Financing coastal resilience by combining nature-based risk reduction with insurance

Ecological Economics 169 (2020) 106487

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Ecological Economics journal homepage: www.elsevier.com/locate/ecolecon

Financing coastal resilience by combining nature-based risk reduction with insurance

T

Borja G. Regueroa,b, Michael W. Beckb,a, David Schmidc, Daniel Stadtmüllerd, Justus Raepplee, Stefan Schüsselef, Kerstin Pfliegnerg,* a

Institute of Marine Sciences, University of California, Santa Cruz. 115 McAllister Way, Santa Cruz, 95060 CA, United States The Nature Conservancy, 115 McAllister Way, Santa Cruz, 95060, CA, United States c New Reinsurance Company Ltd. (NewRe), Zollikerstrasse 226, 8008, Zurich, Switzerland d InsuResilience Secretariat, hosted by GIZ GmbH, Friedrich-Ebert-Allee 40, 53113, Bonn, Germany e The Nature Conservancy, 201 Mission Street, San Francisco, 94105 CA, United States f Münchener Rückversicherungs-Gesellschaft (Munich Re), 80802, Munich, Germany g The Nature Conservancy, Schiffbauerdamm 8, 10117, Berlin, Germany b

A R T I C LE I N FO

A B S T R A C T

Keyword: Resilience insurance

The increasing impacts of climate hazards combined with the loss of coastal habitats require urgent solutions to manage risk. Storm losses continue to grow and much of them are uninsured. These losses represent an increasing burden to individuals, businesses, and can jeopardize national development goals. Pre-hazard mitigation is cost effective, but both the public and private sector struggle to finance up-front investments in it. This article explores a resilience solution that combines risk transfer (e.g., insurance) with risk reduction (e.g., hazard mitigation), which have often been treated as two separate mechanisms for disaster risk management. The combined mechanism could help align environmental and risk management goals and create opportunities for public and private investment in nature-based projects. We assessed this resilience insurance with hypothetical cases for coral reef restoration. Under conservative assumptions, 44% of the initial reef restoration costs would be covered just by insurance premium reductions in the first 5 years, with benefits amounting > 6 times the total costs over 25 years. We also test the sensitivity to key factors such as project cost, risk reduction potential, insurance structure, economic exposure and discount rates. The resilience insurance mechanism is applicable to many coastlines and can help finance nature-based adaptation.

1. Introduction

developed urban areas, small island states and coastal low lying areas globally, the need to adapt and manage these risks is particularly urgent (Hallegatte et al., 2013; Hinkel et al., 2013; Tessler et al., 2015; Storlazzi et al., 2018). Global losses due to natural catastrophes and tropical cyclones have been increasing in recent decades (Fig. 1). Storms impact national economic productivity; threaten water and food security; increase diseases; and damage critical public infrastructure, basic services and value chains (Munich Re, 2013).Yet, a large fraction of global losses remains uninsured, which represents a growing burden on national budgets and development goals (World Bank, 2011). Many governments and public utilities are overexposed and underinsured against these risks (Munich, 2013; The Geneva Association, 2014). This means that when a disaster strikes, vulnerable communities and individuals turn to governments and international agencies for recovery assistance

Natural catastrophes, including tropical cyclone flooding induced by storm surges and waves, represent a significant and growing economic challenge, particularly for developing and emerging economies (UNISDR, 2015a). Coastal areas are particularly at risk from extreme weather events given the high concentration of economic activity and the exposure to cyclones, tsunamis and other coastal hazards (Kron, 2013; Reguero et al., 2015). Coastal risks are also expected to increase in the future from the effects of climate change such as sea level rise (Church et al., 2013; Vitousek et al., 2017), more powerful ocean waves (Reguero et al., 2019a), and an increased tropical cyclone destructive potential (Woodruff et al., 2013; Ranson et al., 2014; Knutson et al., 2015). Poor and vulnerable people in developing countries have been and will be disproportionally the most affected and vulnerable. In

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Corresponding author at: The Nature Conservancy, Schiffbauerdamm 8, 10117, Berlin, Germany. E-mail address: kerstin.pfl[email protected] (K. Pfliegner).

https://doi.org/10.1016/j.ecolecon.2019.106487 Received 25 September 2018; Received in revised form 5 August 2019; Accepted 22 September 2019 0921-8009/ © 2019 Elsevier B.V. All rights reserved.

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Fig. 1. Overall and insured losses worldwide from tropical cyclones between 1980 and 2018. Direct overall losses are represented by green bars, whereas the insured losses are indicated in blue. Losses are inflation adjusted via country-specific consumer price index and consideration of exchange rate fluctuations between local currency and US$. Source: Munich Re Geo Risk Research, NatCatSERVICE, as at April 2019 (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article).

public and private entities struggle to finance resilience and face post storm payouts, the funds for investing in nature-based risk reduction are disproportionally limited compared to other infrastructure (McCreless and Beck, 2016). Among major limiting factors has been that the risk reduction benefits of nature-based solutions have been rarely quantified tangibly. However, an increasing number of rigorous valuations of such risk reduction services now allow their consideration in climate risk financing and insurance (e.g., Beck et al., 2018; Menéndez et al., 2018; Reguero et al., 2019a,b; Storlazzi et al., 2019). The need to advance nature-based approaches and risk finance is endorsed by many international agreements and initiatives such as the Sendai Framework for Disaster Risk Reduction, the Sustainable Development Goals (SDGs), or the Paris Climate Agreement. These agreements support an alignment of environmental and risk management goals to address the growing needs of managing climate risk, to confront environmental degradation, to improve the adaptive capacities of vulnerable communities, and to advance public and private investment in disaster risk prevention and reduction. However, key open questions that remain are: (1) how to align hazard mitigation with risk transfer mechanisms; and (2) whether nature-based approaches could be structured into these mechanisms and thus unlock risk finance funds. Here, we describe and test a combined risk reduction and risk transfer mechanism and apply it to a hypothetical reef restoration project to assess its economic feasibility. The proposed mechanism can help build coastal resilience because it creates an incentive to invest in risk reduction while also transferring risk through insurance. To assess such insurance resilience solutions, we calculate the concept for a hypothetical coral reef restoration and develop a cost-benefit analysis, showing a practical application for naturebased coastal protection. We also test the sensitivity of the solution to variation in key factors such as project cost, risk reduction potential, insurance structure, economic exposure and discount rates. This approach may offer a new way to incentivize nature-based projects with the potential to provide risk reduction services.

