Data will drive move away from single risk to greater pricing sophistication, says LexisNexis

“Being able to understand consumer behaviour around whether they are leaving the features on tells us something from an underwriting perspective.” Jeffrey Skelton, Insurance UK and Ireland managing director for LexisNexis Risk Solutions.

· Insurers aim for a 360-degree view of the consumer and their risk
· Holistic approach offers indirect growth boost through reinsurance
· Monitoring in-car safety features to drive pricing innovation
· Tangible property data to upgrade geospatial tool risk assessments

LexisNexis looks to a post-COVID-19 world where data and analytics will support sustainable insurance industry growth.

Ensuring there is still a viable economy when the world comes out of the COVID-19 induced stasis is a focus for many in the business world. Life after ‘corona-world’ is certainly something Jeffrey Skelton, Insurance UK and Ireland managing director for LexisNexis Risk Solutions, is thinking hard about. And, he says, the insurance market is heading towards
greater pricing sophistication in the next few years.

“It’s all about getting better at understanding your customers and the risks you’re underwriting. The industry will evolve, or migrate, away from focusing on single risk,” he says.

Rather than underwriting separate policies for people, such as a motor policy and a homeowners policy, insurers are trying to understand the 360-degree view of the consumer and all of their risk, Skelton says.

When a flood happens, he explains, it is not just a customer’s home that is affected—it’s the car that was parked out the front as well.

“The risk exposures are all tied together, they’re not in little silos.”

As a data business, LexisNexis is working to bring together the data it holds with data from insurance companies to pin it all together “so that when you’re pricing the risk you’re looking at the total risk, not just the individual bits”.

New product

Skelton’s UK and Ireland business is working with the company’s US operations to develop this idea into a viable commercial product.

It involves taking known weather-related events and overlaying this information with the actual claims that the insurance companies received and what the payouts were.

“If you look at a series of weather events and all the personal losses, whether they were homeowner or motor, you can bring them all into one view to understand the real risks that are associated with certain types of weather events,” he explains.

“You watch the news and you see all the water, so you know there’s a lot of damage. But what you don’t know is: ‘What was the result in terms of claims? What was filed with the insurance company? What was paid out? How did that affect their expense ratio, their reserving, and then obviously future reinsurance costs?’,” he says.

“If you can understand the past and pull all this data together you can then model it, and the insurance companies can use that information when they’re writing a new piece of business.

“For example, with a house they’ve never covered before, they can better understand how to underwrite the risk. We’re on the cusp of being able to bring to market a new score that will help drive better pricing and risk understanding.”

This shift towards holistic understanding of risk will have another less direct impact for reinsurers and this in turn will drive growth for insurers, Skelton says, as insurers get better at identifying which types of risks they want to specialise in.

“Reinsurers can then respond to that because they will be better able to cope with understanding what the real risk profile looks like and how much exposure there is going to be,” he says.

“Ultimately, if insurance companies are better at pricing, they have a healthier balance sheet, which means they have a better cash flow, and better loss reserving, which means they don’t need as much reinsurance to operate.

“If you’re not good at those things, then you need the reinsurance to cover you because you may be a bit sloppier in some areas than others, whether it’s claims or operating expenses.

“When you tighten all those things down you can use reinsurance as a tool for plain growth rather than a backstop against catastrophe.”

Further advances

This overarching approach is underpinned by other advances the company is working on. Skelton says it has been working on insurance pricing solutions for motor based on the in-car activation of safety features.

“We’ve been working with automobile manufacturers, getting access to the data that’s available on board the car as it is moving,” he explains. This includes data about what features a car is equipped with when it comes off the assembly line—for example, braking assist, lane assist, etc.

“Understanding what is available on the vehicle will help the insurance companies better price the risk. At the time of a claim, if they didn’t know about those features, they may not have priced for a very expensive sideview mirror replacement, for example,” he explains.

“They may think they have a standard piece of equipment for a couple of hundred pounds but then they find out it’s loaded up with cameras and sensors and now it’s going to be a couple of thousand pounds all in.”

This information product is planned to launch in the autumn. LexisNexis already has a couple of customers testing it with a view to evolving the science of pricing and claims control.

Also in the pipeline is research looking at consumers who have purchased newer cars and have chosen to allow that information to be monitored. This will allow data managers to keep track of which of the safety features consumers are turning off.

“For example, there has been a lane assist feature around for a couple of years so that if your vehicle strays out of the lane, the steering wheel shakes. But guess what—that’s really irritating, and people quickly figure out how to turn it off, and a safety feature that should help reduce insurance rates is no longer giving the benefit it was designed to do,” Skelton says.

“Being able to gather this data will inform insurers and manufacturers about consumer behaviour when they’re turning that kind of feature off,” he adds.

“Being able to understand consumer behaviour around whether they are leaving the features on tells us something from an underwriting perspective. If there’s an event that tells us something too. There’ll be a lot of intelligence. Right now designers and manufacturers don’t know because consumers aren’t giving them feedback.”

The enticement for consumers to opt in to sharing their data is still being discussed, although it could simply be lower insurance costs.

Another advance the company is working on involves greater use of geospatial data to help improve property risk knowledge. LexisNexis currently has a visualisation tool which uses geospatial layers to help insurers understand the topography and any other data they want to use to assess exposure.

“The last thing an insurance company wants is to insure every house on the block, especially when it’s in a flood plain,” Skelton says.

The basic layers for the tool are in place and now the firm is overlaying more peril-type information such as construction type and size of building.

“The next evolution is adding what I’ll call more tangible data, such as the number of people living at the property, commercial use at the property that’s not declared, is it a rental that has been not declared, the number of vehicles at that property. So it is taking all the different exposures and starting to layer them up.

“When we are done with our weather work we’ll be able to layer over that score, which will add a little bit more predictive ability to what they’re doing,” he concludes.