,000, respectively. The government increased taxes on corporations and announced the sale of some state-owned assets. The protection gap also occurs in more developed parts of the world. Europe has been hit by several catastrophes this year. Significant events include flooding in southern Germany in May and Paris in June; the destruction of acres of commercial greenhouses and other property damage by hailstones the size of tennis balls in the Netherlands; and the Italian earthquake of August 24.


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In the light of the conceptual framework we discussed in the previous sections, we can answer that, yes, it is a relevant speculation, and the understanding and explanation of the protection gap of environmental risks in Brazil would be associated with a greater relative scarcity of capital from the local insurance/reinsurance market to retain it.

And, always in dialogue with the conceptual framework hitherto presented, this relative scarcity of capacity would be a function of greater informational and regulatory uncertainty.

Munich Re estimates the cost of catastrophe losses from hydrological events alone in Europe in May and June 2016 at USD 5.2 billion, with only 46 percent of loss covered by insurance. In 2011, the German federal government hastily established a state fund of EUR 8 billion to cover the costs of infrastructure and private property flood losses[...]Transferring risk from the public sector to the private sector is an important means of mitigating and reducing the cost of catastrophic losses to public finances. The use of pools and other mechanisms to spread the potential cost of losses to the private sector is well established in Europe with many schemes operating to cover natural catastrophes, terrorism and nuclear risk. Nevertheless, gaps remain and in Europe, the growing severity of the flood peril, driven by climate change, has been a catalyst for new developments. Most notable was the launch of Flood Re in April 2016, a U.K. government scheme that enables insurers to reinsure the flood element of homeowners insurance policies at a fixed reinsurance premium based on the properties’ taxable valuable. It is supported by a small levy on all policies and enables insurers to offer cover on flood-prone properties that ordinarily might be considered uninsurable […] An integrated and coordinated approach to collaboration between the insurance industry, governments and other public bodies is increasingly recognized as an effective method of creating sus-tainable risk-transfer mechanisms. More strategic discussions among governments, non-governmental organizations, the scientific and academic communities and the insurance industry will help to promote better disaster risk management and the implementation of pre-event insurance solutions. The protection gap presents opportunities for the (re)insurance in-dustry far beyond the catastrophe segment. New risks in areas such as technology, science, medicine, climate change, population growth, food security and urbanization offer challenges and provide opportunities for profitable growth. Some of the risks are very complex or were previously little understood, yet today we better understand risk than at any time in history. We have better science, data and analytics, and tools to understand, measure and price risk. Concurrently, signifi-cant market capacity exists due to the inflow of large amounts of capital looking for opportunities to transfer risk [...]”

90 http://www.gccapitalideas.com/2016/03/03/insured-versus-uninsured-loss/: [...] By their nature, uninsured risks are rarely explicitly recognized by the ultimate holders of the risk and are not managed appropriately pre-event. An exacerbating factor around certain uninsured risks stems from the lack of exposure measurement and systematic risk mapping, which could provide insight into risk mitigation and risk financing options. Globally, most funding for hazard mitigation is made available post event, which in turn is coupled with an over-reliance on post-event financing. For example, during the period of 2011-2014 in the United States, the US Federal Emergency Management Agency (FEMA) granted only USD 223 million in pre-disaster mitigation grants compared to USD 3.2 billion in post-disaster grants [...]. Since 2000, globally there has been over USD 1,600 billion in uninsured loss from natural catastrophes (70 percent of total losses) requiring various forms of post-event funding and loss financing or held directly by those impacted [...].In Europe, The European Union Solidarity Fund (EUSF) was established to provide financial assistance to European Union (EU) countries facing major natural disasters. In the 13 years it has been in existence, the EUSF has paid EUR 3.8 billion (Italy and Germany have received 60 percent of that amount) to supplement the countries’ own public expenditures on essential emergency operations. These payments represent 4 percent of the total damage bill and do not include losses to private property, which are assumed to be other-wise insured by private markets. The EUSF encourages risk mitigation but is essentially a post-loss mechanism with finite funding. The exposure beyond the limited financial resources of EUSF, for example, a large event - potentially affecting mul-tiple countries, falls back to the EU countries at a time when their capacity to fund loss is stretched and financial tolerance varies from country to country. A recent study by AIR Worldwide indicates that a one-in-100 year earthquake in California could result in USD 75 billion of damage to residential properties. After accounting for insurance take-up, applying deduct-ibles and insurance limits the corresponding estimated insured damage is only USD 9 billion, meaning 88 percent of the loss would be unfunded [...]. If an individual’s property sustains damage that exceeds the equity in the property (the United States has an average loan-to-value ratio for single family residences that is over 72 percent [...]), that homeowner may simply walk away from his or her home mortgage, shifting the financial burden to lending institutions, primarily the Federal Housing Finance agencies. Without the homeowner to mitigate loss, carry out repairs and continue to make mortgage payments, the ultimate economic loss multiplies. This creates a larger economic problem for the public sector to manage. Despite this exposure to significant loss there is no urgency on the part of public sector entities or lenders to address the matter. As a result, we are left with an environment ripe for greater utilization of private sector monies [...]”.


