Future of Insurance: How Technology May Change P/C Underwriting and More
With rising inflation and the prospect of a recession on the horizon, the present macroeconomic environment is forcing property/casualty underwriters to adapt to new technologies and sources of data. All the while, policyholders are demanding more from underwriters, whether it’s greater transparency or access to dynamic pricing.
A variety of industry stakeholders gathered on stage at ITC Vegas to discuss the future of property/casualty underwriting, focusing on ways that carriers can better leverage data and technology and engage with customers.
The topic that was top of mind was inflation, which is expected to continue amid supply chain issues and geopolitical uncertainty.
Cameron Talischi, an industry expert at McKinsey & Co., said the management consulting firm estimated $30 billion of additional lost costs in excess of historical loss trends in some of the core P/C lines. Moreover, federal policy decisions in response to recession fears could lead to a drag on demand and profitability in some lines.
With a lot of carriers, current conditions may have “exposed a lot of weaknesses in internal processes, exposed a lot of challenges in some of the data foundations that they have,” said Talischi. “If you can’t get intra-monthly claims data, loss data, it’s hard for you to actually pull off trends at that time scale.”
Adam Ghattas, emerging technology solutions practice leader at Deloitte, said the inflation situation will lead to more pressure on profitable growth. Ghattas cited high transactional costs as an unsustainable expense. “Investments in technology, automation, reducing costs in general, in order to be nimble and survive this market is going to be extremely critical,” he said.
In an economic environment where premiums are expected to increase, there is an ongoing shift from innovation to operational efficiency, said Steve Dowling, GTM strategy at Google Cloud. “From an expense standpoint, it’s really thinking through, all right, how can I run more efficiently and how can I automate the things that I do today,” he said.
Leveraging Data
All panelists agreed that leveraging data is paramount to helping underwriters adapt to the current market and beyond. Speakers also drove home the point that there is no one-stop-shop automation model when various segments and lines of business differ so much depending on individual state regulations.
Google Cloud has been at the forefront of manufacturing its own data and distributing information in a business applicable way. Dowling credits the cloud for helping carriers shift away from “shackled” data they might have in a mainframe or legacy system.
“With the Cloud, what that really does is it creates that agility and flexibility to make real-time decisions, because historically insurance has been relatively slow,” Dowling said. “So how can we get more proactive in some of our decision making?”
Once predictive analytics are in the hands of underwriters, they turn into “insurance heroes,” said Jeff Heine, chief revenue officer at Betterview. Heine sees underwriters’ ability to share data with agents and policyholders as a crucial step in developing profitability and consumer trust.
“The hero part is their loss ratio, with the information we provide, generally goes down significantly but their relations are stronger,” he said. “And you look at the non-renew rate, it’s less than 2%, which gives you a really good idea of what you can achieve with the type of insights we provide, in the market that we provide.”
Procuring and distributing data is not a one time and you’re done process, however. Ghattas recalled several conversations with clients who implemented an AI model and asked, “Am I done?”
“What’s the opposite of AI? It’s IA, which is internal audit,” Ghattas said. “It prohibits progress by looking at that one model without building a system or a culture that would enhance that change.”
Instead of seeking a one-time transformation, carriers are taking a selective approach to best fit their needs.
“What we are seeing in the market is, it’s not about getting one product or one entire thing which is best in everything, but rather, picking and choosing each vendor who is best of the beef in that particular space,” said Kanisha Khaitan Agarwal, insurance core and emerging technology at Deloitte. “Whether you start from submission intake, or you move to rating, or you move to post-production transactions, or even the course for data and customer salutation.”
Automation Here to Stay
Max Drucker, CEO of Carpe Data, doesn’t have to look far in the past to see the way automation transformed a core P/C line. Auto insurance became a fully automated product with the use of automated credit scores, vehicle reports and loss history.
“What we’re doing and what you look at other companies seem to do is, [ask] what are those critical data elements that will unlock that automation for other lines like small commercial, for example?” Drucker said. He added that having great consistency and compliance remains critical to success but that ultimately operational efficiency, especially with inflationary trends, are critical for a carrier to succeed.
The demand for automation in lines like small commercial, middle-market and personal lines is accentuated by an aging workforce and a shortage of skilled talent, he said.
“Nobody’s thinking about, how can I hire a new army of underwriters?” he said. “There’s no carrier that is ever going to say that. The impact that can be driven by using data to be able to automate those processes is profound.”
In the next five years, Drucker expects underwriters in small commercial to consider a business’ online reviews to determine whether they’re likely to incur losses or not.
While Drucker acknowledges that a Yelp score, for example, isn’t predictive of anything, aggregating social data across a segment can be an effective proxy for how well a business is running.
“I get asked questions all the time, ‘Well my brother-in-law opened his restaurant, and he had all his friends write reviews,'” Drucker said. “And my response is, that’s probably actually a good risk, right? The insurer’s looking to who’s going to have a loss or not. And if that brother-in-law cares enough about that business that he hired some firm to juice up his results or have his friends do it, or whatever else, he’s probably doing all the other right things, too, to make that business be successful.”
Talischi also sees AI changing the way small and middle commercial lines are underwritten. He anticipates automated data as a way for carriers to develop more uniformity for how underwriters approach exposures. Empowered by AI, underwriters operating in more complex levels of commercial lines can turn to troves of information when determining whether to write a policy or deciding what premium to charge.
“Take mid-market as a common example,” Talischi said. “It’s a segment where you often find generalist population of underwriters that have to write this across a multitude of industry classes and lines of business. They’re not specialized. And typically, you think about risk in very different ways, right? So, there’s lack of consistency.”
One idea that’s receiving traction, he said, is carriers determining an institutional view for a given type of risk. Across lines, what matters as an institution and what factors should underwriters be on the lookout for? “Really embedding in dynamic workflow that sort of guides the underwriter through the thought process and brings to bear data at relevant points in time,” he said.
A bubbling undercurrent of the session was at what point does automation overtake the core responsibilities of the underwriter. Talischi reassured the audience that data exists to better inform underwriters, not to constrain them. “They can actually still exercise judgment and overrule,” Talischi said.
What was evident by the end of the session is that pressure to turn in profitable growth amidst a worsening economic market will force carriers’ hands to embrace automation more readily in the coming months and years.
“We now live in a world where data is constant, it is fluid, it is continuous, and there’s tremendous opportunity to leverage that,” Drucker said. “Both across the same cycle, across the underwriting cycle, across the life of a policy. This should be evolving.”