Crossing the data divide – how the UK and US insurance markets compare


Authored by Jeffrey Skelton, Managing Director, LexisNexis Risk Solutions, Insurance, UK and Ireland

As a veteran of the US insurance market and prior to that, a financial regulator for the sector, now living and working in the UK, I am often asked to draw comparisons between the two insurance markets.  

All insurers share the need to understand risk to underwrite effectively and manage claims. So there are a lot of parallels between the US and the UK. Obviously both industries are trying to do the same type of service for their customers. But there are some critical differences, and the differences lie in the types of risks they face, the regulatory environments in which they operate and the way each market leverages data to support underwriting and pricing functions.

The US experiences a very strict regulatory environment, where insurance companies do not have freedom to change rates when they want to. The US market has 50 regulators, one for each state, compared to one for the whole of the UK.  Pricing changes need approval from each regulator which has the effect of making the US far less agile in its pricing adjustments than the UK. 

What I have found here in the UK is there's a much more dynamic marketplace. Insurance providers are able to use data and deploy it to change rates across distribution channels, change rates literally from day to day, if they wanted to. They're able to use data to respond to market changes and change rates along the way.

The UK is not only more dynamic in its pricing but the use of data is far more sophisticated than the US. The application of predictive analytics to understand the risks related to cancellations and named drivers are good examples, mobilising the data to continually implement rate changes and tweak the profitability or tweak the risk profile.

In contrast, the US insurance market has access to far more data. That’s not just because there is a much larger volume of policyholders, in the US, the use of detailed prior claims data is standard and it’s also critical to how the market writes risk.  LexisNexis Risk Solutions has been supporting this in the US for about 30 years.

Claims data provides a much greater understanding of the nature of prior claims – the circumstances, the settlement, the parties involved.  This data is contributed by the whole of the market and on the cusp of being replicated in the UK for home and motor.

Richer claims data can then allow for greater pricing segmentation, and a better opportunity for those consumers with the right kind of claims history to actually benefit. That process is not something as simple as, "Has this prospect had a prior claim or not." But it can drill down into, what type of claim? When was the claim? How was the claim disposed? All of these things really speak to people's behaviour. And sometimes consumers with prior claims are excellent risks and should be given the opportunity to benefit from that in the form of lower premiums.

In the US, there is also much greater data cross-fertilisation across different lines of business.   An underwriter is permitted to use motor policy and claims history to help understand risk for home insurance – and vice versa.

Motoring violations is another key data source used by the US market to help rate for motor risk.  Again, consider that there are 50 states each with a different way to describe each motoring violation.  This amounts to over 2 million types of offences.  LexisNexis Risk Solutions normalised all of that data down to 587 codes and descriptions, which are now used as standard by insurance providers across the US.

Normalisation sounds a little dull for a process that has become fundamental to insurance.  With the increasing volume of connected things, we are facing a data deluge and the only way to make sense of that data to help consumers benefit, is through normalisation.

In the US and Europe, we have spent 6 months normalising data regarding which Advanced Driver Assistance Systems (ADAS) are equipped on vehicles so that the market can start to price for the presence of in-car safety features. The next step will be normalising dynamic data from the connected car, leveraging all that we have learnt and developed for telematics insurance. There is a global need for this data so this is certainly an area where geographical differences will become less marked.

The home market is not moving at the same pace of change as motor – the biggest difference is the price paid for insurance. Home insurance costs are low here in the UK whereas in the US, due to the extreme weather experienced across the country, the average premium is £1,200.  Given the extreme flooding this winter in the UK we could soon see pricing strategies change and geo spatial data, data visualisation combined with property and claims history data can help the market through that process. 

In the final analysis, insurance companies want happy customers. They want customers who are going to be profitable. People who will stick around for a long period of time, who will not file a fraudulent claim, who will pay their premiums on time. All of these attributes are really what creates a win-win environment for everybody. And it really comes down to having accurate and dependable data so that all of these promises can be delivered on.


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