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As a corollary, still speculatively, we would have, in the Brazilian market, a lower penetration coefficient, in the large risks, than that of the more developed countries; and also a lower rate of retention of the risks originated here.

This is what we are going to discuss next.

Taking as an example the case of Mariana, the largest environmental catastrophe ever occurred in Brazil and assuming, hypothetically, the case as representative of a more general framework, the estimate prepared by reinsurer Terra Brasis for this natural disaster reached economic losses totals of R$ 26 billion, compared to an estimated insured amount of R$ 2.3 billion by the national and foreign insurance and reinsurance market91.

As the estimated insured losses in the Mariana event were, according to the percentages above, in the vicinity of 10% of the projected economic losses, based on them, the local insurance and reinsurance market covered 13% out of 10% of the estimated economic losses for the event, that is, only 1.3% of them (according to Diagram 3, below).

This configuration, characteristic of the biggest environmental disaster that has ever occurred in Brazil, gives rise to a reflection on what we have discussed in the previous sections, regarding the existence of a market failure at the international level in addressing and covering environmental risks.

It also allows, always taking the example, by hypothesis, as representative of the general framework of coverage of environmental risks by the Brazilian insurance and reinsurance market, to establish inquiries about what would be the explanatory facts of the observed differential in metrics such as the protection gap and the coefficient of penetration, when comparing the international and Brazilian statistics for these metrics, regarding environmental risks.

91 Terra Brasis. Special Report. Mariana (2016).


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diagram 3, below, prepared by Terra Brasis, illustrates this observation:92

92 Terra Brasis (2016).

Diagram 3 Risk Coverage and Retention - Mariana disaster

Diagrams 4 and 5, below, also prepared by Terra Brasis, illustrate, for the period 2010-2015, the same flows of coverage, retention and transfer of risks, in the local and foreign markets, applicable to all risks in Brazil.

Diagrams 4 and 5 Risk Coverage and Retention - Brazil 2007-2015


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Source: Terra Brasis Resseguros (May and June, 2016).


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Table 2 below, based on the Swiss-RE reinsurer’s Sigma studies, in the period 2007-2015, allows for the calculation, at the level of geographic regions, of the ratio between total insured and economic losses at large environmental risks arising both from nature and also from human action.93

Table 2Ratio between total Insured Risks and Economic losses -

Environmental Risks (2011-2015)

Year Gap % AL & Caribe Gap % World

2011 10.7 31.2

2012 21.4 41.6

2013 22.2 32.1

2014 28.0 31.6

2015 42.7 40.2

Average 25.0 35.3

Source of primary data: Swiss-RE. Sigma Series – 2012-2016 editions.

Based on data on the protection gap of total insured to economic losses in man-made and natural disasters casualties extracted from the Sigma/Swiss RE series, in the 2011-2015 period presented in Table 2, Latin America & the Caribbean have this ratio around 25%. Worldwide, this ratio stands at 35% in the same period94.

If Mariana (the gap is in the vicinity of 10%, according to Terra Brasis estimates) is representative of the same ratio for the group of environmental risks in Brazil and, as Brazil is (still) the largest economy in Latin America and the Caribbean, the average of the region was downgraded by Brazil, which would imply that the coverage gap in Brazil is even higher in relation to the region, ex-Brazil.

Still, in relation to both LA & the Caribbean and globally, the differential of Brazil’s protection gap seems to be materially relevant.

Finally, Graph 7, prepared by CNseg, highlights the insurance penetration coefficient in Brazil for risks in general and allows the comparison of this coefficient with the international reference and also with its corresponding value for large risks in Brazil95.

