Recent hurricanes have brought widespread attention to the insurance industry and the final bill it faces for the rebuilding operation. Here at MS Amlin we are working to understand the potential problems of relying too much on models to assess risk and whether they might pose a threat to the system as a whole.
The devastation left in the wake of hurricanes Irma and Harvey have reminded us all of the power of nature, its impact on people’s lives and livelihoods.
It’s also put the insurance industry under the spotlight.
The full extent of the damage, and therefore the final cost for insurers and re-insurers, is unlikely to be known for some time, but it’s certain that the losses will be significant, and may well have a longer-term impact insurance market as a whole.
It will inevitably reignite the debate about how much climate change is to blame for the force and frequency of such weather-related catastrophes. And, of course, whether we only have ourselves to blame for the changing climate
Less likely to be debated is the social role insurance plays in our lives. After all, it is insurance that oils the wheels of the whole recovery process.
So it’s more important than ever that we have a robust, sustainable insurance industry that can cope with the demands made on it.
We all know what happened when the banking industry took risks they didn’t understand, using tools that were flawed. The effects of the 2008 financial crisis are still being felt today.
Given the critical role insurance plays – not only in financial markets, but more broadly in people’s lives – it’s crucial that we have an insurance market that works.
One of the lessons learned from 2008 is the danger of over-reliance on models, and prompted MS Amlin to commission research into the relationship between models and the underwriters who use them.
The aim has been trying to deepen our understanding of the systemic risk of modelling. Our ground-breaking work with the Future of Humanity Institute at the Oxford Martin School laid bare the potential risks of over-reliance on models.
After all, as our original report pointed out “the catalyst for this financial meltdown was the bursting of the US housing bubble which peaked in 2004, causing the value of securities tied to the US housing market to plummet and damage financial institutions on a global scale.”
The value of these securities was based on modelling assumptions that were fundamentally flawed. And since everyone was using the same models, the consequences spread across the market.