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How AI is Reinventing Life Underwriting with Actionable Medical Insights

Published On
March 21, 2025
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The life insurance industry is grounded in expertise, precision, and trust, yet it faces growing inefficiencies as underwriting workloads and the complexity of medical record reviews increase. It’s essential to find a solution that upholds the core values of the industry while eliminating bottlenecks. Like the world’s greatest innovators, underwriters are problem-solvers who constantly analyze data to make the best possible decisions.

This blog will explore how DigitalOwl has leveraged imagination to overcome challenges and equip underwriters with the most innovative, effective tools for medical record reviews.

Breaking Free from PDFs: A Game-Changer for Underwriters

2024 was a big year for underwriting innovation. With the launch of our new platform, we moved beyond static PDF summaries, giving underwriters the flexibility to analyze medical records in multiple ways. This shift was a game-changer, helping underwriters work faster, more efficiently, and with greater confidence.

But we didn’t stop there. Case Notes, introduced later in the year, provided concise, actionable insights tailored to life underwriters. Powered by the first AI Agents designed for insurance-related medical record reviews, Case Notes moved beyond summarization to highlight critical decision-making information, treatment gaps, severity assessments, and future treatments. 

This was a major leap forward in providing underwriters with the tools they need to assess a case effectively. Previous solutions placed the burden of connecting the dots and diving deeper solely on the underwriter. Case Notes changed that by applying specialized industry logic to surface the most relevant insights—ensuring underwriters have the right information at the right time to make confident, informed decisions.

AI Agents: The Future of Underwriting Assistance

AI Agents aren’t just another AI tool—DigitalOwl designed them exclusively for insurance-related medical record reviews, with built-in boundaries and guidelines to ensure trust and accuracy. These AI Agents function like digital detectives, recognizing patterns, assessing severity, and presenting underwriters with exactly what they need to make informed decisions in a fraction of the time it would take a reviewer.

For example, rather than simply stating that an applicant has diabetes, an AI Agent will analyze the severity of the condition, treatment history, and potential risks—offering a holistic view of the applicant’s health.

With page counts growing longer and underwriters facing tighter deadlines, these AI Agents are a crucial tool to help underwriters save time on electronic medical record reviews without missing crucial details. 

Efficiency Without Compromise

Underwriters are risk-averse by nature—and for good reason. Every decision they make impacts applicants, policyholders, and financial outcomes for carriers and agents. That’s why we designed our AI to be fully transparent and auditable.

Unlike "black box" AI models, DigitalOwl’s AI provides click-to-evidence verification, so underwriters can see exactly how and why an insight was generated. We know that trust is earned, and we aim to build confidence, not replace expertise.

Meet Me at AHOU and See AI Agents in Action

The underwriting world is changing, and at AHOU, we’re showcasing what the future holds. By combining human expertise with AI-powered efficiency, we’re not just improving processes—we’re unleashing imagination, reinventing underwriting, and empowering underwriters to focus on what matters most.

Want to see how AI Agents can transform your underwriting process? Schedule a demo with me at AHOU booth #305/307 to see our solutions firsthand. 

Whitney Barnes
Sales Director, Life Solutions
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DigitalOwl
About the author

Whitney Barnes has over 20 years of experience in the Life Insurance industry. She serves as Sales Director and helps life insurance carriers and others in the industry enhance and accelerate the medical records review process.