essentially as ‘insurers of last resort’. Furthermore, many coastal cities and communities are also coping with aging and underperforming infrastructure systems that increase the likelihood of cascading failures and disaster losses (Re.Bound, 2017). Investing in pre-disaster hazard mitigation has also been proven highly cost effective. For example, in the USA, pre-disaster investments can save USD $6 in future disaster costs for every USD $1 spent on hazard mitigation (Multihazard Mitigation Council, 2018). However, funding these investments often represent a challenge, particularly when natural catastrophe losses keep mounting. These factors create a growing global protection gap, particularly for tropical coastal nations (World Bank, 2011). The traditional response to these challenges has relied on risk transfer (e.g., insurance) and risk reduction (e.g., hazard mitigation). However, these two approaches have been typically treated as two separate planning and financing processes within disaster risk management. Governments, businesses and individuals confronted with contingent fiscal liabilities from exposure to natural hazards often face a decision to allocate limited funds either to (Fig. 2-a): (a) risk reduction or ex ante hazard mitigation projects that can avert future losses, or (b) risk transfer solutions that mitigate ex post the financial consequences of disasters, for example through insurance. However, it is possible to combine these two approaches. This paper identifies and calculates a way to do so through a resilience insurance solution. The use of ecosystems for adaptation and risk reduction (also known as ‘ecosystem-based adaptation’, or ‘green’ or ‘natural’ infrastructure) is gaining traction as a strategy to adapt to coastal risk (Cheong et al., 2013; Temmerman et al., 2013; Spalding et al., 2014; World Bank, 2017; Jongman, 2018; Reguero et al., 2018b). The exposure of communities and coastal assets to flooding and erosion is also increasing because coastal ecosystems that serve as a first line of defense, such as marshes, mangroves, seagrasses, oyster reefs, and coral reefs, are being lost at alarming rates (MEA, 2005; Orth et al., 2006; UNEP, 2006; Worm et al., 2006; Beck et al., 2011). These coastal ecosystems protect people and assets on the coast by reducing wave energy, trapping sediments, and attenuating storm surge (Wamsley et al., 2010; Gedan et al., 2011; Shepard et al., 2011; Pinsky et al., 2013; Ferrario et al., 2014; Möller et al., 2014; Narayan et al., 2016, 2017; Reguero et al., 2018a). Similarly, nature-based solutions can be used for coastal protection cost effectively, particularly when combined with other traditional measures (Reguero et al., 2018b). However, the role of ecosystem-based projects in risk reduction and risk transfer thus far have been very limited (Colgan et al., 2017). Ecosystem-based risk reduction is still relatively new and the application of insurance mechanisms in relation to the protective services of ecosystems is novel (Reguero et al., 2019a,b). Furthermore, while

2. Methods 2.1. Summary of the resilience insurance mechanism A conventional ‘risk owner’ (i.e., the individual, agency or government who owns the assets) would typically transfer part of its risk through an insurance mechanism over a pre-defined time period. This study proposes a mechanism that addresses typical tradeoffs between risk transfer and risk reduction investments, which is summarized as follows (Fig. 2): 2

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Fig. 2. Representation of the traditional trade-off between risk transfer and risk reduction through resilience-building measures (panel a), and how the insurance resilience solution addresses it (panel b). Panel (a) describes the decision for the risk owner: dedicating limited resources to projects that reduce risk (left panel) or transferring the risk to insurers and possible also to the capital markets (right panel). The first option requires an upfront investment, the second periodical premiums payments. Panel (b) represents a resilience insurance mechanism that addresses this tradeoff because it combines hazard mitigation with risk transfer. An investment in hazard mitigation at the beginning of the period reduces the underlying risk (1); the risk-reduction effect is monetized via reduced premiums during the treaty duration (2); a fraction of the initial investment is amortized at the end of the treaty (3), creating an incentive for the risk owner to invest in risk-reducing infrastructure while part of the risk is transferred through an insurance cover that ensures a payout in case of a catastrophic loss event (4).

• A conventional insurance mechanism transfers part of the risk from the risk owner to the insurer; • However, a hazard mitigation project, at the beginning of the risk •

either in whole, or in part, over an insurance treaty term (2);

• The savings from reduced premiums can partly pay for the initial investment in risk reduction measure (3); • In case an insurance payout is triggered by a disaster, the risk owner

transfer period (1 in Fig. 2-b), reduces the risk of flood losses for the risk owner; This risk-mitigating impact is monetized via reduced premiums

receives funds to pay for the negative financial consequences of the event (4).

