Client change instructions
Classified, extracted and linked back to source evidence for reviewer control.
MTA document automation
AI MTA document automation for commercial insurance brokers
DocBeaver automates the document handling around mid-term adjustments, from client instruction through insurer response and final filing.
The workflow compares the requested change against endorsements, revised schedules, certificates, AP/RP notes and finance evidence so handlers can review exceptions before release.
45-70%
Target reduction in routine MTA handling time
Document inputs
Real documents this workflow is built around
These are the source files DocBeaver expects to map during an audit and prototype. The implementation can start with a narrow subset, then expand as extraction quality and review rules are proven.
Endorsements and revised schedules
Classified, extracted and linked back to source evidence for reviewer control.
Certificates and evidence documents
Classified, extracted and linked back to source evidence for reviewer control.
Additional or return premium notes
Classified, extracted and linked back to source evidence for reviewer control.
Finance adjustment records
Classified, extracted and linked back to source evidence for reviewer control.
Insurer emails and portal outputs
Classified, extracted and linked back to source evidence for reviewer control.
Manual bottlenecks
Why this workflow is a strong automation candidate
Step 1
The client instruction, insurer endorsement and revised schedule are compared by hand.
Capture client instructions, insurer responses, endorsements, schedules and finance documents.
Step 2
Premium changes can be missed when AP/RP notes, invoices and finance records sit separately.
Classify the MTA type, affected policy section, requested date and urgency.
Step 3
Certificates and evidence documents may not match the final accepted change.
Extract changed risk details, premium movement, effective dates, certificates and conditions.
Step 4
Handlers spend time filing documents and updating status across several systems.
Compare insurer documents against the original client instruction.
Extraction and checks
Fields extracted and validation checks performed
The automation should produce reviewable data, not a black-box answer. Every important field or exception needs a source link, confidence signal and review route.
| Extracted fields | Validation checks |
|---|---|
| Policy number, client, insurer and effective date | Client instruction matched to endorsement |
| MTA type, affected risk, location, vehicle, property or insured item | Revised schedule checked against requested change |
| Additional premium, return premium, fees and tax | Effective date and premium movement verified |
| Endorsement wording, subjectivities and certificate references | Certificate presence and version checked |
| Handler, status, review outcome and filing destination | Finance adjustment and invoice evidence checked |
Workflow outputs
What the implementation should produce
DocBeaver normally starts with a controlled workflow output: summaries, exception queues, review files, dashboards or proposed system updates. Direct writes into operating systems should be added only after review rules are proven.
- MTA review summary
- Exception checklist
- Updated policy field proposal
- Finance adjustment review queue
- Filed source-document pack
FAQ
Common questions
Which MTAs are best suited to automation?
Repeatable MTAs with clear source documents are strongest, such as address changes, vehicle changes, sums insured changes, certificate updates and routine premium adjustments.
Can DocBeaver handle insurer portal documents?
Yes. Portal downloads can be included alongside email attachments, BMS exports and shared-folder documents, subject to access and permission constraints.
Assess this workflow using your real documents
Start with a focused audit of document types, source systems, manual checks, exception rules and review requirements.