What he may not have realised, though, is that much of the work he mentions is already being done. There is a growing number of - like ourselves - which seek to use a combination of data, customer focus and persistence to solve problems – and it’s working.
But it’s crucial that the rest of the industry catches up. The public perception of insurance leaves a lot to be desired, and this is particularly true post 2008. However, insurance is a key foundation on which the rest of the economy is built. Society wouldn’t be able to function in the same way without it and, in an even more practical sense, it is responsible for 315,000 jobs.
So why do customers think so poorly of it?
There are some great insurers and brokers out there, but sadly they are the exception to the rule. All too frequently, these businesses are not customer focused – even more often, they are not tech led. There has not yet been the recognition that the proper application of technology can provide transformative benefits for customers.
Data science can deliver better products, better service, and better price points – and yet the industry is digging in its heels.
For an industry like insurance, this is of course surprising. Insurance is built on data, but the old school actuarial models on which the industry relies must be updated for everyone’s benefit. Actuarial science is ripe for an update, but that relies on a sea change in the perception of technology.
When I began in this industry six years ago, business insurance was one of very few industries that hadn’t seen a first wave of tech disruption.
This was primarily because of the complexities of the products. Personal lines had already been caught up in the wave of aggregators, but it is clearly more difficult when you’re developing products for hundreds, maybe even thousands of trades.
But the problems aren’t intractable.
Through the application of cutting-edge data science techniques, and by remembering that the end goal is a better offering to the customer, we can transform the industry through tech.