Experts criticize industry’s cat modeling practices

Faced with constantly changing predictive modelling practices, brokers are left explaining large rate shifts to bewildered clients.

Property/casualty insurers are making sweeping changes in their modelling practices, increasing their use of predictive modeling in virtually every line of business over the past year, according to a new survey from Towers Watson.

While predictive modelling has been very useful to insurers, allowing them to more accurately price accounts and assess claims analytics, two Towers Watson executives see room for improvement—particularly when it comes to catastrophe modelling.

For one, cat modeling practices change too often, says Towers Watson actuary Ron Kozlowski.

“When one of the large cat modelling firms revises one of their models, you can have a pretty significant impact, say on your one in 200 year PML or maybe even the cost,” noted Kozlowski. “I don’t know if I would call that a problem, but I would call it a criticism of the modellers.”

Furthermore, modelling firms are not uniform in their practices, leading to sometimes wide disparity between carriers’ pricing on an account. That puts wide pressure on agents to be able to explain the complicated predictive modelling process. However, most carriers fail to inform their agent partners of their modelling practices.

In fact, less than half of insurers told Towers Watson they regularly provide insights on modelling to their agents, and just 17% explain their pricing models. Carriers also fail to keep in touch when they make modelling changes, with just 17% reporting communicating upcoming alterations to agents. And just 7% involve their agents in the model-building process.

“There’s a fair amount of disparity between rates that you can get pre- and post-modelling, and even fine tuning predictive modeling practices can cause rates to way up or way down,” Klayton Southwood, senior consultant with Towers Watson, told Insurance Business. “This continued gap in communication puts agents in a position where customers walk through the door and want some explanation of why their rates have suddenly changed.”

The agent communication metric is a new one for Towers Watson, which has been running industry surveys on predictive analytics since 2009. Southwood said the inclusion of the metric was a direct result of what he and other Towers Watson employees had been hearing during consulting assignments.

“We’ve done a couple assignment where the client was having trouble, believing something had broken the predicting model. But most of the time, the modelling itself wasn’t really that bad,” he explained. “It was predicting the experience well, but the breakdown was in the level of communication happening throughout the organization—through marketing, underwriting and the sales force. It’s getting to be a big concern for a number of agents.”

And it isn’t just agents losing out on this lack of communication. Carriers who don’t consult agents when considering predictive modelling could lose out a wealth of information regarding policyholder attributes that may help rates more accurately reflect risk. Southwood likened the advantage to usage-based insurance or telematics, which has helped carriers validate important metrics like mileage.
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