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the risk reduction effect of the project. The new adjusted premium, considering the risk reduction effect of the project, was calculated as:

2.2. General approach for structuring the resilience insurance mechanism The key parts for developing this resilience insurance mechanism involve: assessing the baseline risk, calculating the risk reduction benefits of the project, identifying project costs, and structuring the risk transfer solution. The different steps are described below. The baseline risk was characterized by the expected economic damages on the assets to be insured. Risk was defined through an exceedance loss-probability curve that relates a certain level of loss (in dollar value) to its corresponding probability of occurrence (Fig. 2-a, left panels). The probability was expressed in terms of return periods (i.e. a return period of N-years corresponds to a probability of occurrence in a given year of 1/N). Loss-probability curves are specific for each site and can be determined based on risk modeling of local coastal hazards, coastal defenses and asset distribution by topography (Kroeker et al., 2016; Whelchel et al., 2018). The underlying hypothesis was that the implementation of a project would prevent economic losses (Fig. 2-a, left panels). Such risk reduction effect can be quantified by modeling coastal flood risk (i.e. tropical storm induced storm surges) before and after the project, and is represented as a reduction in losses for the different probabilities (Kroeker et al., 2016; Whelchel et al., 2018). The specific flood attenuation and loss prevention would depend on the local characteristics of each project, as would the cost. The financial feasibility of the combined solution, i.e. risk reduction and insurance protection, were determined by calculating the Annual Average Loss (AAL), and the insurance coverage limit for the coastal zone to be protected. The AAL is the sum of the losses weighted by probability of all events that create a loss (e.g., the integration of economic losses from flooding across probabilities) and can be calculated for all the losses (i.e., baseline risk), or only between two specific probabilities (see below). The fraction of risk that is transferred from the risk owner to the insurer defines the catastrophe excess of loss insurance cover or ‘insurance layer’ hereafter (Fig. 2-a, right panels). This type of cover protects the client from the losses that arise from a single catastrophic event. The insurance layer was delimited by an initial and an ending probability, which are represented by an attachment point and an exhaustion point, respectively (Fig. 2-a). The attachment point defines the economic loss (and the corresponding return period on the loss-probability curve) at which the insurer would start responding to losses, whereas the exhaustion point defines the economic loss (and probability) where the insurer would stop covering losses. The insurance limit is the maximum dollar amount that the insurer would pay out per period and was calculated as the difference in economic losses between the exhaustion and the attachment points. Loss amounts below the attachment point or exceeding the exhaustion point (Fig. 2-a) would have to be borne by the insurance buyer (this is also known as the deductible or self-retention). The annual insurance premium was determined based on the AAL for the insurance layer and a certain load or multiplier that adds the cost of capital, transaction and administration expenses for the insurer, and is calculated as: Original premium = [multiplier] * [initial insurance layer AAL]

Adjusted premium = [multiplier] * [adjusted insurance layer AAL] (2) and where the [adjusted insurance layer AAL] is calculated as: [initial insurance layer AAL] * (1- insurance layer risk reduction ratio). The multiplier was assumed constant for the original and adjusted premium calculation although it could vary depending on the size of the structure. The attachment and the exhaustion points were fixed in absolute currency amounts for the recalculation of the adjusted insurance layer AAL. The difference in insurance costs before and after the project is implemented represents the premium savings (Fig. 2), which can be calculated as the difference of the unadjusted and adjusted annual premiums every year for the treaty duration. However, the premium savings only provide accrued benefits within the insurance layer, whereas the resilience project would still provide flood protection to the risk owner for events not covered by the insurance layer (i.e. losses below and above the attachment and exhaustions points) and beyond the treaty term (i.e. risk reduction benefits after the end of the risk transfer treaty). To measure this effect, we calculated a Benefit to Cost Ratio (BCR) by calculating the Net Present Value (NPV) of the project’s total benefits (total averted losses) divided by the NPV of the total costs (costs of initial investment in project implementation and payments of premiums of the insurance treaty) over a typical lifespan (i.e. how long the project would be delivering coastal protection services) of a coastal protection project. The lifetime BCR was used as an additional metric of whether the benefits were sufficient to justify the costs of investing in risk reduction (Reguero et al., 2018b). The NPV of the costs and benefits was calculated by discounting the values as:

NPV =

T

∑t=1

bt (1 + i)t

(3)

where i is the discount rate (assumed constant) and bt represents the benefit (or cost) in year t considering the risk reduction effects of the project. The discount rates were assumed to be the same for the benefits and the costs. 2.3. Hypothetical case study: implementation for a coral reef restoration project Coral reefs are particularly effective as a first line of defense from erosion and flooding (Narayan et al., 2016; Elliff and Silva, 2017; Reguero et al., 2018a). Fringing natural reef crests function much like low crested breakwaters, dissipating wave energy and protecting the shoreline (Sheppard et al., 2005; Rogers et al., 2013; Gallop et al., 2014; Reguero et al., 2018a). This protection represents risk reduction benefits to people and property globally, which has been estimated in hundreds of millions of dollars for many tropical nations per year (Beck et al., 2018). Reefs have sustained significant damage globally from coastal development, sand and coral mining, overfishing and destructive (e.g. dynamite) fishing, storms, and climate-related bleaching events (Bjorn et al., 1986; Gardner et al., 2003; Mumby et al., 2007; Barbier et al., 2011; Hughes et al., 2018). However, restoration and reef management can help to maintain their structural complexity and the coastal protection service (Cinner et al., 2016; Torda et al., 2017), hence helping to manage coastal risk in tropical coastlines. From the different reef restoration techniques (Jaap, 2000), we focused on approaches of reef restoration for coastal protection – i.e. the restoration and rehabilitation of degraded reefs with the potential to reduce wave impact. This type of restoration would take place on shallow reefs, often near the reef crest, where the greatest wave breaking occurs and, likely, will involve repairing the integrity of the

(1)

The initial insurance layer AAL was calculated as the integration of losses between the probabilities of the attachment and exhaustion points, before the implementation of the project. The main hypothesis for the mechanism is that the implementation of the project would reduce the baseline risk (AAL) by a certain risk reduction ratio. The exact risk reduction would depend on the effectiveness of the project in providing coastal flood protection. The project implementation produces a reduction in the AAL, and therefore, the premium. Based on a repricing mechanism, the original premium for the insurance layer was adjusted for the new risk level after applying

