The fast-changing risk landscape should not worry the insurance industry – we’ve been here before.
It’s sometimes said that we are living through an ‘era of uncertainty’. But what does this really mean for insurers and reinsurers?
Clearly there are many uncertainties, economic, political and social, as well as new risks and exposures. But the reinsurance industry has always faced a level of uncertainty.
Our uncertainty is not unprecedented. Other times saw existential threats to elements of the market. And, of course, while uncertainty in the world can create short-term problems, in the longer term it creates opportunity for the reinsurance industry.
The industry has evolved as risks have emerged. In the 1980s, there was the first casualty crisis of the modern era, and the industry evolved and changed and ultimately responded to the challenges.
In 1992, there was a catastrophe loss that was multiples of what people thought was the worst-case scenario.
In the late 1990s/early 2000s, there was a second casualty crisis followed closely by the impact of the 2004/2005 hurricanes, which changed things again. And of course, there was 9/11, and the response created the vibrant terrorism insurance market that we have today.
In the aftermath of the 9/11 tragedies, it was very difficult to get terrorism coverage, but, maybe just a couple of years later, capacity was deployed in the (re)insurance markets to create the products that are now second-nature.
Similarly, catastrophe coverages evolved in the wake of Andrew in 1992, the storms of 2004, and then Katrina, Rita and Wilma.
Sometimes there might be a period where the market doesn’t respond immediately because it is trying to re-calibrate what the risk/reward equation is. But fairly quickly the market usually finds a way to create opportunity out of these situations.
Analytics and modelling
The rising use of analytics and modelling has enabled the industry to quantify uncertainty. It helps companies to think through decisions about what risks to take on, what risks to hold, and what risks to transfer.
Catastrophe modelling helps companies to quantify what their exposures might be. It also reduces the level of information asymmetry between counterparties in a reinsurance transaction. When both sides have a fairly good feel, on a relative basis, of what the risk components are, and both feel they are working off similar numbers, it provides a level of confidence in that transaction.
The flipside is that sometimes companies can become too reliant on the models and the output, instead of thinking about the real-world applications of some of the conclusions.
We have seen companies whose capital models have shown a diversification benefit but, when the losses actually happen, the impact can be quite unexpected compared to the capital model. The market reaction or the rating agency reaction can be different from what the models may have suggested.
Models are a tool – they are not necessarily meant to be something on which to rely exclusively. Analytics is not a substitute for common sense.
We don’t know what the next risks will be. They may be cyber, floods or mortgages, but clearly the risks will evolve and, to date, the industry has done a pretty good job of meeting its challenges.
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For further information please contact Ed Hochberg on +1 215 309 4520 or email firstname.lastname@example.org.