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Covid-19 – Insurance innovation your time has come

Insurance has a fatal flaw. Few of us want to be reminded of how dangerous the world is. Cars crash, buildings burn, accidents happen. Usually to other people. So unless we are highly sensitive to risk, unusually thoughtful about the future or regulation requires it, we don’t care much about insurance.

Last Wednesday that all changed. The WHO declared Covid-19 a pandemic. Suddenly we’d lost 20% of our savings, the rest of the world didn’t want to see us, most events planned for the coming months were cancelled and it pushed everything else off the BBC evening news. Now we care.

For the last five years, the celebration of the emergence of innovation in insurance and the invention of “Insurtech” has had to battle with a fundamental problem. How to change an established industry, reliant on legacy, which most people don’t really care too much about and which is, most of the time, good enough?

Successfully driving any change without a major shift in how we see the world is really hard. Often we need a dramatic shock to the system. Our view of how our lives might change – for better or worse – radically alter if we directly experience disasters (personal, national or global).

The emergence of new technology can also drive massive changes. Sometimes very quickly. And not just recently. The Liverpool to Manchester Railway opened in 1830. Within three months over half the twenty-six horse-drawn stagecoaches on the route had gone out of business.

Covid-19 will bring many challenges, but it may be the reset button for insurance innovation. It’s happened before. Hurricane Andrew hit Florida in 1992, the most destructive hurricane ever to hit the state. The insurance claims bankrupt 12 insurance companies.

Soon after, the insurance rating agency A M Best required every insurer to prove that it had sufficient capital to withstand a “one in a hundred-year” loss. No actuary had enough claims data to figure that out.

Andrew, and then the California Northridge Earthquake in 1994, gave birth to the specialised techniques of catastrophe modelling and led to the founding of RMS and AIR (now part of Verisk).  

The power of first-mover advantage, and the difficulty of building credible catastrophe risk models, is demonstrated by the fact that almost 30 years later both companies still dominant this space, with combined revenues of around $500 million.

Fast forward a decade or so. Despite 2019 being a record year in funding for insurance technology start-ups and scale-ups, with over $6bn invested, it’s getting hard for some of the most well-known business ideas to gain traction.

Trov and Wrisk have announced recently they are shifting from being insurers (or more accurately MGAs) offering contents or device insurance, to becoming platforms. Their clients will now be other organisations with established insurance offerings or existing distribution and customers.

Lesser-known companies have quietly packed up, or are stuck in Insurtech zombie land, never quite launching. Other well-known entrants such as Bought by Many and Lemonade appear to be doubling down on pet insurance. A perfectly acceptable strategy, but a future defined by our love of furry animals is not quite where were many people expected us to have got to by 2020.

That’s why innovation is really hard. We may have heard of the H1N1 variant known as Spanish Flu from 1918, but until we started to experience the impact of Covid-19 virus, few of us gave much thought to the possibility that a pandemic was something we would need to deal with in our own lives.

I haven’t done a comprehensive search of Google, but I’m struggling to find any Insurtech like company that has been building solutions to model the risk of pandemics. 

A quick editorial note here. I write “Insurtech like” because there is no universal agreement on what the word actually means these days. I’m using it here as a shorthand for any company launched within the last 10 years or so that is using new technology or data or analytics to help with distribution, pricing, risk management, claims and probably a lot more.

Please don’t quote me on that definition though – the topic probably merits a full article in itself and I prefer Andy Yeoman of Concirrus’s definition when I interviewed him last week. “Every insurance company is Insurtech, some just have a bad tech”. But I digress.

RMS started building pandemic models in 2012 to help price “excess mortality”, a polite actuarial term to describe too many people dying at once. The idea was to help insurance companies manage their capital and get access to tools to help them buy reinsurance more effectively.

The problem was that the rather simplistic capital models accepted by the regulators gave a lower risk price, and less capital requirement, than the sophisticated RMS models, which ultimately would have led to more costs for the insurers.

