LLMs Will Transform Insurance Underwriting (But Not Just Any LLM Will Do)
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Today’s LLM-based AI solutions boast powerful capabilities that just three years ago were only found in science fiction. Modern AIs, driven by advances in machine learning & computational methods inspired by the human brain, continuously gain new capabilities from the data they encounter, enabling them with previously unattainable potential.
However, when it comes to operating within complex, highly regulated sectors like insurance, not any ol’ AI solution will do. In this post, I want to explore why carriers are turning to a new generation of vertical AIs purpose-built to address the industry’s unique needs and challenges.
Horizontal solutions only leverage the Internet’s surface
“Horizontal” LLM-based chatbots (e.g., Open AI’s ChatGPT or Anthropic’s Claude) are competent at a wide range of tasks, but you’d never trust them to execute a consequential insurance underwriting workflow.
Well, I mean, you could. But your underwriters would still need to engage in dozens (or even hundreds) of rounds of prompts, follow-ups, and clarifications to surface the information they need—all of which would require close review & scrutinization for accuracy, compliance, and hallucinations. They'd need to invest time in sorting through pages of answers to find important facts, correlate & de-dupe information, build timelines, and draw relevant connections. After which, they'd have to relate all of these processed facts back to their risk appetite to evaluate the quality of the risk.
Horizontal, multi-use AI solutions deliver little—if any—operational efficiencies for a complex enterprise use case like underwriting. The industry needs something more from its AI.
How vertical solutions overcome the data dilemma
One key area where general-purpose LLM chatbots and wrappers crucially fall short is lack of access to specialized data. A LLM’s “knowledge” can only run as deep as the data it’s been trained on. With a horizontal solution, you’ve generally been limited by what’s publicly available online. To echo a common observation: these models offer “the average of the internet.” They might be perfectly helpful in, say, planning out a keto-friendly dinner for two, but much less so when it comes to assessing risk signals on insurance applications.
In order to be useful in underwriting, a generative AI solution must have been — as table stakes —trained on informative but isolated datasets such as loss histories. Even anonymized versions of these datasets aren’t available for AI training purposes (they can’t even be purchased).
To access this invaluable cloistered data, an AI vendor must cultivate relationships with specialized data gatekeepers and arrive at a precise alignment on use and security. It’d be impractical for a horizontal AI provider to address every possible enterprise niche. To pry these data doors open, you need highly specialized vendors with a singular industry focus.
Vertical solutions: a partnership of insurance nerds and tech geeks
Beyond special data access, a vertical AI solution is designed to address the highly specific needs of its sector. The complexity and regulations inherent to insurance underwriting require a team that is as well-versed in emerging tech as they are in long standing carrier challenges.
A vertical AI solution likely incorporates a medley of intelligent tools under a single platform umbrella. A foundational LLM, for example, may be tapped for specific functions (e.g., summarization), but higher-level capabilities can only be achieved when the LLM is partnered with purpose-built functionality dedicated to specific tasks (e.g., external data APIs, vector stores, etc.) The solution’s precise structure must be guided by experts with an intimate understanding of today’s industry challenges—and an eye on the ones soon to be in effect.
Keep your eye to the verizon
Horizontal AI solutions are amazing, but they fall short in core underwriting tasks due to their shallow expansiveness; lack of access to specialized data; and ultimately the fact that they’re just one building block that must be partnered with industry-specific capabilities to deliver value to carriers.
