The S curve – the effect of wealth on insurance markets

The global insurance industry is not fulfilling its potential - many companies and individuals are underinsured for key risks. In less developed countries, losses from natural catastrophes can be almost totally uninsured. Last month, Swiss Re released a report that plotted the complex relationship between insurance penetration and GDP.

"I often hear naive comparisons where insurance penetration in advanced economies is X percent and in Tanzania or Kenya or India it's only 0.7%," says Daniel Staib, senior economist at Swiss Re. "You have to take into account disposable income. We can see that a lot of nat cat losses are not insured. This is certainly an opportunity."

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Staib is one of the authors of Swiss Re's latest survey of the global insurance industry. For him, the S-curve demonstrates the empirical relationship between disposable income and insurance penetration (insurance premium divided by GDP). A minimum GDP per capita of $5,000 appears to be the magic number at which insurance take-up really picks up, as this reflects the growth of an economy's middle class.

"For low income countries we see an elasticity between insurance and GDP of around one which means insurance market growth is at the same pace as GDP," he says. "But if we go beyond that threshold of $5,000 to about $35,000 we see the elasticity is much higher. It could be close to two where insurance market growth is twice as fast as GDP growth."

"This is different from country to country and that's where you have a middle class growing," he continues. "This is the part of the population that have insurable assets - they start building houses and owning cars - and they also have a need to protect their family against loss of income as a result of illness or death."

"When you look at China it is really moving up along the S-curve on the non-life side particularly in the last few years," he adds. "A big driver is motor insurance because it's worth 80% of the non-life premium. And of course the [insurance] regulator in china is very active - for example they have really pushed the development of the agricultural insurance market."

While China currently sits right on the S-curve, for many other markets there is a substantial deviation. There are a number of different reasons for the scatter graph, including low take-up in Muslim countries, comparatively undersized motor insurance markets in small city states such as Hong Kong and Singapore and countries where there is a high degree of social security and state subsidies.

Staib points to Italy as a country which has a large reliance on the government to step in post-catastrophe and which, as a result, has a low take-up of residential earthquake cover. Indicative of this are the losses from earthquakes in L'Aquila in 2009. Economic losses for the 2009 event were estimated at €10 billion, while claims were just €250m.

A catastrophe pool that encourages or mandates homeowners to take out insurance, including earthquake cover, is one solution for such markets, with Staib pointing to schemes in Turkey and Romania as examples. It is understood such as scheme is currently being mooted by the Italian government.

The S-curve in non-life insurance demonstrates a clear pattern between insurance penetration and GDP growth. While insurance take up increases substantially at per capita incomes between $5,000 and $35,000, beyond this level in the advanced economies insurance growth flattens, even stagnates.

This trend was exacerbated by the financial crisis, according to the report, on both the life and non-life side. In Europe in 2014, for instance, non-life premiums in advanced economies were just 0.5% higher than their level in 2007, the weakest gain over the seven-year period of any region. Even in emerging markets, average annual premium growth has been slower than in the pre-crisis years.

Posted: Monday, July 13th, 2015