Solution
For commercial P&C underwriting teams at carriers, MGAs and specialty writers: every broker submission triaged, appetite-checked and ranked before it reaches the desk.
The problem
Thousands of submissions arrive as broker emails and attachments. The ones worth quoting sit in the same pile as the rest, and speed to quote decides who wins them.
Insured details, limits and loss history live in PDF applications and Excel loss runs — captured by hand before any judgment happens.
Guideline adherence varies by individual, and the drift only shows up later, in the portfolio.
The product, not a promise
How it works
Broker emails, ACORD forms and loss runs are ingested and classified as they arrive.
Insured details, coverage limits and loss history are captured without manual keying.
Each submission is checked against your risk appetite and underwriting guidelines.
External data — property details, credit signals — completes the risk profile.
Submissions are prioritized by risk quality, broker tier and deal size, then queued for the underwriter.
Who it's for
Underwriter
Head of underwriting
Portfolio, actuarial & IT
Underwriting desks lose business two ways: quoting slowly, and quoting the wrong risks. Thousands of broker submissions arrive by email, the good ones buried among the rest, and the data an underwriter needs — insured details, limits, loss history — sits in PDF applications and Excel loss runs that take hours to re-key. Meanwhile guideline adherence varies by individual, and risk creep accumulates quietly in the portfolio.
The Underwriting Decision Engine automates the submission lifecycle from inbox to queue. It ingests broker emails, ACORD forms and loss runs, extracts the risk data without templates, validates each submission against your specific appetite, and enriches the file with external data so the underwriter opens a complete risk profile instead of a stack of attachments.
Appetite rules run before a human touches the file: submissions outside defined bounds — excluded classes, loss thresholds — are declined at intake with the reason recorded. What remains is ranked so the best business gets quoted first, and the underwriter’s time goes to risk selection rather than data entry. Guideline validation applies the same logic to every file, which is how consistency stops depending on who happened to pick up the submission. Seasonal spikes and new markets are absorbed by the same pipeline, without hiring a bench of underwriting assistants first.
Every extracted field links back to its source document, and every validation and declination is logged with the rule that produced it. Pricing models and underwriting decisions reference the same structured data, so actuarial teams and the front line argue from one set of numbers instead of two. When a decision is examined later — by audit, by reinsurers, by your own portfolio review — the file shows exactly what the underwriter saw and why the engine ranked it where it did.
Objections, answered
Only where your appetite rules say so explicitly — excluded classes, defined loss thresholds — and each declination is recorded with the rule that produced it. Everything else queues for an underwriter, ranked. The quote, refer or decline call on live submissions stays human.
Appetite and guidelines are expressed as explicit rules against the extracted fields, so an update is a rule change, effective on the next submission processed. Rule versions are logged, so you can see which appetite edition handled which risk.
The file as the underwriter saw it: extracted fields with links to the source documents, the rules that fired, the ranking rationale, and the logged decision. The answer to why a risk was written is in the record.
There is no per-broker template work — the engine reads submissions as they arrive today. Most teams run it alongside their current triage on the live inbox and compare queues before cutting over.
Watch ACORD forms and loss runs become an appetite-checked, ranked risk profile live in the demo.
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