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2019) and Mexico (Reguero et al., 2019b) show that these global estimates are reasonable and a indicate similar flood protection estimates. These studies also show that reefs provide the most flood protection benefit for high frequency (i.e. low return periods) (Quataert et al., 2015; Beck et al., 2018). Based on these prior studies, we assumed that risk reduction varied linearly from 50% (1-in-2-year event) to 20% (1in-250-year event). This level of risk reduction could be achieved by structural reef restoration (i.e. a low crested or submerged reef breakwater) that is combined with ecological coral restoration (Pickering et al., 1999; Fabi et al., 2011). This reef restoration would be designed to deliver ecological and risk reduction benefits and use techniques commonly deployed in oyster reef restoration projects and increasingly in coral reef restoration projects (Beck et al., 2011; Ferrario et al., 2014; Reguero et al., 2018a), as shown in Fig. 3 for a pilot project in Grenada (Reguero et al., 2018a). These approaches can provide risk reduction benefits immediately after implementation. The project was assumed to be completed over a 2-year period based on implementation estimates from the project in Grenada (Fig. 3).

reef framework often with a combination of (i) structural enhancements including reef rubble, limestone and/or cement and (ii) planting of small corals (Ferrario et al., 2014; Reguero et al., 2018a). The specific assumptions for the case study are described below to illustrate this resilience insurance mechanism for reef restoration, as an example of application to other nature-based solutions. 2.3.1. Hypothetical coastal zone at risk We calculated and tested the resilience insurance mechanism in a hypothetical case of a 5-km stretch of coastline with an economic asset value exposed to flooding of USD $400 million. In absence of local flood risk modeling, the loss-probability curve was defined by hypothetical loss ratios (percentage of damage) multiplied by the economic exposure ($400 million). To justify the need of a risk transfer solution, the resulting AAL should be representative of a section of coastline at relative high risk of coastal flooding. From a hazard point of view the hypothetical setting could be any site exposed to coastal flooding, but we decided to base the example on loss ratios calculated from a Country Risk Profile from the Global Assessment Report (UNISDR, 2015b). We took the figures of Dominica as input for our hypothetical case study. We used Dominica’s loss ratios because the country presents a ‘medium’ hazard level for coastal flooding (GFDRR, 2019), and presents an AAL for coastal flooding of 1.56% (nation-wide, Table 1). This AAL can be considered high for an entire nation, although it is significantly lower than the AAL for other tropical nations like Bahamas (UNISDR, 2015c). However, this mechanism would focus only on sections of coastlines (e.g., 5 to 20 km) that are at high risk to flooding (i.e. high local AALs) and high reef risk reduction effects (Beck et al., 2018). For the case study, the loss ratios were calculated dividing the expected damages from coastal flooding over the total capital exposure for the return periods provided by the country risk profile for Dominica. The loss ratios were linearly interpolated to obtain return periods of 2 years and to recreate an AAL of 1.56%. The final loss-probability curve for the hypothetical case study was obtained by multiplying the local economic exposure ($400 million) with the loss ratios in Table 1.

2.3.3. Cost of the project To estimate the cost of the restoration project, we used the median structural reef restoration cost of $1290 per meter from (Ferrario et al., 2014), which for a 5-km restoration project results in $6.45 million. To assess the sensitivity of our results to these cost estimates, we also used a higher cost estimate of $3600 per meter based on a reef pilot project in Grenada (Reguero et al. 2018a), shown in Fig. 3, that involved structural restoration with sections higher than 1-m, as considered in (Ferrario et al., 2014). This assumption is considered conservative because this unitary cost was calculated from a ∼30 m demonstrative section of reef and a larger implementation (5-km of coastline) could offer some economies of scale. 2.3.4. Structuring the insurance layer The insurance layer was defined from the loss probability curve between the 1-in-20-years (attachment point) and 1-in-50-years losses (exhaustion point). These expected return period losses were obtained from Table 1 for the probabilities 1/20 and 1/50, respectively. These attachment and exhaustion probabilities are in a typical range for a catastrophe excess of loss cover, but it could well be different depending on the financial situation and the risk tolerance of a potential insurance buyer. We assumed the premium (i.e. cost of insurance) was defined by the AAL of the insurance layer with additions for costs of capital, administration and margin for which we assumed a 50% increase in cost (i.e. a multiplier of 1.5). The value for the multiplier was taken only as a hypothetical load for illustrative purposes and should not serve as a reference figure. We also examined the sensitivity of the results to a higher multiplier of 2.0. After the project is implemented, the risk is reduced, and the adjusted premium was recalculated on an annual basis using the adjusted

2.3.2. Hypothetical reef restoration project for risk reduction The hypothesis for the implementation test is that a reef restoration project could attenuate flooding from storms such that the risk reduction benefits could be used to substantively underwrite project cost. In a real project, the risk reduction effect of the project would be calculated from high resolution modeling of wave attenuation and flooding (Monismith, 2007; Lowe et al., 2010; Buckley and Lowe, 2013; Monismith et al., 2013; Quataert et al., 2015; Costa et al., 2016; Reguero et al., 2018a) and subsequent modeling of the flood losses (Whelchel et al., 2018). However, here we estimated the risk ratio of the project based on recent research on the risk reduction benefits of coral reefs. A global assessment of the risk reduction benefits of coral reefs estimated reduction in flood losses varying from > 75% to 25% across different return periods (Beck et al., 2018). state-of-the-art reef modeling and damage assessment in the USA (Storlazzi et al., 2017,

Table 1 Loss ratios and loss-probability distribution considered for the case study. The loss ratios were calculated by dividing the expected damage for each return period over the capital stock for the country ($2028 million). Coastal flooding damages for the hypothetical case study resulted from multiplying the loss ratios with the local economic exposure ($400 million). (*) interpolated from the rest of damages to reproduce an AAL of 1.56%. Hazard

Coastal Flooding Damage - Dominica Loss Ratio (percentage of damage over capital stock value) Coastal Flooding Damage – Hypothetical case study

Return Period (years) 20 Probability

50

100

250

500

1000

1500

1/20

1/50

1/100

1/250

1/500

1/1000

1/1500

182 (*) 9.0% 36

344 17.0% 68

509 25.1% 100.4

734 36.2% 144.8

760 37.5% 150

810 39.9% 159.6

860 42.4% 169.6

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Fig. 3. Example of structural reef restoration in Grenville, Grenada, by The Nature Conservancy. Pilot units of reef restoration project in 2017 (a) and detail of one of the reef structures after construction in 2015 (right). Source: (Reguero et al., 2018a) and The Nature Conservancy.

changes in the different assumptions. Specifically, the sensitivity analysis compared the effect of:

AAL of the insurance layer (following expression 2). The savings in premiums per year were calculated as the difference between the adjusted and unadjusted premiums on a yearly basis over a 5-year treaty term.