93 Swiss-RE. Sigma. Several issues.

94 The protection gap, averaging 10 years until 2015, was around 32% globally (Source: Swiss RE Sigma 01/2016).

95 CNseg (2016).


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An insignificant percentage of local coverage and retention, in the Mariana example, we speculate, results from informational uncertainty (for example, there is no capacity to price the risk, based on probabilistic catastrophe and capital models); and regulatory uncertainty, with consequent insufficient capital to retain this type of risk locally96.

A possible claim that the 1.3% for domestic retention in Mariana would be indicative of local (re) insurance market efficiency in risk management/transfer can alternatively be seen as a way of not facing the above constraints, and to not consider the international dynamics of the sector in the coverage of this type of event97.

96 Environmental Disaster in Mariana and Insurance: Effects and Mitigation http://cpes.org/en/desastre-ambiental-de-mariana-e-o-seguro-efeitos-e-mitigacao-en/11/02/16

“ [...] In addition, environmental insurance is a very new product in Brazil and underwriting risk is hampered by informa-tion asymmetry [...]. “Event took place shortly after the Mariana catastrophe. The conclusion, regarding the asymmetry of information, is in line with the explanatory hypothesis proposed in this chapter.

97 The ongoing regulatory changes at the international level have had an impact in Brazil (for example, absorption of large risk portfolios by global players), intense consolidation in the insurance market and also in the reinsurance market, polari-zed by the increasing pressure for capacity, that is, greater capital requirements to deal with large risks. Consolidation, by generating operational synergies, entails rationalization of the capital base, which corresponds to a RAROC optimization strategy (in the RAROC formula, given the economic and regulatory pressure for more capital, the synergy of consolidation costs imply in an increase on the numerator, and, thus, on the result).

Graph 7penetration Coefficient - Brazil - General Risks and high Risks

Source: CNseg (2016)


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The conceptual framework of insurance microeconomics and environmental risk taxonomy explains how rational agents (the local insurance/reinsurance market) ended up not retaining the environmental risk, in the example of Mariana, transferring it abroad, due to uncertainties of information and regulatory nature that preclude risk pricing and imply a large capital requirement.

Transferring risk is a rational corollary of this vector, bearing in mind the objective of local agents, to maximize returns (by not drawing capital into large risks) and to mitigate the risk of going bankrupt in this type of high-impact event on solvency.

Without value judgement, the explanatory hypothesis of the strategy in light of the conceptual typification of environmental risk seems to be robust.

The big question is: the huge gap in the local market, the absorption of these risks (which is beginning to attract the interest of large international reinsurers, who have bought large risk portfolios of Brazilian banks in the last two years) is, in light of the confirmation of the rational behavior of local agents, economically and socially desirable (which would imply implementing, or not, strategies through regulation to reduce regulatory and information uncertainties)? Lower uncertainty, lower capital requirement, higher local absorption (and income retention).

And, using the same conceptual framework, now referring to a comparison of the insurance penetration rate to GPD and coverage coefficients of economic losses by insurance/reinsurance, could one speculate, given the low local market penetration rates for environmental risks (1.1% for non-life risks, against an average of 5.6% for all risks, in Brazil, in the period 2011-2015, according to CNseg studies98; and 1.5% against 4.4% in the comparison between environmental risks in Brazil and in developed countries)99, whether informational and regulatory uncertainties would be greater here than in developed markets?100

In time, still on the subject of the relatively low absorption of environmental risks by the local insurance and reinsurance market (always taking the Mariana disaster as a hypothetical benchmark of this segment, which, of course, deserves to be further studied): if only 1.3% of estimated economic losses were absorbed in Brazil and only 10% were absorbed/insured here or offshore, then 90% of the economic losses were left uncovered. As a result:

98 CNseg (2016).

99 See chart 4 presented in the Introduction, taking the USA and non-life risks as a reference

100 CNSP statistical studies.


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- a flow of income leaked outward, by not retaining the risk in Brazil (which is economically arguable); and

- the Brazilian state (or society as a whole) paid for (or will pay for), in this case and possibly in other cases, 90% of economic losses (which is socioeconomically inefficient).

That is, the rational response of the local market to the restrictions that govern the game (informational & regulatory uncertainties and capital limitation) generates a negative economic NPV (Net Present Value) for society, and as a result, it is pertinent to understand the phenomenon and to ponder on regulatory incentives aimed at the reduction of the protection gap.

