Page 37 - Insurance Times July 2024

Underwriter Co-

Pilot

Future of Insurance

Underwriting with Generative AI

Dobi
(Co-Founder and Chief
Product Officer at LUMIQ)

Enter Large Language Models (or commonly known as Generative AI), which are not just a stepping
stone but a giant leap, bringing a new era of optimized underwriting. By rapidly analysing complex
and voluminous data points, it can proactively identify risk and deviations with a high degree of
accuracy.

I n the Insurance sector, underwriting isn't just a Leading the wave of innovation, we, at LUMIQ, have

developed a Gen AI enabled Underwriting Co-pilot that
process-it's the cornerstone of risk evaluation. As we
embeds LLM models into the existing Underwriting process
look towards a market projected to surge to $222
billion by 2026, underwriting's role in shaping
underwriting workflow with the sharp acumen of
premiums and coverages has never been more pivotal. of the Customer. It doesn't replace but enhances the current
Traditional underwriting has been a complex and time- Generative AI. The application is designed to create a
consuming process involving hundreds of data points symbiotic framework where technology works in tandem
(medical history, financial stability, occupation risk, lifestyle with human expertise, ensuring that UWs have an extensive
factors, etc.) and multiple guidelines that must be carefully support without any disruption to their familiar workflow.
reviewed.
Here's the impact it makes
Enter Large Language Models (or commonly known as
Generative AI), which are not just a stepping stone but a Without Generative AI:
giant leap, bringing a new era of optimized underwriting. For each application, based on the information disclosed by
By rapidly analysing complex and voluminous data points, it the customer, the data is provided to the Underwriter.
can proactively identify risk and deviations with a high Based on this, the UW identifies the most important
degree of accuracy. parameters in the application and starts mapping these to
the risk assessment guidelines.
The result? A streamlined process that not only accelerates
decision-making but also reduces bias and improves However, since these data points are often in hundreds, the
standardization, paving the way for accurately tailored journey is fraught with potential oversights and critical errors
premiums and coverages. can lead to significant financial repercussions.

The Insurance Times July 2024 33