How to automate loss-run and ACORD extraction for commercial lines
Commercial submissions arrive as PDFs and get re-keyed into the rater and AMS by hand. An extraction layer with a human checkpoint reads them once.
Answered in short
5 things that decide this
- 01Automating loss-run and ACORD extraction means a document layer reads the PDFs, a validation step flags missing or inconsistent fields, and the clean data posts to your rater and AMS once.
- 02Most commercial submissions get typed three or four times before they reach a carrier. Extraction removes the re-keying; the coverage judgement stays with your producers.
- 03Accuracy comes from the validation step. A field the system couldn't read with confidence goes to a person instead of quietly reaching a carrier.
- 04The shape is proven in insurance documents. On PremiumAudit.io, an audit platform Hashlogics built, calculation errors fell 95% once the document flow ran through one shared record.
- 05An agency writing a handful of commercial accounts doesn't need this. It earns its keep where submissions stack up and a CSR re-keys all day.
How loss-run and ACORD extraction works
Loss-run and ACORD extraction runs in four moves. A document layer reads each PDF, whether it's an ACORD form, a carrier loss run or a supplement, and turns it into structured fields. A validation step checks those fields and flags anything missing or inconsistent. Clean data fills the rater. An AMS write-back then posts the same record once, with the source document attached.
The validation step is what makes it trustworthy. Loss runs from different carriers show the same claim in different formats, and scanned copies come in rough. When a field reads as low confidence, or two documents disagree, that submission routes to a person. Nothing invented reaches your rater.
Write-backs cover AMS360, Applied Epic, EZLynx or whatever you run. Posting once is the point: the extracted record lands in the AMS with the source PDF linked, so an underwriter's question later gets answered from the document rather than from memory. Extraction is the capture layer of the insurance document automation we build for agencies and carriers. Verification, routing and write-back are described there.
- Documents arriveACORD forms, loss runs, supplements, as PDFs.
- ExtractionEach document becomes structured fields.
- ValidationMissing or inconsistent fields go to a person.
- Rater fillClean data fills the rater, no re-keying.
- AMS write-backPosted once, source document attached.
The exception queue is the trust mechanism. Confident reads flow through; doubtful ones stop.
Where automation stops in a commercial submission
Extraction automates the re-keying and nothing else. Coverage recommendations, carrier selection and pricing conversations stay with your producers, because those calls carry your E&O exposure and the client relationship. Captive agencies also hit a lower ceiling: carrier-mandated systems limit what an integration can touch. And a low-volume commercial book may not hold enough re-keying to be worth removing.
There's also one question worth asking any vendor: what happens to a field the model got wrong? A system without a human exception queue is a system that files errors faster. Ask to see the queue before you ask to see the extraction demo.
Related questions
01Which systems does this write to?+
Common agency-management systems such as AMS360, Applied Epic and EZLynx expose APIs a custom build writes to, and the same layer can post to an older AMS, a rater or a spreadsheet you run today. Integration is the real work of the build; reading the PDF is the easier half.
02What about a crooked, coffee-stained scanned loss run?+
Rough scans are normal input here, not an edge case. The extraction layer scores its own confidence per field, and low-confidence reads route to a person for a quick confirm. That one document moves slower, and the whole book still moves faster than hand re-keying.
03Does this help with quote turnaround?+
Extraction removes the slowest manual step in the submission flow, the re-keying, so it feeds quote turnaround directly. The full turnaround problem is bigger than documents, though. Our answer on cutting quote turnaround covers the rest of the flow.
Related
- Business process automation →Our service page: document flows wired into the systems you already run.
- PremiumAudit: AI insurance audit automation →The insurance document platform behind the numbers on this page.
- How to cut quote turnaround in an insurance agency →The rest of the submission flow, beyond documents.
- Software for insurance agencies →Our insurance hub: what agencies actually buy.