In terms of international evidence and comparisons, it would be important to obtain data on the percentage retained in other Latin American countries (for example, in Chile). If they were superior to those of Brazil, it would be a reinforcement for this argument. However, we could not find this information sufficiently broken down across different countries.101

Let us highlight some additional elements in this kaleidoscope:

- in the Sigma/Swiss RE studies, in the 2011-2015 period, the insured/economic losses metric in the Latin American and Caribbean region is significantly higher than the same ratio in Mariana;

- rational agents, in our understanding, based on the translation of the conceptual framework into a strategy of optimization of results by the local market, adjusted the retention of risk to the constraints of their risk-return and solvency utility functions; and

- there is recognition that local retention of environmental risks is in-deed low, but causes are not discussed based on a conceptual frame-work, nor is it reflected in strategies to establish regulatory incentives to reduce the local market gap. It is understood that this framework is “natural”, with ensuing non-economic benefits.

101 According to Sigma (Nº 05/2016), in 2014 Chile achieved a penetration rate to GDP of 1.43% with respect to P&C (which is roughly close to Brazil´s 1.38%, as one can infer from the same study). However, the research does not provide detailed data enough on the insured/total losses protection gap ratio (though a measure of this gap for natural catastrophes, in nominal terms and also in relation to the GDP, is available for a group of countries), so that a more accurate comparison could be made. Preliminary estimates on the basis of available information in the same report indicate that, even though Chile and Brazil share comparable penetration rates, their corresponding protection gaps are materially different. On one hand, Chile’s lower protection gap is followed by a higher percentage of the gap in relation to GDP (which is quite lower than Brazil´s), and also a higher ratio of insured losses to GDP (equal or even higher than that regarding countries with higher penetration rates); while on the other hand, the higher protection gap in Brazil is tracked by a lower ratio of this gap with respect to GDP (which is quite higher than Chile’s), as well as by a lower ratio of insured losses to GDP (materially lower than Chile’s and also in respect of countries that post higher penetration rates).


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However, the net social-economic cost of the environmental risk protection gap, based on the analysis and comparison of available local statistics (with Mariana as a base), with those produced internationally, seems to be evident.

One solution suggested by representatives of the (re)insurance market, is to make environmental insurance compulsory.

In light of our conceptual framework, nothing changing in the other restrictions of informational and regulatory uncertainty, the restriction of capital due to the mandatory nature would generate:

- an increase in the flow of premiums transferred abroad; and

- an increased market failure, as not even the international market has the appetite and tolerance to cover the whole risk (it covers, as we have seen, always based on Mariana’s exercise, 90% of 10% of eco-nomic losses).

The requirement would possibly create a market for a state insurer, since the private sector could not be required to provide insurance and reinsurance if it is unable to do so.

Is this a socioeconomically better design than reducing market failure through regulatory incentives that reduce uncertainty and capitalization constraints?

That is, the obligation of environmental insurance, while maintaining the other restrictions of the problem, could not lead to a reduction of market failure, but rather (we speculate) to its preemption by a government-sponsored insurance provider vehicle. The implications and risks of such a strategy involve challenges that have been well explored throughout this chapter.

Based on the discussion presented in the previous sections, we can synthesize the main findings that we have arrived at:

- environmental risks do not fit into the typical properties of the so-called insurable risks, the non-applicability of the Law of Large Numbers and the consequent non-effectiveness of restrictive diversification strategies implying a high capital requirement for their retention;

5. Conclusions and Recommendations


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- the non-compliance of environmental risks with the logic of ordinary risks is associated with the prevalence of factors related, in a synthetic way, to concentration risk, its basic constituent elements being uncertainty (informational and regulatory), volatility and risk correlation;

- this non-compliance leads to a failure of the insurance and reinsurance market, addressed by vehicles providing public insurance and, to a lesser extent, by insurance and reinsurance products based on financial instruments developed by the non-insurer capital market (Insurance-Linked Securities and Cat-Bonds);

- the standard of allocation (retention and transfer) of environmental risks in and out of the insurer/reinsurer market, in our understanding, will be a function of the greater or lesser capital (in)sufficiency to absorb them, the capital variable (solvency) being the critical factor to explain the strategies of economic agents with tolerance to these risks;

- also explaining risk retention and cession strategies, as a vector of capital linkage with the returns of the economic agents of the insurance market, is the target of RAROC optimization for the shareholders of these agents, subject to capital restriction in context of imperfectly diversifiable (environmental) risks;

- imperfect addressing of the market failure by government bodies may accentuate it through unadjusted pricing of public insurance products and/or the moral hazard associated with the provision of ex post public disaster relief and/or ex ante imperfect regulation regarding the planning and prevention of natural and man-made disasters (the concept of resilience, such as building codes and risk-adjusted urban zoning).

