Meet the First AI Accuracy Validator Built for Insurance Underwriting

Today, we’re excited to introduce the first-ever AI Accuracy Validator built for insurance underwriting. 

This application provides our commerical insurance customers with a transparent and comprehensive way to evaluate Sixfold’s accuracy—reinforcing our commitment to bring reliable and trustworthy risk assessments to underwriters.

Why did we build this?

For an AI solution to truly add value in underwriting, it needs to be both efficient and accurate. Many claim to be both—but is there proof?

For an AI solution to truly add value in underwriting, it needs to be both efficient and accurate. Many claim to be both—but is there proof?

Measuring efficiency can be fairly straightforward—reducing manual work, processing submissions faster, and automating repetitive tasks all provide clear benchmarks. But accuracy? That’s a completely different challenge.

How does it work?

The Accuracy Validator compares Sixfold’s AI-generated insights to the ideal version—what an experienced underwriter at the carrier would expect. It checks for accuracy, scores the results, and provides feedback to improve alignment with human analysis.

Here is a video overview from Lana, Head of Product at Sixfold, on how the validator works:

AI that speaks Underwriter

‍‍For AI solutions built for underwriters, accuracy isn’t about finding a single “correct” answer—it’s about reasoning like an underwriter. Take a risk summary as an example, an AI-constructed risk summary shouldn’t just condense information; it should highlight the key risk factors that matter to each carrier.

But what happens if an AI summary leaves out a key risk detail? How do you measure how off it is? What do you compare it to? And when a model is updated, how do you know it’s actually improving accuracy—not just changing the output?

So we started searching for an evaluation tool that could help us answer these questions — but nothing existed.

These were the questions we asked ourselves. So we started searching for an evaluation tool that could help us answer these questions — but nothing existed. It wasn’t just that we couldn’t find the right tool—we realized the industry wasn’t even thinking about accuracy in an insurance-underwriting-specific way.

So, we built it. With this capability in place, we can continuously improve Sixfold’s output, ensuring underwriters receive factually correct, reliable, and actionable insights for every risk assessment.

Benefit #1 - Track progress over time

Evaluating AI accuracy isn’t just a one-time task—it’s about ensuring consistency and continuous improvement. With clear benchmark metrics, insurers can easily track progress and see how Sixfold’s AI aligns with their underwriting standards over time.

Accuracy benchmarks help insurers assess Sixfold’s performance during the pilot phase, ensuring it delivers value to the underwriting team before moving to full implementation.

Considering a Sixfold pilot? Accuracy benchmarks help insurers assess Sixfold’s performance during the pilot phase, ensuring it delivers value to the underwriting team before moving to full implementation. Want to keep tabs on accuracy? No problem. We offer on-demand reports to give our customers a real-time look at how well our AI is performing, whenever they need it.

Benefit #2 - Confident AI adoption

From day one, our goal has been to build an underwriting AI solution that users trust. If underwriters can’t trust Sixfold’s insights, why would they rely on them for critical decisions?

Even in low-stakes tasks, AI’s accuracy isn’t always guaranteed. Take general-purpose LLMs—they handle simple research tasks and tasks such as summarizing reports, but even then, you might find yourself second-guessing their output. They’re right sometimes—but how often? And can you tell when they’re not?

The result? More confident decisions, stronger justifications, and a clearer business case for when to quote—and when not to.

That kind of guesswork isn’t good enough for underwriting. The high-stakes decisions underwriters make every day demand high-stakes trust.

With transparent accuracy reporting, underwriters know exactly how reliable Sixfold’s insights are. The result? More confident decisions, stronger justifications, and a clearer business case for when to quote—and when not to.

Benefit #3 - Audit-ready records

To support insurers’ audit and compliance needs, we conduct regular assessments using this application — both after code updates and at scheduled intervals—to prevent model drift and ensure reliability. This process helps identify inconsistencies and flag any deviations from expected results before they impact underwriting decisions.

The Accuracy Validator generates a transparent, audit-ready log for each assessment, allowing insurers to:

✅ Verify the reasoning behind AI-generated insights and decisions.

✅ Monitor model performance over time to proactively address potential drift.

✅ Demonstrate compliance with regulatory requirements by providing clear, documented AI processes

Feedback from customers

As we’ve started to introduce this capability to insurers, the response has been overwhelmingly positive. Some have even asked if they can use it to evaluate some of their other AI applications — a very clear proof of its value from day one. Others have asked to use the Accuracy Validator outside of AI applications to monitor overall underwriting accuracy.

Another key feedback we’ve received is that no other AI solution offers this level of structured performance measurement and tracking.

Another key feedback we’ve received is that no other AI solution offers this level of structured performance measurement and tracking. Sixfold is the first to give insurers a clear way to validate AI impact and track results over time in underwriting.

Curious to learn how you can get started with Sixfold? Check out the FAQ section to learn more about our pilot program, designed to help insurers fully assess the value of Sixfold before scaling up.

Reach out with any additional questions!