November 2025 ITL FOCUS: Underwriting

ITL FOCUS is a monthly initiative featuring topics related to innovation in risk management and insurance.

underwriting

 

FROM THE EDITOR

While I’m generally allergic to the terms that consultants concoct—“decisioning" can take a long walk off a short pier—I’ve come to like a recent coinage: the “zero office.” It’s highly appropriate for this month’s focus on underwriting.

The “zero office” refers to the idea that AI can take over all the functions of the back office, including at insurance companies. A “zero office” would not only provide radical efficiency but let underwriters operate closer to the speed that customers increasingly demand—and that competitors will provide if you don’t.

I know the “zero office” sounds harsh. Nobody wants to think about wiping out all sorts of people’s jobs. A truly “zero office” is also not practical for now, either, especially given generative AI’s well-known hallucinations. In the late ‘80s, when personal computer enthusiasts gushed about the prospects of a “paperless office,” I quoted an analyst in the Wall Street Journal who said, memorably, that “the paperless office is about as likely as the paperless bathroom.”  Offices still produce loads of paper more than 35 years later, and there will still be lots of people in back offices decades from now.

But, but, but… the “zero office” is a useful guide for thinking about how the insurance industry can operate. You can be sure that lots of insurtechs are at this very moment pitching venture capitalists about “AI-native” this, “AI-native" that, and “AI-native” the other thing. I heard just the other day from an “AI-native TPA”—and a pretty impressive one, at that. As all these folks are envisioning how to take all the clerical work out of every aspect of insurance, including underwriting, you should, too. Then you should do it again in a year, and a year after that, because possibilities for efficiency will keep presenting themselves as technology improves and as you move up the learning curve.

For now, I encourage you to read this month’s interview, with Balázs Kaman, head of product at BindHQ, who details just how much efficiency is now possible in underwriting, how his company has tapped into the possibilities—and how important it is.

As he notes, the efficiencies that AI allows make it possible for underwriters to respond far faster. “What used to take maybe days can now be handled immediately or can at least surface a preliminary price or rate, so you can then come back with a more polished rate after all the underwriting was taken into consideration,” he says.

He adds: “Speed is the name of the game.”

Cheers,

Paul

 

 
An Interview

Speed Is the Name of the Game

Paul Carroll

What are the main challenges in underwriting today, and how might emerging technologies address these issues?

Balázs Kaman

One of the biggest challenges in underwriting today is simply getting the right data into the system. Many of our MGA customers underwrite highly specialized risks such as crypto exchanges, mining rigs submerged in the ocean, or electric vehicle chargers. The prerequisite for accurate underwriting is having high-quality data available for rating, but collecting and structuring that data is still painful and time-consuming.

Over the last decade, the industry tried to solve this by pushing data entry downstream and asking agents or insureds to fill out information directly in portals. With AI, we now have a better path forward. Instead of changing long-standing submission behaviors like sending emails, AI can extract and structure that data automatically and trigger the necessary workflow steps. That allows underwriters to spend less time rekeying information and more time focusing on evaluating risk.

read the full interview >

 

 

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Insurance Thought Leadership

Insurance Thought Leadership (ITL) delivers engaging, informative articles from our global network of thought leaders and decision makers. Their insights are transforming the insurance and risk management marketplace through knowledge sharing, big ideas on a wide variety of topics, and lessons learned through real-life applications of innovative technology.

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