Risk based pricing the new normal

Until recently, domestic property premiums were largely cross-subsidised, with lower-risk locations effectively subsidising higher-risk ones. However, challenges posed by earthquakes and natural disasters in New Zealand have caused a shift away from cross-subsidisation towards a more individualised approach to property pricing.

This can be done via risk-based pricing, where statistical modelling can predict the likelihood and impact of certain events for individual locations, rather than just the wider area. In New Zealand, the most concerning risks come from the natural environment — earthquakes, floods, landslides and erosion. Following the catastrophic Canterbury earthquakes [in 2010 and 2011], insurers now have billions of dollars’ worth of claims data with which to assess their exposure.

The overall industry trend is towards risk-based pricing. Tower Insurance introduced it for domestic property in mid-2018, and others such as AA Insurance have followed suit, citing concerns about natural disasters as impetus for the change. A recent Lloyd’s report notes that New Zealand is the second-riskiest country in the world for natural disasters.

The 2011 Canterbury earthquakes caused damage equal to 15 per cent of its GDP, and extreme weather events look set to increase with climate change. The reinsurance industry is increasingly concerned about the impact of these losses. Figure 1, from Munich Re, highlights this upwards trend.

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THE EFFECTS OF RISK-BASED PRICING ON INSURERS

Risk-based pricing allows insurers to drill down into individual risks and assess them on their own merits, based on factors such as seismic calculations and flood maps. In the past, they used broad-rating tools such as postcodes so the uncertainty around the risk posed by individual locations led to high rates of cross-subsidisation.

Insurers who fail to use risk-based pricing will face pressure from competitors who can provide lower premiums for lower-risk customers while charging more for high-risk ones. A possible result will be that adverse selection will mean consumers who have seen their premiums increase will start moving their high-risk properties to insurers that don’t use risk-based pricing. Over time, this will increase the proportion of high-risk policies on these insurers’ books, eventually leading to higher claims costs and increasing pressure from reinsurers.

WHAT DOES RISK-BASED PRICING MEAN FOR CONSUMERS?

According to the Insurance Council of Australia (ICA), cross-subsidisation tends to result in higher average premiums overall due to the level of uncertainty around individual risks.

Conversely, Australia’s Actuaries Institute says risk-based pricing results in lower premiums for most customers. Figure 2 shows how improved analytics or big data lead to a flattened premium distribution — more low-risk customers see premium decreases (B) and fewer customers are treated as ‘average’ (A). Conversely, there will also be an increased subsector of high-risk customers (C), who will be priced out of insurance entirely.

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Some areas, however, may be viewed as too risky and left uninsurable. We see this in Australia where advanced flood modelling has effectively priced some properties out of the private insurance market and left them unsellable. This will be exacerbated by future exposure and losses due to climate change. A recent report by New Zealand’s National Institute of Water and Atmospheric Research advises that 50,000 properties in New Zealand collectively worth NZ$12.5 billion are currently exposed to extreme coastal flooding. That figure could increase as we begin to feel the impacts of climate change.

Risk-based pricing may also reduce choice for consumers. This is the case in Australia’s Northern Territory. According to the Australian Competition and Consumer Commission 2018 interim report on the Northern Australia insurance inquiry, general insurance customers faced increasingly limited choice, as insurers were unwilling to open themselves to flood exposure and some insurers declined to quote entirely in some areas.

EFFECTS ON SOCIETY

Increasing premiums could also lead to some areas being affordable only to the well off, while those on lower incomes are filtered into riskier locations. Perversely, the people least likely to have insurance and to be able to recover in the event of a large loss could also become those most at risk.

The ICA says this rising insurance unaffordability could raise public policy issues and questions around the role of government.

Taking a more optimistic view, risk-based pricing may lead to better long-term results for society. In this scenario, insurance risk modelling would be considered when the New Zealand Government and developers determine where to build. We are seeing the insurance industry push for a low-carbon economy in the light of climate change. Many of the large global insurers have withdrawn from underwriting coalmines and power plants, and 19 of the major global insurers are divesting from coal and other fossil fuels.

IS THIS THE END OF COLLECTIVE POOLING?

Insurance at a fundamental level involves the transfer of risk from the insured to the insurer, where the level of risk determines the premium charged and the restrictions imposed. These premiums are collected and pooled together and allow insurers to pay the claims of the few out of the premiums of the many. Historically, insurers did not have access to the level of data that they do today and so there was more uncertainty around individual risks. As discussed, this resulted in a high degree of cross-subsidisation, which led to the premiums for higher-risk locations not accurately reflecting the risk they posed.

In a low interest rate environment, insurers face decreasing investment returns. This shifts the emphasis to delivering underwriting returns, and risk-based pricing is a key tool in achieving this. However, risk modelling company RMS points out that this can lead to tension between the insurer’s role as a profit-making entity versus its role as a risk pooler. 

The Reserve Bank of New Zealand’s recent Financial Stability Report also notes that extreme risk-based pricing could threaten the collective pooling of risk — some insurance customers face higher premiums and a small proportion are unable to acquire total insurance cover, reducing the size of the pool and leading to properties facing a premium tailored to their individual locations rather than the wider area.

Ultimately, however, risk-based pricing will not do away with collective pooling entirely. Insurance is rooted in uncertainty, and, except for the highest risk locations, no amount of data can predict with certainty when losses will occur and what they will cost. Insurers still need to cross-subsidise and collectively pool risks in the face of these uncertain future losses.

Better data analytics do not mean that risk pooling will come to an end. Sharing losses has always been a basic concept of insurance, and more granular pricing just means that insurers can charge a premium that better reflects the risk.