• A lower risk reduction effect from the project of 30%-10% versus 50%-20%. • Larger cost estimates based on the Grenville´s demonstration arti-

2.3.5. Calculating the Benefit to Cost Ratio over the project lifespan Additionally, we calculated the Net Present Value of the restoration costs and benefits over a lifespan of 25 years, which is assumed as a minimum typical lifespan of a coastal protection project (e.g. USACE, 2002). The costs included the project cost and the insurance cost. The benefits were calculated as the NPV of the differences in adjusted and unadjusted AAL (see previous section) over the 25-year lifespan. Initially, we used a discount rate of 0% assuming the discounting will be initially compensated by economic growth and to avoid the effect of discounting in the benchmark case study. However, we also examined the sensitivity of the results to other discount rates (2 and 5%). We use the same constant discount rates for the costs and benefits.

• • • •

ficial reef of $3600 per meter (Reguero et al., 2018a) as compared with the median cost of $1290 per meter from (Ferrario et al., 2014). Lower value of assets at risk: $300 million versus $400 million. A lower entry point for the insurance layer of 15-years instead of a 20-years return period. A larger multiplier load of 2.0 for the premium calculation, instead of the default 1.5. Higher discount rates: 2% and 5% as compared to the assumption that discounting was completely offset by the economic growth.

3. Results 2.4. Sensitivity analysis 3.1. Case study of the resilience insurance solution for reef restoration project

The costs and benefits of a combined reef restoration and risktransfer solution depend on several factors related to (i) the project and (ii) the structuring of the mechanism. Some factors related to the project include the length of the restored reef and the protected coastline, the amount of exposure, and the risk reduction effect of the project. Other factors related to the financials of the mechanism include the insurance layer definition, the multiplier load and the discount rate applied, among others. Given the variety of factors that can affect the results of the solution, we conducted a sensitivity analysis to compare different scenarios and test the range of variation in the results to

The main configuration of the hypothetical case study is summarized in Table 2. The resilience insurance solution includes an insurance policy and a construction of a reef restoration project to protect 5-km of shoreline, with assets at risk of $400 million. The loss-probability curve is represented in Fig. 4. The AAL for the case study is 1.56%, which represents a risk of $6.24 million per year. The cost of the project was estimated in $6.45 million. Based on the risk transfer mechanism, the insurance buyer would

Table 2 Resilience insurance solution configuration for the hypothetical case study. The reef restoration project

The risk transfer structure

Technical details of project: Length: 5000 m Restoration technique: structural reef restoration. Costs and financing Unitary cost of reef restoration: $1290 per linear meter. Total Cost of project: $6.45 million External financing share: 0% (conservative) Restoration Costs for Risk Owner: $6.45 million (100% of cost). Estimated risk reduction impact: Maximum risk reduction (2-year return period): 50% Minimum risk reduction (250-year return period): 20% Time until full risk reduction impact is achieved: 2 years (duration for the project to be completed) (*)

Assets at risk: $400 million Coverage details: Coverage limit: $31.9 million Covered peril: Coastal flooding (storm surge and wave-driven flooding) Covered asset: Local infrastructure and properties. Treaty term duration: 5 years, with annual premium adjustments based on pricing reset mechanism.

• • • • • • • • •

• • • •

Insurance layer: Attachment point: $35.9 million (1-in-20-years loss). Exhaustion point: $67.8 million (1-in-50-years loss). Initial (before project) AAL: 1.56% (of covered assets) Initial (before project) AAL for the insurance layer: 3.0% (of insurance limit) Initial (before restoration) Annual Premium: Multiplier (1.5) * Initial AAL = 4.51% (on limit) Adjusted insurance layer AAL (after restoration): 1.32% Adjusted annual premium (after restoration): 1.99%

• • • • • • •

(*) After year 1, 50% of the risk reduction effect was already activated and accounted for, assuming partial implementation of the project. 6

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Fig. 4. Loss-probability curve and risk reduction effect of the reef restoration project. Risk is reduced by 50% for the return period of 2 years, and by 20% for the 250 years. Losses (Yaxis, left) for the hypothetical coastal zone are calculated multiplying the economic exposure ($400 million) with the loss ratios (percentage damage) in Table 1 for each return period (Xaxis). The insurance layer (or catastrophe excess of loss cover) is indicated in shading. The attachment and exhaustion points are annotated on the original curve.