There wasn’t much interest from the catastrophe bond market either. There are a couple of parametric bonds in place just now, but few companies really worried enough about pandemics to justify the cost of buying protection. 

Find out more about what RMS is up to from Robert Muir-Wood, Chief Risk Officer, in our Pandemic Podcast Special (see below).

Metabiota, another San Francisco-based company, founded in 2008, uses real-time data collection and analytics to model epidemics. A partnership was announced with Munich Re in 2016 to develop models and insurance solutions for property and casualty insurance designed to mitigate the economic losses caused by epidemics.

Marsh has tapped into the Metabiota and Munich Re relationship to create PathogenRX. According to its website this is an index-based insurance that offers protection to US clients against losses resulting from a pandemic or epidemic impacting international travel, study-abroad and research programmes.

I’m not sure how successful this has been (watch this space) but anyone that has bought the cover is going to feel pretty smart just now. Techcrunch mentions that Metabiota is also working with the African Risk Capacity (ARC), the agency using parametric insurance to provide cover for a number of African countries. 

By the way, if you don’t already know what an epidemic is, it’s a sudden increase in the number of cases of a disease, more than what’s typically expected for the population in that area. A pandemic is an epidemic that has spread to several countries.

SparkBeyond, an Artificial Intelligence company formed in 2013 that I spoke to recently, has been commissioned by one major country to help it understand how to use analytics to minimise the pandemic spread.

The company operates across many industries so it’s not really an Insurtech (by whatever definition you use) but does hint at what could be on offer for those currently in the insurance world.

One system shock that may give the London market the jolt it needs is the potential for Lloyd’s to close for an extended period, forcing insurers and brokers to exchange risks electronically.

The market shut for the first time last Friday for one day to test its resilience to a longer shut down and at least one London company, Canopius, has announced that it is asking all staff to work from home starting Monday 16 March.

The recently launched PPL system for placing insurance contracts may not work as smoothly as it needs to, but it’s unlikely that the Lloyd’s market could ever have contemplated working remotely without it. 

And so as we start to understand the far-reaching implications of this pandemic, and adjust our lives to cope with it, it’s worth remembering that with every crisis comes an opportunity.

I was working the phones this Thursday, speaking to some of the experts from modelling, medicine, insurance, supply chain and AI to help put some context around the news and record their insights for this weekend’s pandemic podcast special.

I explored what has been done around analytics and what could still be done in order to give some pointers to those of you looking for new business ideas or even just consulting work. I asked what the insurance implications would be, and I discovered how vulnerable the supply chains are.

I found out that there are massive amounts of data available related to the pandemic, much of which is open source and I reveal where to go to get the best insights.

The podcast is number 72 in the InsTech London series. Its 40 minutes long and a chance to hear what Robert Muir-Wood (RMS), Doctor Chris Martin (medical), Nick Wildgoose (supply chain), Sam Casey (Insurance Insider) and Alex Easaw (SparkBeyond) have to say you can find it at any decent podcast channel (search “instech london”), or listen now in our podcast section.

Of one thing we can be sure, however the world looks in a few months’ time, we are going to be thinking very differently about the threat of pandemics and what this means for insurance. 

Unfortunately, for many people and companies, insurance cover will be found to fall short of expectations in compensating losses and when life returns to normal we might see a fundamental rethink of what insurance is all about.

But maybe, at last, we can move beyond accepting that pet insurance is the best we can do when it comes to introducing impactful innovation into insurance.  

Find out what I’m up to from my profile and what I’m thinking and learning from my previous articles. Enjoy our past events, podcasts and see all the great companies supporting us at www.instech.london.

For a weekly dose of what’s fresh and relevant in data, analytics, insurance and yes, even Insurtech, sign up for our weekly newsletter – handcrafted by the Instech London team and buffed and polished by me every week.

This article is now available on the Insurance Day website or as a downloadable PDF. Thank you to Simon Hayes and NextGen Communications for your support. 



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