Parametric insurance – a long history, a bright future

Parametric insurance is nothing new. But the products first dreamt up 200 years ago are an entirely different beast to the sophisticated, data-driven, bespoke offerings available now.

Sitting alongside traditional products, they allow corporates to access cover for defined risks and fill protection gaps in an increasingly risky environment.

The earliest examples of parametric insurance date back to the 1800s. The Hamburger General-Feuer-Kasse [Hamburg Fire Office] in 1817, for example, gave landlords the option to purchase loss of rent coverage as a supplement to fire insurance. Like a lot of early insurance, the first parametric covers were structured more like a wager – both sides betting against the odds of something happening.

It wasn’t until around the late 1990s that Swiss Re and other mainstream insurers started offering parametric products. These were much more sophisticated and created as an alternative approach to risk designed to sit alongside traditional insurance products.

“The birth of the modern parametric was largely driven by a demand from larger clients for a faster claims processing time, more flexible protection and greater certainty around pay-outs,” Jan Bachmann, Head Innovative Risk Solutions, EMEA, Swiss Re Corporate Solutions, explains.

“Banks, for example, wanted to have cover for their mortgage portfolios in the instance that the properties themselves were destroyed.”

Swiss Re’s first parametric products were created to provide additional earthquake cover for businesses.

The global parametric industry generated USD 11.7 billion in 2021, and this could rise to USD 29.3 billion by 2031. The interest in parametric solutions is on the rise – as of August 2022 Swiss Re Corporate Solutions had seen an increase in parametric product sales of over 40% compared to 2021.

“The parametric market is growing on a daily basis and it’s bigger than anyone expects. It makes traditional insurance more efficient,” Bachmann confirms.

Nowadays, parametric insurance is being used for everything: whether coverage for waterfront hotels in the hurricane-prone Caribbean, offshore platforms in the Gulf of Mexico, or hedging lower retail revenue after major earthquakes. We’ve also helped cover public sector assets for storm damage, car dealers for large hail, and bolster benefit programmes so companies can assist employees and their families following disruptive natural catastrophes. See examples of how parametric insurance can help.

Usually, parametric insurance is linked to data provided by a renowned and independent third party, such as the US Geological Survey or the US National Hurricane Center. This allows insurers to establish some baseline ‘norms’, and use these to set up parameters that, when breached, will trigger payment.

Earthquakes, hurricanes and other natural catastrophes (Nat Cat) are comparatively easy to create parametric products for because there is lots of historical data – this includes things like seismic measurements, wind speed information, or storm tracks.

Hydrological events, in particular flash floods, are harder to account for because of how transitory they are. At Swiss Re Corporate Solutions, we are now able to extend our modelling beyond the traditional calculations based on flood plains, but it is still a harder proposition than some other Nat Cat.

The increasing severity and frequency of these events, coupled with the far-reaching supply chain impact of some large Nat Cat, have put parametric insurance higher up the corporate agenda. This has stimulated more interest in the parametric market, from the insurance sector in general. But if these products are going to provide the strength of cover they were intended to, it is important they are built on strong data and sophisticated modelling. Without this expertise they will not provide a proper solution.

Another area receiving a lot of attention, particularly since the pandemic, is business interruption cover. Covering the full fall-out of an event can be tricky on the traditional market, particularly when the damage is financial or reputational – rather than physical – because of delays and other issues.

There are also a growing number of risks that can no longer be covered on the traditional insurance market because there have been too many historic losses.

This is where parametric products can provide you with alternatives and workarounds.

An example of this is cover for overhead wire damage (T&D lines). Companies were struggling to find an insurer to underwrite the risk because of the high frequency with which this can happen.

A root cause of much of the damage is wind – something we have a lot of data on.

Swiss Re has established a bespoke product based on wind thresholds and recurrence periods, which enables us to come up with an appropriate price for the risk.

Parametric products are currently the preserve of sophisticated corporates. In future, however, they are likely to be increasingly used to cover smaller risks, like those faced by homeowners. And semi-automatic products could make a basic offering scalable.

As data becomes increasingly available and sophisticated, this is opening up new ways of gauging risk.

But it is also worth noting here that climate change is affecting our modelling – we can no longer put too much emphasis on historic data.

We also need parameters or indexes for the client’s business, too – that’s how we gauge how they might be suffering above or below a certain level.

Typically, data needs to come from an independent third party, but the insurance industry is becoming increasingly at ease with using data from its clients, which can be very precise. This offers new ways of indexing.

Unlike traditional insurance products, which have a fully-fledged predefined catalogue of what information is needed from a client, parametric products can be more flexible.

For example, if clients don’t want to tell us their turnover, we can work with information about what they expect to be reimbursed in the case of an event.

We can also be creative when it comes to how we measure an event. Phone signal data can be used as a proxy for footfall data, for example. And such information helps assess how busy a location such as a shopping mall is. We have used variations of this approach to establish the impact of railway station closures on the shops and businesses nearby.

So, in this way, parametric insurance is expanding the bounds of insurability. It is continuing to evolve as our data sources expand and become increasingly accurate.

And it is no longer an outside product limited to sophisticated clients. As the risk landscape evolves and hardens, it will become a key tool to allow businesses to respond.