Turn a professional liability submission into a ready-to-quote file in minutes, not hours.
DigitalEdge Policy modernizes submission intake and underwriting for professional lines, so your team spends its time on judgment, not data entry. See the proof, then see it on your own submissions.
The submission bottleneck
Professional liability submissions arrive as long, unstructured documents. The traditional path: an underwriter reviews each one, hands it to an underwriting assistant, and the assistant keys the data in by hand. It works until volume climbs. Then the only lever is more headcount, speed to quote slips, and complex risks sit in the queue.
See how it works
Four resources for a professional liability buying committee, from a live customer walkthrough to a business case you can bring to leadership.
From Manual to Modern: Falcon Risk Services on Embedded AI
Nell Baird, AVP of Operations at Falcon, walks through the AI Submission Agent inside DigitalEdge Policy, and how her team built trust in it. Insurance Journal Demo Day, ungated.
Watch the walkthrough →
Professional Liability MGA Leverages Data and Automation
How one professional liability MGA cut submission intake to 3 minutes and underwriting cycle time to 30 minutes on DigitalEdge Policy and Claims. Datos Insights award winner.
Read the case study →The ROI One-Pager for Your Committee
The numbers, the objections a buying committee raises, and the answers, in one page you can forward to leadership. Built for underwriting, IT, and economic buyers together.
Download the one-pager →Key Tech Insights from Industry Leaders
Falcon CIO Rich Pluschau and Datos Insights analyst Martin Higgins on what modern submission automation actually changes for a professional lines MGA.
Read the insights →The AI Submission Agent: an added layer, with the underwriter in the lead
Beyond the platform gains above, the AI Submission Agent (a capability within DigitalEdge Policy) reads incoming submissions and prefills the underwriter workbench. It prepares the submission. The underwriter decides.
- Confidence-score color coding flags which fields to double-check before you rely on them.
- Source-document highlighting maps every populated field back to its exact origin in the submission PDF.
- A validation step records the underwriter's review with an auto-stamped name, date, and time, for accountability and audit.
- Cogitate data scientists tune the model monthly against the fields most often corrected, so accuracy climbs over time.
See it on your own submissions
Bring a real submission to a working session. We'll show you what your underwriters would see, and how fast it gets to quote.
