Are premium price increases really a way to reduce climate risk exposure?

Home insurance prices are increasing in advanced economies around the world, at a rate that is making insurance unaffordable in countries such as Australia, Canada, the UK, and the USA. This is a problem because both individuals and the societies in which they live have come to rely upon insurance as a key source of post-disaster funding for recovery and reconstruction. Insurance is also a key factor in wider economic stability, such as homeowner markets, where insurance is a necessary condition to take out or retain a mortgage. Yet owners of properties in climate exposed areas – those properties likely to or already suffering greater losses from the increased severity and/or frequency of hazards such as windstorm, flood, and wildfire – are facing rising premiums to reflect their higher risk of a claim. This insurance practice, known as risk-reflective pricing, means that those at higher risk of a loss are charged a higher price to reflect the potential losses that they bring to the pool of everyone insured by a given insurance company, or indeed, the insured public more broadly. Increasingly, therefore, those with higher exposure to losses find that their insurance prices have gone up.

 

In theory, owners of such climate-exposed properties either will move away from the high-risk zones or will undertake structural changes to reduce the risk of a loss to their properties; for example, by raising their homes above flood levels. This argument that people will respond to risk-reflective pricing by reducing their risk is often advanced by the insurance industry as a reason why governments should not intervene to lower insurance pricing. However, the assumption that price is an effective signal to shape behavior towards relocation or mitigation does not necessarily hold up in what people actually do, or are able to do, to change their exposure to climate risk. Rather than changing where or how people live, the increasingly high premiums from risk-reflective pricing are leaving swathes of people without insurance to recover from extreme weather disasters including wildfire, flood, and tropical storm. This problem is known as the insurance protection gap - the gap between economic and insured loss after a disaster.

 

Governments, regulators, insurers, and individuals are increasingly recognizing the serious and widespread effects of this protection gap on economies and societies. Disaster insurance helps to stabilize regions, both prior to and post disaster, because it supports mortgages and other lending for homeowners and businesses pre-disaster and provides global insurance and reinsurance capital to reconstruct after a disaster. Lack of insurance is associated with pre-disaster inequality for those who are often already financially vulnerable because they are unable to access other financial systems such as homeowner mortgages. This inequality is further compounded post-disaster, where lack of insurance is associated with delayed recovery and increased financial burden on individual households, and also with reduced economic activity or even failure for businesses in under-insured regions. The implications of unaffordable or unavailable insurance for individual property owners and for the communities in which they live are, therefore, devastating economically and socially.

 

In response, many governments are intervening in insurance markets to create national insurance or reinsurance risk pools to help lower the costs of insurance. National risk pools are typically not-for-profit insurance or reinsurance schemes, legislated by governments to provide insurance to people who would otherwise struggle to access or afford it in the private market (e.g., Flood Re in the UK; EQC Toka Tũ Ake in NZ; the NFIP in the USA). One key way that such pools make insurance affordable is by subsidizing the policyholder’s premium, thereby reducing its true market cost in the private sector. For example, Flood Re in the UK is a reinsurance pool that receives a £10 GBP ($12.50 US) levy from every homeowner policy, making a capital fund that is then used to subsidize the costs of insurance to those in areas of high flood risk to make their premiums more affordable. This mechanism, known as risk redistribution, has been shown to be effective in lowering insurance premiums to high-risk homeowners. For example, premium reductions of more than 50% were achieved on many previously flooded homes in the UK after the implementation of the Flood Re scheme. Effectively such risk pools diversify risk across the entire insured population and redistribute the benefits of this diversification to those at high risk to ensure that they can remain in the pool of insureds.

 

While risk pools are one way to lower premiums, they are often criticized because they enable those at high risk to remain insured, thus providing no incentive to relocate away from the extreme weather zone, or to mitigate against its effects. The argument is that a high insurance premium is a signal about climate change that should not be distorted by a pool. As one manager of a pool in our research noted:

 

Maybe insurance coverage wouldn't be available in some locations if it wasn't for the [pool]. Because private insurers they'd be like “no, we’ll be out of here, thanks, we're not covering tops of cliff and floodplains and fault zones.”  So maybe it is taking away the absolute incentive to adapt and mitigate to climate change effects.

 

The point being made is that, in suppressing the insurance price signal, a pool may be generating perverse incentives not to engage in climate adaptation. However, the notion that insurance price is an effective signal for changing exposure to climate risk falls down in relation to both relocation and risk mitigation, for reasons that I now explain.

