Underwriting Workbench
Innovating beyond an existing AI-powered underwriting vision
Role
Product Strategy · Research · Workflow Design · Prototyping
Context
Enterprise transformation for a national insurance carrier (anonymous for confidentiality).
01. Leadership Context — Innovation on Top of an Existing Vision
We weren’t starting from zero. Two years earlier, the company had already defined a vision for a new Underwriting Workbench:
- Unify underwriting tools
- Make workflows easier
- Embed AI into decision steps
- Focus on speeding small-business underwriting
On paper, the strategy was strong. But two years later, only ~50% of that workbench vision had been implemented.
“Help us innovate — but not by re-designing what we already planned. Push beyond the existing vision.”
Our mandate was to understand why progress stalled, where the vision fell short, and how AI should actually fit into the workflow beyond simple execution.
02. Discovery — Talking to the People
We interviewed 12 underwriters across different lines, internal dev architects, process owners, and agent experience owners. Our goal: understand reality vs. vision.
We mapped actual workflows, tools, exceptions, handoffs, and bottlenecks. What emerged was clearer than any roadmap slide: underwriters were managing far more than just tools—they were managing mental chaos.
03. What We Really Learned (Not Assumptions)
Underwriters were managing mental models, not just data.
Beyond juggling emails, PDFs, and spreadsheets, they were constantly balancing conflicting company rules, complex guidelines, and profitability requirements—all while trying to hit a target premium. A huge portion of underwriting was mental — not visible to systems.
The Volume Paradox
Underwriters are buried under a mountain of applications, yet over 50% fall outside the company's appetite immediately. Of those remaining, 70% trigger manual flags for guideline violations.
>85%
Wasted Effort
The majority of an underwriter's day is spent investigating cases that will never result in a quote.
The Hidden Agent Tax
Research showed ACORD submissions were a massive bottleneck. Agents spent hours filling 50–100+ page forms and re-entering data. By the time it reached underwriting, it already carried structural inefficiencies.
AI was positioned as a helper, not an owner.
The existing vision imagined AI as a productivity assistant. But underwriters didn't want to "work faster"—they wanted to eliminate re-work and gray areas. They wanted AI where repeatable patterns existed, not where nuance lived.
04. Reframing the Vision — Beyond Their Workbench
“From AI as copilot → to Human as AI supervisor.”
We proposed a shift: The Workbench shouldn’t simply assist underwriters. It should prepare perfect cases and escalate only what truly needs human judgment.
AI Owns the Process
- • Normalizes ACORDs
- • Checks completeness
- • Enriches risk automatically
- • Routes cases intelligently
Human Owns the Decision
- • Reviews edge cases
- • Handles complex nuance
- • Overrides when necessary
- • Documents reasoning
05. Product Shape — Same Workbench, Different Brain
For Agents: Submit right, the first time.
We designed adaptive intake flows that proactively check for completeness and irrelevant questions, ensuring transparency throughout the lifecycle.
For Underwriters: Judge risk — not chaos.
The reimagined workbench surfaces clear gaps, provides AI-prepared context, and offers consistent decision steps with built-in collaboration.
06. Validation — Two Structured Approaches
1️⃣ Deep Qualitative Validation
1-on-1 sessions with 9 underwriters testing trust thresholds with automation and comfort with AI-owned steps.
2️⃣ Broad Organizational Alignment
A vision landing page with explainers and prototypes shared with the entire workforce to measure sentiment and excitement.
07. Where This Innovation Landed
Our work did not replace their internal workbench roadmap.
Instead, it:
- clarified why their progress stalled
- identified the gaps their roadmap didn’t address
- repositioned AI from assistant to orchestrator
- brought agents into the problem (not just underwriters)
- helped leadership understand why SMB underwriting still dragged
Embedded to their corporation new future vision and will be implemented piece by piece accordingly.
“Systems should handle predictable underwriting. Humans should supervise complexity.”