1. Introduction
As the number and severity of climate change impacts rises, attention to loss and damage in international climate change fora has increased, and with it, the pressing need to find financial mechanisms to deal with climate change harm. The potential of insurance schemes to respond to this need had been explored at the regional level through insurance pools in developing countries long before their formal inclusion as part of the Warsaw International Mechanism for Loss and Damage (WIM). Insurance schemes have garnered support as financial tools for mitigating loss and damage (Lees, 2017),1 but certain issues remain unaddressed, namely the lack of continued and secure finance, the inappropriateness of insurance to meet context-specific needs, and responsibility avoidance.
This paper focuses on the potential of insurance schemes to address climate-related loss and damage, with the aim of contributing to the existing literature on finance instruments in a three-fold way. First, the paper consolidates existing work – primarily stemming from policy papers, reports, academic literature, and legal sources – identifying design options for insurance schemes as a financial means of addressing climate change loss and damage (Blampied, 2016; Mahul, Boudreau, Lane, Beckwith, & White, 2011; Schäfer, Waters, Kreft, & Zissener, 2016; Whalley, 2016). Second, the paper provides an overview of the existing insurance schemes used to respond to climate change impacts and draws on recent case studies to evaluate their effectiveness. The final section analyses the unsuitability of insurance schemes in the context of sudden and slow onset events and non-economic loss and damage (NELD), and adds to the existing literature by critically analyzing insurance schemes in light of: (i) the principle of common but differentiated responsibilities and respective capabilities (CBDR-RC); (ii) intergenerational equity; (iii) economic inequality; (iv) gender considerations; and (v) human mobility.
2. Insurance for loss and damage and summary case studies
Calls for the establishment of a loss and damage mechanism to respond to the adverse impacts of climate change were made as early as 1991 (Roberts & Huq, 2015), and have since gained growing attention until its inclusion in the Paris Agreement (Article 8; UNFCCC, 2015). However, a crucial question remains over how to support a monetary response to loss and damage in an already underfunded climate change finance system. While a number of options have been discussed, much of the debate surrounds the use of insurance schemes.
The 1991 proposal of the Alliance of Small Island States (AOSIS) also put forward the use of insurance to address loss and damage (Roberts & Huq, 2015).2 Since then, insurance has repeatedly formed part of the loss and damage debate,3 most recently culminating in its inclusion in the WIM's mandate, illustrated by the indirect reference made to risk transfer and risk-sharing in the decision establishing the WIM. The WIM then incorporated insurance in its 2-year initial work plan and again in the subsequent 5-year rolling work plan. The latter includes comprehensive risk management approaches in strategic work stream C, where finding climate risk solutions through insurance is identified as a priority activity for 2019–2021 (WIM ExCom, 2017). In addition, work stream E, in particular sub-section 1(a)-(c), focuses on securing financial instruments to address loss and damage. Further support for wider coverage provided by insurance is evident in the mandate given to the Executive Committee of the WIM by the COP to develop a clearing house for risk transfer, the Fiji Clearing House for Risk Transfer, which was launched in 2018 (UNFCCC, 2016, 2018).4
Insurance is a type of risk transfer that can be used to shift the risk of loss and damage from one entity to another in exchange for a premium.5 One form of risk transfer is risk pooling, whereby risk can be aggregated if organized in a pool (regionally or nationally), which allows for premiums to be lowered as risk is spread both across multiple actors (Gewirtzman et al., 2018) and in geographical terms (UNFCCC, 2012). These insurance pools or schemes can exist on three different levels: micro-, meso-6 and macro. A summary of insurance mechanisms in operation shows that most are established on a micro- or macro-level, which is consequently where this section will focus. Micro-insurances are implemented at a local level for low-income populations and are suitable to insure crops or livestock. Here, individuals create a pool of policyholders and the payouts are made directly to the individuals within the risk pool (Schäfer et al., 2016). In macro-insurance schemes, the policyholder is a national government within an insurance pool consisting of other countries in a specific geographical region. Payouts in macro-insurance schemes are made to the respective governments who can then invest in rehabilitation measures.
Regardless of the level they operate at, insurance schemes fall under one of two types: indemnity-based or index-based. Indemnity-based insurance schemes evaluate the loss and damage after an extreme event, once a claim has been handed in, and make payouts based on this assessment. However, the assessments can result in long delays before money is dispersed. On the other hand, index-based insurance works on the basis of pre-determined parametric triggers for natural disasters, such as rainfall amount or wind speed. Once triggered, a payout is made, which results in quick relief payment as no post-disaster assessment is required. This is a major benefit of index-based insurance.7 Due to its particular relevance to loss and damage in the context of the climate change regime, this articles deals exclusively with index-based insurance.
When looking at existing insurance schemes and insured and uninsured losses over several years, the numbers are striking. In Africa, losses from hydrological, climatological and meteorological events between 2013–2015 equated to USD 11.5 billion, of which only 810 million were insured (NatCatSERVICE (MunichRE), 2019a). Similarly, losses from tropical cyclones in the same years in the Caribbean were USD 101 billion of which only USD 44 billion were insured (NatCatSERVICE (MunichRE), 2019b). It is worth noting that MunichRE only counts major catastrophic cyclones that meet certain parameters,8 and therefore the uninsured losses are likely to be much higher in relation to overall losses.
In the last decade, macro-insurance schemes through risk transfer have been a popular solution at the regional level. Although only four regional insurance schemes exist, three of them cover reasonably sized and vulnerable geographical areas, namely the Caribbean, the Pacific, and parts of Africa. The first successful regional insurance scheme, which has been in operation since 2007, is the Caribbean Catastrophe Risk Insurance Facility (CCRIF). It aims to provide index-based insurance against extreme weather events for Caribbean governments and had, by 2017, made an accumulated payout of USD 100 million to its members (SPC, 2017). In the Pacific, the Catastrophe Risk Assessment and Financing Initiative (PCRFI) insurance scheme is operative.9 The scheme was effective in 2013 when it made its first payout of USD 1.27 million to Tonga ten days after Cyclone Ian hit the island (Bank, 2013, 2014).10 However, the initiative’s impact is questionable, as illustrated by a different example, namely the payout to Vanuatu in 2015 after Cyclone Pam. In this instance, the insurance covered USD 1.9 million against a total damage cost of USD 449.4 million, which equates to less than half a per cent of incurred cost (Government of Vanuatu, 2015).
Their African counterpart is the African Risk Capacity (ARC), where prospective member countries must provide a spending and allocation plan in the case of a payout before entering the pool. Under the ARC, members are scheduled to receive a payout within three to four weeks of the end of the rainfall season (Capacity, 2018). However the mechanism proved problematic when it mishandled Malawi’s extended drought in 2015, which included major crop failure. The event was exacerbated by its coupling with a rare flood just before the drought, which resulted in major food shortages in subsequent years (Richards & Schalatek, 2017). The ARC’s models initially assessed that the drought did not trigger the policy and therefore refused to make a payout. In light of the severity of the situation, the ARC re-assessed their model to reflect more realistic growing times for crops, and the policy was triggered (Richards & Schalatek, 2017). This example uncovers three major problems with climate insurance. First, the assessment process and correlate...