receive compensation for flood-related losses from tropical storms up to a cover limit of $31.9 million (the difference in losses between the attachment and exhaustion points). The annual premiums depend on the amount of risk that is transferred, defined by insurance layer and indicated in shading in Fig. 4. The AAL for the insurance layer is 3% (AAL calculated between the attachment and the exhaustion points) and the initial premium (in year 1) results 4.5% of the insurance limit after applying the multiplier (x1.5), which totals $1.44 million. The reduction in risk reduces the annual premiums based on the pricing reset mechanism. The financials over a 5-year term are outlined in Table 3 and represented in Fig. 5. An initial investment of $6.45 million in coral reef restoration for 5-km of shoreline length reduces the AAL for the insurance layer from 3% to 1.32%. This lowers the annual premiums from $1.4 million to $0.6 million. The annual saving from reduced insurance premiums ($0.8 million per year) represents a 12.5% savings per year on the initial project cost. Over the treaty term duration of 5 years, the total savings would be $2.8 million, which represents 43.7% of the initial cost of the restoration project (Table 2). In this hypothetical example, the remaining restoration cost of $3.6 million (56.3% of the original cost) would have to be financed from other sources. In this case, the reef restoration is not fully paid by premium savings, but the solution does reduce premiums (Fig. 5). For comparison, an equivalent annual cost for the buyer from having the insurance cover

and the remaining cost of the project outside the resilience mechanism would represent a 6.8% all-in annual premium (of the insurance limit). However, the reef restoration also would also provide risk reduction benefits for the beneficiary outside the insurance layer (shaded area in Fig. 4), below and above the attachment points (20- and 50-years return periods), as represented in Fig. 4. Assuming a 25-year lifespan for the reef project (and that the economic growth offsets the discount rate), the cumulative value of total risk-reduction benefits of the project amounts $67.9 million, as represented in Fig. 6, which constitutes a BCR of 6.3. 3.2. Sensitivity analysis The case study shows that the savings in insurance premiums accumulated across the duration of the treaty term can help finance the upfront investment in flood risk reduction. However, several factors control the results of the resilience solution, including: the risk reduction effect of the project; the economic exposure; and the project cost. We tested the sensitivity of the results to these parameters and compared their effect on the total premium savings over the project cost, and the estimated BCR over a 25-years lifespan. Results for the different scenarios are outlined in Table 4, and include lower economic exposure (i.e., lower risk), higher costs, and lower risk reduction effect of the project. The expected risk reduction effect of the project is one critical

Table 3 Insurance premium development: expected premium development and cross financing flow of the reef restoration project costs. Year 1

2

3

4

Insurance layer AAL (%) 3.00% 2.16% 1.32% 1.32% Annual Premium: AAL (%) x multiplier 4.51% 3.25% 1.99% 1.99% Initial Annual Premium – without project ($) $1,440,211 $1,440,211 $1,440,211 $1,440,211 Adjusted Annual Premium – with project ($) $1,440,211 $1,037,427 $634,643 $634,643 Premium Savings ($) $0 $402,784 $805,568 $805,568 Savings over the initial investment (%) 0% 6.2% 12.5% 12.5% Total Premium Budget Commitment (sum of all adjusted annual premiums) Total Premium Savings Remaining Restoration Costs Total average losses for the risk owner without the project and the risk transfer solution during a 25-year period (without discounting) Total average losses for the risk owner with the project and the risk transfer solution during a 25-year period (without discounting) Total risk reduction benefits for the risk owner during a 25-year period (without discounting) Total costs for risk owner during a 25-year period (without discounting) Benefit to Cost ratio during a 25-year period (without discounting) Benefit to Cost ratio during a 25-year period (assuming a 2% discount rate)

7

5 1.32% 1.99% $1,440,211 $634,643 $805,568 12.5% $6,965,683 $2,819,488 (43.7 % of total cost) $3,630,512 (56.3% of total cost) $156,000,000 $88,063,697 $67,936,303 $10,831,569 6.27 5.06

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Fig. 5. Insurance premium development and cross financing of the initial reef restoration project costs. Figures are expressed in $ million. The premiums (grey bars) are adjusted each year based on the risk reduction project.

discount rate = 0%). However, we tested this effect separately, by comparing the results with 2 and 5% discount rates. The results are provided in Table 6.

factor for savings over the cost of the project and BCR. However, a break-even scenario with BCR of 1.0 could be achieved with a mere 6% risk reduction, which is significantly lower than modeled risk reduction estimates from existing coral reefs (e.g., Beck et al., 2018; B.G. Reguero et al., 2019a,b; Storlazzi et al., 2019). Another influencing factor in the resilience solution is the definition of the insurance risk layer. To test the sensitivity of the results to where the entry and exhaustion points were set, we compared the results to changes in the risk transfer structure, by comparing: two economic exposures ($400 million and $300 million), an attachment point of 15years return period instead of a 20-years return period, and a larger multiplier in the premium calculation 2.0 versus 1.5). The results are provided in Table 5. A lower entry point provides more savings relative to the cost of the upfront investment in risk reduction. More assets at risk and larger multipliers increase the percent savings over project costs. Finally, the benchmark case study did not include the effect of discounting the future benefits because we assumed that economic growth in a high-exposure coastal zone could offset this effect (i.e.

4. Discussion 4.1. Risk financing for advancing nature-based risk reduction We present a first example of how to combine risk transfer and risk reduction mechanisms to incentivize both nature-based solutions and insurance to address the growing protection gap. This resilience insurance solution has the potential to scale up investments in reef restoration, and other nature-based solutions. The solution overcomes traditional tradeoffs between hazard mitigation and risk transfer by combining insurance repricing with an upfront investment in risk reduction. The risk reduction impact is quantified and credited with a reduced insurance premium, which creates a direct incentive for the risk owner to invest in risk reduction. Thus, the savings in insurance premiums can also be seen as a resilience dividend, and the model as a Fig. 6. Summary of risk reduction benefits over costs over a lifespan of 25 years. The left panel represents the benefit from the reduced AAL on a yearly basis, over the project lifespan. The right panel represents the total accrued risk reduction benefits over the 25 years, the costs of the project, the premium payments, and the total net benefit.

