Every underwriting team has a version of the same complaint: the submission isn’t really a submission until someone has spent an hour on it.
A broker email arrives with an ACORD 125 commercial application, a property section, a schedule of values in a spreadsheet, three years of loss runs as scanned PDFs, a supplemental questionnaire for cyber, and a note that says “renewal attached, need terms by Friday.” Before an underwriter can make a single judgment, someone has to check clearance, find out whether the insured is already known, pull the pieces into the system, notice what’s missing, and chase the broker for it.
Extraction tools can read the documents. That’s necessary but not sufficient. What underwriters actually want is a clean file: complete, cleared, structured, appetite-checked, and traceable back to what the broker sent. This post describes how to build intake that produces one, and how to make the experience better for brokers at the same time.
Define “clean file” before you automate anything
Most intake programs skip this step, and it’s the one that matters most. Agree with underwriting leadership, in writing, what a submission must contain before it reaches an underwriter’s queue. A typical definition for a commercial or specialty line includes:
- Identity: named insured, legal entity, address, and any related entities, matched to existing records where they exist.
- Clearance: confirmation that no other broker has already submitted the same risk, or a flag that a conflict exists.
- Core application data: the required fields from the ACORD application and line-specific sections, such as the 126 for general liability or the 140 for property.
- Exposure data: a schedule of values, revenue, payroll, fleet list, vessel details, or record counts, depending on the line.
- Loss history: loss runs covering the period your guidelines require, with gaps flagged.
- Line-specific supplementals: for example, security controls for cyber, or voyage, commodity, and packing information for marine cargo.
- Requested terms: effective date, limits, retentions, and any coverage extensions requested.
That definition becomes the checklist that intake (human or automated) is measured against.
Stage 1: Receive everything in one place
Submissions arrive through email, broker portals, ACORD data feeds, and occasionally direct API integrations. The first job is to land all of them in a single intake queue with the original artifacts preserved. Each submission gets an ID, a received time, and a record of which broker and channel it came from. Nothing is rekeyed at this stage, and nothing is lost.
Stage 2: Classify, split, and extract
A single email often contains a dozen documents, and a single PDF can contain several forms. AI does the sorting: identifying each document type (application, supplemental, SOV, loss run, prior policy, financials), splitting combined files, and extracting the fields your clean-file definition requires.
Two rules keep this trustworthy:
- Every extracted value links to its source, meaning the page and location in the original document. An underwriter who doubts a revenue figure can click through and see it.
- Confidence is visible. Low-confidence extractions are flagged for review rather than silently accepted.
Where the broker submits electronically using ACORD data standards (what many teams call eSubmission), use that structured data directly and reserve extraction for the attachments that still arrive as documents. Even then, validate it: an electronic submission can be complete in format and still carry stale loss runs or an exposure figure that contradicts the attached financials. Structured input is a head start, not a guarantee of a clean file.
Stage 3: Clear and match
Before an underwriter invests time, the system should answer two questions automatically:
- Is this risk already in play? Check for prior or concurrent submissions on the same insured, using fuzzy matching on names, addresses, and identifiers, since the same company rarely appears the same way twice.
- Do we know this insured? Pull prior submissions, quotes, policies, and claims into the file.
Clearance conflicts go to whoever owns broker-of-record decisions under your rules. Clean matches move on.
Stage 4: Check completeness and appetite
With structured data in hand, compare the submission against the clean-file definition and your underwriting guidelines:
- Completeness: which required items are missing or out of date (for example, loss runs that stop eighteen months ago).
- Appetite: whether class, territory, size, and requested limits fall inside appetite, outside it, or in a referral band.
- Data conflicts: a revenue figure on the application that disagrees with the one in the financials, or an SOV total that doesn’t match the application.
Out-of-appetite submissions can be declined quickly and courteously, with a reason, which brokers value far more than silence.
Stage 5: Close the loop with the broker fast
This is where intake stops being an internal efficiency project and becomes a broker experience advantage. Within hours of receipt, the broker should hear one of three things:
- “Received and complete. It’s with an underwriter.”
- “Received. We need these specific items to proceed,” with an exact list rather than a vague request.
- “Outside our appetite, and here’s why,” so they can place it elsewhere quickly.
Specific, early requests for missing information save days compared with an underwriter discovering the gap later. Brokers place business where they get fast, clear answers.
Stage 6: Present a file underwriters can trust
What reaches the underwriter’s queue should look like a well-prepared file: a summary of the risk, the structured data, appetite and completeness results, insured history, and links back to every source document. The underwriter’s time goes on judgment (pricing, terms, conditions) rather than assembly.
Prioritization helps too. Order the queue by effective date, broker relationship, appetite fit, and expected value, so the best opportunities don’t wait behind the incomplete ones.
Measure submission quality by broker
Once intake is structured, you can see patterns that were invisible before: which brokers consistently send complete submissions, which ones omit loss runs, which ones send risks outside appetite. Shared tactfully, this data improves the relationship. A broker who knows exactly what you need sends better submissions next time.
Illustrative example: an MGA writing marine cargo and cyber might find that most of its follow-up requests are for the same two items: updated loss runs and completed security supplementals. Asking for both automatically at receipt, and publishing a short “what we need” guide for brokers, could take a full round of back-and-forth out of most submissions.
What to track
- Time from receipt to acknowledgment and from receipt to underwriter-ready
- Percentage of submissions complete at first receipt, by broker and line
- Follow-up rounds per submission
- Clearance conflicts detected before underwriting effort
- Underwriter time spent on assembly versus evaluation
- Quote and bind ratios for submissions handled through the new intake
The goal: trust at the point of handoff
Underwriters will use an intake process the moment they trust it: when the data matches the documents, the gaps are flagged honestly, and nothing the broker sent has gone missing. Build for that trust first, and speed follows.
See where your submission intake loses time. Book the Aketud Underwriting Workflow Assessment to define your clean-file standard, map intake from broker email to underwriter queue, and find where AI can take assembly work off your underwriters.