 

First, people are often in a high-risk area through no fault of their own. Rather, as both the weather and the built environment have changed, properties that once were not prone to extreme losses have now become uninsurable. The owners of these properties suffer the effects of legacy assets; meaning their once safe, insurable homes, on which they may have long-term mortgages, are now no longer insurable. Others may buy into a new area, unaware that it is in a high-risk zone, because there is no requirement by land planning or developers to ensure that homes will be built only in insurable areas, and the hazard maps for those areas are neither updated to reflect current risk, nor to incorporate climate projections for future likelihood of disaster. Hence, the price signal may arise only after the property is owned, and sometimes has been owned for many years. That means the signal was not effective as a deterrent because it came too late in the property ownership journey.

 

Second, once property owners realize that they are no longer insurable, the prevailing assumption in the insurance sector is that the high price will be a signal for people to move. However, numerous studies have shown that there are multiple reasons why people do not move from uninsurable properties. These range from an inability to sell the property in areas where hazard and insurance pricing disclosure is now readily available or even required as a condition of sale to a lack of available and affordable housing in areas where they might also get work or find suitable schooling for their children, to a social reliance on family, friends, and community to support them through the aftermath of disasters. The latter is particularly likely to apply to those who are no longer able to rely on or have lost trust in institutions, such as insurance payments or government funding, for disaster recovery.  

 

I refer to these issues in using insurance price signals as a means of driving relocation as ‘the illusion of choice’. A price signal is based on the idea that individuals will make rational choices to move when confronted with their inability to remain insured. However, as the aforementioned compelling reasons for not moving show, choices are complex and there may be equally rational reasons to remain, such as an inability to find affordable housing or work elsewhere. Hence, the choice to move away from a high-risk zone because of high insurance premiums is an illusion; it assumes individuals a) are responsible for the bad situation in which they now find themselves, and b) could simply make a better choice, without considering whether other choices are actually available to them.

 

Another argument related to price signal is that it will drive risk mitigation, while subsidized insurance will provide no incentive for mitigation. The argument is that those with high premiums will be incentivized to make changes to their properties that will reduce their insurance premiums. However, while risk mitigation is very important in improving people’s resilience to disaster, there is limited evidence that it has significant effects on premium pricing, particularly for disasters like flooding. That is, risk mitigation, such as retrofitting a home to make it more durable to extreme weather and to incur lower losses, may make people safer and enable them to get back into their homes more quickly after a disaster. However, the link between those mitigations and the reductions in premium are complicated, so that, in reality, the insurance premiums may remain high even after mitigation.

 

Additionally, risk mitigation may be necessary in infrastructure and the built environment, such as levee banks, changed drainage systems, and wetlands for water absorption in the case of flood. Some of the specific measures that will have significant effects in reducing the risk of loss are largely untested at scale or simply unsuitable for some regions. For example, levee banks are not suitable for some areas with severe flooding, while other long-established developments in historical flood plains have no obvious infrastructure solution. Importantly, risk mitigation measures of such scale are beyond the capacity of individual property owners. While the price signal applies to the individual property, the means to change that signal through large-scale risk reduction measures are not within the individual’s remit. In our book we refer to this as the ‘hot potato’ argument, in which everyone agrees that risk reduction will be key to changing insurance pricing. However, the specific measures to be taken, their likely impact on risk exposure and insurance pricing, and who should fund and implement them is unclear. Rather, the responsibility for risk reduction is passed rapidly between different potential stakeholders, like a hot potato, never settling on any particular stakeholder.

 

The above argument shows that high insurance pricing is indeed an important signal of who is at high risk of a loss from extreme weather. However, it also shows that the means of changing that price signal is not easily within the remit of individual homeowners, who often lack the means to change their risk exposure because of both the illusion of choice, and the weak links between insurance prices and risk mitigation. What then, should we do with such signals? I argue that we should use them to identify those most in need of support with climate adaptation. Rather than using price as a signal to push responsibility onto those individuals who are climate exposed to fix themselves, we need to use this signal to lead societal climate responses. A high price signal shows that specific properties, in their current form, are highly climate exposed. Gathering data on such properties and working with property owners, their communities, government agencies, and insurers in effective cross-sector collaborations to use those data, would enable us, as a society, to generate more effective solutions to the climate adaptations we know must take place. 

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