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Table 4 Sensitivity analyses examining the effects of assets protected, project cost, and risk reduction benefit on the Benefit Cost Ratio (BCR) over a 25-year lifespan (discount rate = 0%). The 50-20% risk reduction effect of the project is compared with a reduced risk reduction of 30-10% (applied linearly on the same loss curve). The Percent Savings from Project are calculated as: 1 – (restoration costs – total premium savings) / (total cost of project). Asset at risk

Cost

$400 million

Median = 1290$/m

$300 million

Grenville = 3600$/m (Reguero et al., 2018a) Median = 1290$/m

$400 million

Grenville = 3600$/m (Reguero et al., 2018a) Median = 1290$/m

Grenville = 3600$/m (Reguero et al., 2018a)

Risk reduction effect of the project RP2

RP250

50% 30% 50% 30% 50% 30% 50% 30% 10% 6% 10% 10%

20% 10% 20% 10% 20% 10% 20% 10% 0% 6% 10% 10%

Percent Savings over cost of project

Final BCR

43.71% 28.09% 15.66% 10.06% 32.78% 21.06% 11.75% 7.55% 9.46% 6.65% 11.05% 3.96%

6.27 3.55 3.04 1.80 5.23 3.01 2.39 1.43 1.25 1.01 1.47 0.78

Table 6 Sensitivity to the discount rate of the savings, benefits and costs. Asset at risk

Discount rate

Percent Savings over cost of project

Final BCR

$400 million

0% 2% 5% 0% 2% 5%

43.71% 41.84% 39.27% 32.78% 31.38% 29.46%

6.27 5.06 3.82 5.23 4.21 3.17

$300 million

premiums significantly; likely offers co-benefits (e.g., tourism and fishery benefits) that were not accounted for here; and will continue to offer significant benefits that more than recover costs over the (25+ years) life of the project. Based on the risk reduction benefits estimated in (Beck et al., 2018), (Reguero et al., 2019b), and (Storlazzi et al., 2019), there are likely many coastlines where reef restoration costs could be fully covered by premium reductions. The hypothetical case study also shows that the coral reef restoration project leads to an attractive BCR over a range of assumptions. Our sensitivity analyses indicate that the project cost and the risk reduction effect are the two most critical parameters affecting the BCR. BCR near or below 1 were only found for scenarios with very low risk reduction benefits (10%) and very high costs in 25-year projects (Table 3). A break-even scenario for the median cost of reef restoration is achieved only by a risk reduction effect of 6% (Table 3), which is substantially lower than existing estimates of the risk reduction effect of coral reefs. Changing the risk transfer structure could also increase considerably the percentage of savings in restoration (Table 5). Lowering the attachment points (i.e. transferring more risk) and increasing the multiplier (i.e. increasing the structuring cost), would both increase the percentage savings in premiums but slightly decrease the overall BCR because the total payments for transferring the risk would increase. However, transaction and capital costs can increase with the cover size although our assumptions only considered a constant multiplier. A real implementation would therefore require precise estimation of flood risk reduction, project costs, and transaction and capital costs. Although premium reductions are not an entirely new concept in the sector, the novelty of this resilience insurance concept is the combination of ecosystem-based adaptation with premium reductions in a private markets’ transaction framework. For example, USA FEMA’s Community Rating System (CRS) within the National Flood Insurance Program does include ecosystem options for reducing the costs of insurance (FEMA, 2019). Communities enrolled in the CRS program may receive discounts on flood insurance, based on mitigation efforts and open space preservation, which can be considered a form of ecosystembased adaptation. However, the CRS has only been accomplished on a public policy basis and remains to be applied in market transactions. The linkage between insurance and investment in projects to monetize avoided losses is also considered in the recently proposed ‘Resilience Bonds’ concept (Re.Bound, 2015, 2017), but this concept is still hypothetical. However, one existing marketable example of a combination

pathway to create incentives for building long-term resilience. The model can also be applied in a range of contexts to fund hazard mitigation investments (e.g. coastal protection projects) and to inform public policy on risk management. These solutions will be increasingly relevant and necessary for adaptation and management as risks increase from climate change, coastal development and ecosystem degradation (e.g. Beck et al., 2018; Reguero et al., 2019a, b; Storlazzi et al., 2019). The increasing risks will show up as costs to governments, businesses and individuals unless innovative approaches are identified to reduce them. Some risk management will require changes in public policy, which can be aided by solutions that help incentive the necessary actions. For example, private insurers, or public policy makers, could require not to reinstate pre-disaster conditions but, instead, invest in measures that can reduce the magnitude of future losses (e.g. ´build back better´). Resilience insurance solutions could also be coupled with direct insurance for this natural infrastructure, e.g., taking out an insurance policy to cover storm damages to natural infrastructure such as the MesoAmerican Reef, which protects coastal properties and livelihoods (Reguero et al., 2019b). These solutions can also benefit from public policy measures that ensure that risk is appropriately accounted for and that help direct recovery investments towards more long-term resilience building. A similar approach can also be applied to a combined coverage for flooding and wind losses, where the premium saving effect could be adjusted depending on the share of flooding in the overall losses. Although, in the case study, the reef restoration was not fully compensated by savings in premiums, the solution does reduce

Table 5 Sensitivity to the risk transfer parameters for different economic exposure. Asset at risk

$400 million

$300 million

Insurance Layer Attachment point (return period)

Exhaustion point (return period)

20 15 20 15 20 15 20 15

50 50 50 50 50 50 50 50

Multiplier Load for premium calculation

Percent Savings over cost of project

Final BCR

1.5 1.5 2.0 2.0 1.5 1.5 2.0 2.0

43.71% 67.77% 58.28% 90.36% 30.78% 50.83% 43.71% 67.77%

6.27 5.23 5.53 4.46 5.23 4.50 4.70 3.92

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Table 7 Comparison of different factors for the resilience solution between mangroves and coral reefs.