- the existence of an absorption layer of large risks by the non-insurer/reinsurer capital market, which is not economically and regulatory guided by the solvency requirement and has an appetite for its retention, since a beneficial diversification effect is applied with risks not associated with environmental risks, gradually appears as an alternative and prior buffer to the governmental insurance coverage layer (reducing market failure); and also as an instrument of mitigation and reduction of governmental action as a vector of the apportionment of society’s losses ex post disasters;

- In Brazil, the protection gap of environmental risks is significant, in light of the available information and in light of the explanatory risk factors (we speculate) of a larger relative capital deficit in relation to


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the developed countries and also in comparison with Latin America and the Caribbean.

As a result of the mapping of the explanatory risk factors of the environmental risk protection gap, we highlight two reflections of international experience as sound advice, aiming at the evaluation and formulation of public policies intended to reduce the gap in Brazil:

Monti, A. (2012):

“Compulsory environmental liability insurance?In light of these considerations, a system of mandatory pollution insurance - at least for those activities that are particularly dangerous for the environment - would seem a desirable solution. Even this conclusion, nevertheless, turns out to be rather problematic. A system of compulsory insurance can be bilateral or unilateral. In the former case, the firm has the obligation to buy coverage in order to be allowed to operate and the insurance industry has the obligation to provide coverage at pre-determined conditions to each and every applicant. Bilateral mandatory pollution insurance, however, is incompatible with the very nature of modern environmental insurance techniques. As mentioned, environmental policies are tailor-made and site-specific and not every plant necessarily has all those characteristics that make it insurable. Standard conditions set by legislature and applicable to every insured, moreover, would drag pollution insurance back to the traditional insurance scheme, which has proved to be highly inappropriate in this context. As long as unilateral mandatory insurance is concerned, purchase of pollution coverage is still a condition to operate for the firms, but insurers do not have any obligation and they may, therefore, refuse coverage to anyone at their own discretion. In this latter case, the incentive mechanism embedded in modern environmental insurance would be able to work properly, but the insurance industry would be placed in the uncomfortable and inappropriate position of environmental policeman. In fact, the insurer would be entrusted with the power to decide which firms can continue their activity and which should instead withdraw from the market. This is a policy choice that the authority has to make.[...]”


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Nguyen, T. (2013):

“[...] In this contribution, we discuss the concepts of insurability and explore the potential reasons for lack of insurance, specifically for extreme events such as catastrophic environmental risks. Furthermore, we analyze the circumstances where a state’s participation in insurance solutions can be justified. We found that in some extreme situations the government should give state guarantees or participate in private-state insurance solutions in order to avoid a collapse of insurance markets. But state risk sharing must not be used to subsidize certain enterprises or branches. This would lead to the false allocations of risks in society. In some cases, it seems to be better to prevent losses before they can happen. The optimal solution is usually a combination of the two, implementing preventative measures to reduce the loss frequency and the severity of damages, and then insuring against rarer and more costly events [...]”.


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Research Papers

Research Paper 01 - October 2015

QuANtIFICAtIoN oF pRoduCtloSS FRoM RoAd tRAFFICACCIdENtS: MEthodoloGYANd pRElIMINARY EvIdENCE

José L. Carvalho

Research Paper 02 - November 2015

StAtIStICS oN pAIN ANd oN loSS oF FutuRE:NEW EvIdENCEClaudio R. ContadorNatália Oliveira

Research Paper 03 - June 2016

INSuRANCE ANd REINSuRANCE:poSt-opENING INtERdEpENdENCEANd CAuSAlItY

Claudio R. ContadorMarco Krebs

Research Paper 04 - August 2017

ENvIRoNMENt ANd INSuRANCEAndré Gustavo Morandi da SilvaEstêvão Kopschitz Xavier BastosJosé Gustavo Féres

ENVIRONMENT AND INSURANCE

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