Insurance Underwriting Assistant

A commercial lines underwriter evaluating 20+ submissions weekly spends 60-70% of time on data gathering, not risk assessment. Each submission involves reading 50+ page broker packages, extracting risk data, entering into the rating system, pulling external data, and compiling for the underwriting decision.

McKinsey found multi-agent AI can handle intake, risk profiling, pricing, and compliance in underwriting. AIG reported AI improved data intake accuracy from approximately 75% to over 90%. By 2026, carriers are scaling AI into production after 2025 pilots.

The bottleneck is data assembly that precedes the decision. Underwriters are skilled risk assessors spending most time on clerical work.

The agent processes broker submissions: applications, loss runs, questionnaires, financials, property schedules. Extracts structured risk data and compiles a unified summary — insured details, coverage requested, loss history, exposure data, risk factors.

Simultaneously pulls external data: property characteristics from data services, loss history from ISO/NISS, financials from D&B. All assembled into a risk profile reviewable in minutes.

Runs through your rating algorithm for a preliminary indication with transparent assumptions. The underwriter reviews, adjusts based on expertise, and decides. Agent handles assembly; underwriter handles judgment.