Underwriting AI Innovations With Jake Jones

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TL;DR:

• AI is reducing administrative burdens for life insurance underwriters by automating tedious tasks like medical record reviews and data extraction.
• Underwriters are leveraging AI-driven decision support tools to quickly flag inconsistencies and extract insights from vast amounts of medical and financial data.
• Change management is crucial—getting underwriters involved early in AI adoption fosters trust and smoother integration.
• Speed is a competitive advantage in underwriting, with AI-powered automation helping carriers issue policies faster than their competitors.
• The future of underwriting will involve AI-powered training, process improvement, and dynamic risk assessment to enhance both efficiency and decision-making.

Before we dive into the key takeaways from this episode, be sure to catch the full episode here:

Meet Jake - Second VP and Actuary of Life Underwriting at Securian Financial

Jake Jones, Second Vice President and Actuary of Life Underwriting at Securian Financial, has spent nearly 28 years shaping risk management and product development in life insurance.

Leading AI-driven transformation efforts, Jake focuses on making underwriting faster, less invasive, and more efficient for both customers and underwriters. His expertise spans integrating AI into medical record analysis, streamlining risk assessment, and optimizing underwriting workflows.

At Securian, Jake collaborates with actuaries, data scientists, and technology teams to enhance decision support, reduce administrative burdens, and future-proof underwriting through AI innovations.

Passionate about bridging the gap between technology and business, Jake is shaping the next era of life insurance underwriting—one where AI augments human expertise to deliver smarter, faster, and more personalized policy decisions.

The Hidden Complexity of Life Insurance Underwriting

Life insurance underwriting is a complex process that policyholders rarely see.

Jake Jones, Second Vice President and Actuary at Securian, explains that underwriters assess risk using medical records, financial data, and personal history, often requiring invasive exams.

Unlike simpler forms of insurance like auto coverage, life underwriting involves detailed evaluations that can take days or weeks.

“We're trying to solve the same problems we always have,” Jake notes, “but with AI, we can make the process less invasive and faster.”

AI helps streamline these assessments, but the challenge remains in balancing efficiency with accuracy.

“AI’s role isn’t just underwriting—it’s transforming the whole insurance process." — Ankur Patel

The role of the underwriter is evolving as AI takes over repetitive tasks, allowing professionals to focus on high-value judgment calls, relationship management, and ensuring policies are priced correctly.

How AI Is Revolutionizing Medical Record Analysis

One of the biggest bottlenecks in underwriting is reviewing extensive medical records.

Jake highlights that underwriters can spend an entire afternoon sifting through hundreds of pages of medical history, extracting information manually before even beginning risk assessment.

“If we could take AI and leverage smart document processing,” he explains, “we can extract that information and get it to the underwriter in a very consumable fashion.”

AI-powered tools help underwriters by identifying medications, treatments, and medical history patterns, reducing processing time significantly. Additionally, AI enables underwriters to ask specific questions about a case and retrieve relevant insights instantly.

By offloading tedious manual work, AI is transforming underwriting into a more strategic, efficient process that allows professionals to focus on evaluating complex cases rather than extracting raw data.

Decision Support: Empowering Underwriters, Not Replacing Them

A major concern with AI in underwriting is the fear of automation replacing human jobs.

However, Jake emphasizes that AI’s role is not to replace underwriters but to act as an assistant.

“Nobody’s looking to replace the underwriter,” Jake says. “We’re looking to better enable them.”

AI-powered decision support tools help underwriters quickly retrieve relevant guidelines, flag inconsistencies, and compare applicant data against historical trends.

Instead of manually cross-referencing underwriting manuals, AI can instantly pull up the most relevant information, saving time and reducing errors.

AI also helps underwriters identify inconsistencies in medical records, prompting further investigation when needed.

By augmenting human expertise rather than replacing it, AI ensures that underwriters spend more time on complex risk assessment and less on administrative tasks.

Overcoming Resistance: Change Management in AI Adoption

Underwriters are traditionally skeptical of AI, fearing it might replace their expertise or disrupt workflows.

Jake acknowledges these concerns, explaining that change management is critical to AI adoption.

“Getting the underwriter to trust AI, to see it providing value, is key,” Jake says.

One approach is involving underwriters early in the development process so they feel a sense of ownership over AI-powered tools. Jake emphasizes cross-disciplinary collaboration between actuaries, underwriters, and data scientists to ensure AI solutions meet real underwriting needs.

Visualization and hands-on experience also play a role—when underwriters see AI working alongside them, they’re more likely to embrace it. By focusing on transparency and demonstrating real benefits, insurers can drive successful AI adoption and overcome resistance to change.

Speed as a Competitive Advantage in Life Insurance

In life insurance, speed is a game-changer. Jake explains that carriers competing for policies must issue offers quickly to win business.

“If I can get the best offer possible out in a day versus my competitor who takes six days, that increases the likelihood we’ll close the sale,” Jake states.

AI helps insurers reduce underwriting time by automating document processing, data retrieval, and risk assessment. Faster turnaround benefits both policyholders and agents, who prefer carriers that can approve policies quickly.

AI-driven automation also eliminates unnecessary delays, ensuring that underwriters spend time on cases that require human judgment while AI handles routine assessments.

In a market where the first carrier to provide a quote has a higher chance of securing the policy, AI is a powerful competitive advantage.

Beyond Risk Assessment: AI’s Expanding Role in Underwriting

AI’s influence in underwriting goes beyond risk assessment. Jake highlights that AI can improve training, quality control, and operational efficiency.

“We talk a lot about leveraging AI not just for risk assessment but for training and process improvement,” Jake notes.

AI-driven training tools can help new underwriters learn faster by analyzing real-world cases and providing instant feedback.

AI can also streamline internal workflows, assisting with document organization, compliance checks, and even customer interactions.

By integrating AI into broader underwriting operations, insurers can enhance consistency, reduce human error, and improve overall efficiency.

Instead of just focusing on assessing individual applications, AI’s expanding role in underwriting ensures that insurers operate more effectively at every level.

The Future Underwriter: New Skills for an AI-Powered Industry

As AI takes over administrative tasks, underwriters must adapt by developing new skills.

“We talk about the underwriter of the future,” Jake says. “It’s not just about transformation of the capabilities but also transformation of the role.”

Future underwriters will need to be comfortable working alongside AI-driven decision support systems, interpreting complex data, and leveraging automation to make better risk assessments.

The role will shift toward higher-value tasks such as relationship management with agents, investigating edge cases, and applying human expertise to nuanced decisions AI can’t fully automate.

Insurers will need to invest in training and AI literacy to ensure underwriters remain effective in this new landscape.

The underwriter of the future will not be replaced by AI but will instead be an AI-empowered professional with expanded capabilities.

What’s Next? The Roadmap for AI in Insurance

The future of AI in insurance goes beyond today’s applications. While document automation and decision support are already making a difference, Jake sees long-term opportunities in predictive modeling, enhanced data analytics, and more personalized risk assessment.

“AI will help us continually improve our underwriting models by identifying patterns and trends in real time,” Jake explains.

AI will also improve feedback loops between claims and underwriting, allowing insurers to refine risk models based on actual outcomes.

Additionally, insurers will explore AI-driven agentic systems that can automate multi-step workflows, reducing the time it takes to underwrite complex policies.

However, insurers must balance innovation with responsibility, ensuring AI remains transparent, fair, and compliant with regulations.

The next phase of AI in underwriting isn’t just about efficiency—it’s about transforming the entire insurance ecosystem.

Want to learn more about insurance process automation? Check out this episode on insurance process automation and unlocking efficiency while maintaining trust with Meredith Barnes Cook.