Restoration techniques

Costs and Timeline

Risk Reduction Impact

Mangroves

Coral Reefs

Replanting Natural propagation and hydrological restoration (disturbances removal and seedlings availability) Sacrificial structures (e.g. permeable dams for sediment trapping and wave breaking) Semi-permanent structures (e.g., mangroves in cement planters) Planting costs: $5000 - $10,000 per hectare, implying $100,000 - $200,000 costs per kilometer of coastline protected Benefits delivery: 7-10 year growth window, with significant risk reduction beginning in year 2 Space requirements 10 – 30% flood risk reduction (surge-driven flooding) 5 – 15% wind risk reduction (after fully grown)

Structural stabilization Natural regeneration (disturbances removal) Active planting / coral nurseries

Restoration costs: $1-3 mill. per kilometer of structural reef restoration Benefits delivery: Immediate upon structural reef restoration (also influence on sediment and coastal stability) Constructability requirements 10 – 50% flood risk reduction (wave driven flooding) Potential benefits on shoreline accretion & stability (not quantified)

a fraction of the initial investment or for the annual premium payments, the calculations would be similar and result in a higher BCR given the reduced initial cost for the risk owner.

of pre-disaster mitigation with insurance cost can be found in the ‘MyStrongHome’ program for wind damage prevention, which offers US residential homeowners in hurricane-prone areas lower insurance premiums after an initial investment for fortifying their roofs. In this program, total premiums savings overcome the costs of structural upgrades over a period of seven years (MyStrongHome, 2019). The application of this mechanism to nature-based projects represents a promising pathway for financing ecosystem-based adaptation and risk reduction. Our case study shows significant cost savings that help amortize risk reduction projects. It therefore constitutes one of the first available examples that can foster investments from the insurance sector in these projects. This has the potential to help pay for conserving and restoring biodiversity (Barbier et al., 2018) and to address the historically limited funding for conservation and nature-based solutions (McCreless and Beck, 2016). This study demonstrates that investments in nature-based risk reduction measures can deliver tangible savings in insurance costs and, therefore, serve as a strong political argument to overcome hurdles for long term investments. These mechanisms are particularly relevant for coral reefs, which are increasingly imperiled globally. This mechanism could be useful in many countries particularly in tropical, coastal countries and Small Island states where resources for hazard mitigation are particularly limited, but where reefs offer significant natural protection from storms. These are also the countries with some of the biggest protection gaps. Reefs, for example, protect many tropical low-lying coastal communities and small island states whose resources and options to face the increasing risks from reef degradation, sea level rise and wave driven flooding are limited. The resilience solution here developed can help them to adapt to these risks and restore their natural infrastructure, but also provide them financial protection against impacts from extreme events. Risk financing can thereby represent a new opportunity to fund and scale up some of the global reef restoration efforts at a time when the global consensus is growing about the increasingly dire condition of reefs. The application of the mechanism to ecosystem-based projects also presents the opportunity to leverage other co-benefits and environmental goals. For example, coral reefs cover less than 2% of the oceans bottom, but are home to 25% of all marine fish species (Burke et al., 2011), which are sources of revenue and food for many populations (Wilkinson, 2008). Coral reef-related tourism is also significant in over 100 countries and valued at nearly $36 billion globally per year (Spalding et al., 2017). Although these co-benefits were not factored in our analysis, they could increase the attractiveness of the investment for the risk owner. Although the resilience mechanism could help finance pre-disaster mitigation, there are still upfront costs that could be difficult for lowincome countries. In these cases, additional external funding could be sought from adaptation and hazard mitigation loans and grants. Although the case study did not include any external financing share for

4.2. Application to other ecosystems This resilience insurance model can also be applied to other ecosystems and hazard mitigation projects, although there will be differences in costs, techniques, timing and effectiveness of risk reduction effects. The approach could also be applied to a combination of green and grey projects for flood risk reduction. For example, mangrove restoration is generally less expensive than reef restoration (Bayraktarov et al., 2015; Barbier, 2017); but the full risk reduction effects could take longer to materialize unless more mature trees or other measures are undertaken.. We identify and contrast some of the key considerations for mangrove and reef restoration (Table 7) while acknowledging that context (ecological, political, geophysical) matters for these systems that occur in more than 100 countries around the globe. The same principles for creating the resilience incentive can also be applied to other nature-based solutions and other natural hazards, including: river and floodplain restoration, urban storm water management, forest-based landslide risk prevention or nature-based fire management (e.g. McVittie et al., 2017; Faivre et al., 2018; Moos et al., 2018; Whelchel et al., 2018). Although each project may present different estimates and characteristics, very importantly, the benefits of these ecosystems must be assessed using techniques and approaches from the risk industry (e.g. Beck and Lange, 2016) so that the integration with risk financing is feasible. For its application to other ecosystem-based projects, we recommend the steps summarized below:

• Model coastal flood risk and calculate the AAL. • Structure the risk transfer solution (in absence of the project) and • • • •

calculate the unadjusted premium for the AAL for the fraction of the risk that is transferred through the insurance. Model the risk reduction effect of the project and its effect on AAL, including how long it will take until the project is able to provide tangible risk reduction. Calculate a reduced premium based on the risk reduction effect of the project in the AAL for the insurance layer. Calculate the total premium savings over the treaty term. Calculate and compare the NPV of total costs and benefits for the project lifespan (which will be longer than the treaty term).

5. Conclusions This paper presents one of the first examples to date that combines nature-based risk reduction with insurance. This combined solution aligns with the goals of international frameworks such as the Paris 10

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Agreement, the Sendai Framework for Disaster Risk Reduction and the Agenda 2030 for Sustainable Development, because it has the potential to advance the investment in resilience and risk reduction while delivering conservation and environmental goals. Such combinations can have high benefits for societies, economies and ecosystems. The case study for reef restoration demonstrates that a significant fraction of the upfront investment could be amortized through savings in insurance premiums. The economics are rather robust with benefits exceeding costs over a factor of 6 during a typical project lifespan, and still above 4 when stressed for different factors and assumptions. The concept can also be applied to other risks and perils and for other ecosystem-based projects and river flooding. The proposed mechanism represents a pathway to finance restoration and nature-based risk reduction, and thereby encourage their implementation, in regions and countries that have less capacity and funding available, but with pressing needs for managing their risk.

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