Insurance is hard (harder, arguably, than any other sector) because we don’t know the price of the product before we sell it. That causes price cyclicality. When you don’t know how far you’re cutting into the margins, it’s easy to shave a bit more off the price to look competitive.

Solving the cyclicality problem would be hugely beneficial for our investors and, more importantly, our customers. To do that, we need to be able to pinpoint (or at least come close to knowing) the actual cost of each risk before we price the coverage.

Systems can help. Pricing is already one of the most important areas where insurance technology is making an impact.

Until time-travel tech is invented, computers will never get us to a place where we know with certainty the cost price of an insurance product before the policy has expired. But in the meantime, technology – when combined with another critical commodity – can get us very much closer to The Right Price.

That commodity is data.

Acting together, data and technology can do wonderful things. For example, in combination they can give us a very much better idea about the probable impact of climate change on the likely frequency and intensity of severe convective storms in a particular location.

That insight, in combination with more data and technology, can help us to understand the damage a specific imagined storm would inflict on a particular, actual portfolio of insured assets. With that we can load pricing for changing tail values at risk with very much greater levels of confidence, and move a step closer to The Right Price.

Getting the technology right is challenging enough. Many Diaries passim focus on that. But what about the data? If we have any hope of getting to The Right Price, we need to overcome the big data challenge. To achieve that lofty goal, we need a different approach to data.  

Last week I read an excellent article by Joe Zuk from Altamont Capital. In it he outlined the insurance industry’s typical “Fortress Model” for data. “The assumption was that whoever had the most data would win,” Zuk wrote.

Insurance companies typically protect their data like Colonel Sanders guards the eleven herbs and spices.* They add to it where they can, then lock it up in their Fort-Knox-like data warehouse.

Those that have it but don’t use it tend to sell it to others who want to add to their stockpile of bits and bytes. When I was Chief Underwriting Officer at a multiline MGA, brokers spent a lot of time trying to sell me data. They had a lot of it, almost everyone wanted it, and quite a few risk carriers were willing to pay.

Zuk challenges this whole approach to data accumulation and storage. He declares: “Owning data is no longer the primary competitive advantage. The future belongs to those who can effectively access and orchestrate it.”

He goes on to describe a market where data ecosystems are preferred to fortresses: “This shift requires more than just technology; it calls for a new culture… Modern insurance innovation increasingly depends on the ability to integrate diverse datasets, partners, and tools through open interfaces and shared standards. It emphasizes partnership over proprietary control. The competitive edge lies in developing the infrastructure and governance frameworks that allow hundreds of datasets and services to work together.”

This is music to my ears. For “innovation” above, substitute “pricing,” and we’re getting close to something rather desirable.

To make the most of the information age – which is code for getting as close as possible to The Right Price – we need to share data in common formats (Oasis provides the standard we all need, as well as a terrific example of an ecosystem, but that’s another Diary entry). We need to do so not by treating data as a commodity to be mined, sold, hoarded, and protected, but as a shared club good within our ecosystems.

We can only ever hope to approach The Right Price on a regular and consistent basis, and get rid of the troublesome insurance pricing cycle, when the market has pretty much the same information. Then, only the way we use it will distinguish us.

Claude Shannon, the Father of Information Theory, was a maths genius and technology pioneer, America’s Alan Turing. Shannon postulated (roughly) that a perfect market can exist only when everyone has the same information, and acts on it accordingly.

Applied to insurance, it mans that to get to The Right Price, everyone needs to have all the available data. No one can get there on their own.

When we all have all the information, competitive advantage will be created by our ability to interrogate and enrich the data in creative ways that deliver valuable insights into individual risks. When we use that knowledge and more technology to show how each well-defined risk relates to our distinctive corporate risk appetite, and how if acquired it would interact with our existing portfolio, we can create intelligent – and tangible – price advantage.

Companies that don’t use all the data in this way, protecting their margin by getting as close to The Right Price as all the available data allows, will surely burn their capital with astonishing speed (or, alternately, they will never sell anything).

When we share and use data in this way, we stand a chance of banishing price cyclicality, or at least narrowing it significantly. At the same time, we will make insurance quite a bit easier.

* For the record, Colonel Sander’s 11 Secret Herbs & Spices are salt, thyme, basil, oregano, celery salt, black pepper, dried mustard, paprika, garlic salt, ginger, and white pepper.