AI OCR for Insurance Operations
Most insurance operations lose time before work even begins. Submissions arrive as PDFs and email attachments that require manual data entry. Selectsys AI OCR turns these files into structured, usable data that moves directly into RQB, Expert Insured (EI), and BPO workflows.
Cycle time improves by 20 to 35 percent, returns drop by 30 to 50 percent, and underwriters can focus on decisioning instead of typing.
From Email and PDF to Structured Data
AI OCR reads incoming submission documents and extracts key information such as insured name, class, limits, state, effective date, and producer details. It then maps this data to fields inside RQB and EI.
Process steps:
- Captures attachments from email, drag and drop, or API.
- Detects document type and layout.
- Extracts and validates key data fields.
- Pushes results to RQB or EI in real time.
- Keeps the original document attached for audit tracking.
Accuracy, Confidence and Audit Trail
Each extraction includes a confidence score.
Items below a defined threshold automatically create a review task in EI.
Approved data updates RQB quotes and EI records instantly.
Every change is logged with user, time, and source file for audit control.
Key metrics:
- Extraction accuracy: 85 to 95 percent
- Manual review rate: below 15 percent after tuning
- Average turnaround improvement: 20 to 35 percent
Integration with RQB, EI and BPO Pods
AI OCR connects directly into the Selectsys ecosystem:
- RQB: pre-fills quote data for faster pricing and binding.
- EI (Policy Admin and Forms): updates account and coverage details automatically.
- BPO Pods: creates structured work tasks for service, endorsements, and renewals with SLA and audit tags.
This removes duplicate entry and creates a closed intake-to-issuance loop.
Interlooping with Other Nodes
- Flows to Submission Triage for completeness scoring and appetite checks.
- Feeds RQB for rating and quote creation.
- Updates EI (Policy Admin and Forms) for documentation.
- Opens tasks for BPO Pods when human validation is needed.
- Sends data back to Analytics and PQI for accuracy tracking and continuous improvement.
This keeps every part of the Value Flywheel connected.
Typical Use Cases
- Managing high-volume inboxes of broker submissions.
- Processing carrier form packets and policy change requests.
- Pre-cleaning data before automated quoting.
- Feeding renewal and remarketing workflows.
Security and Compliance
All files are processed within SOC 2 Type II certified environments.
Access is role-based through EI and RQB.
Data and documents are encrypted in transit and at rest.
Complete audit trail is maintained for every record.
Results and KPIs
- Cycle time reduced by 20 to 35 percent
- NIGO or return rate reduced by 30 to 50 percent
- Hit ratio improvement of 3 to 7 points
- 100 percent audit visibility
Results vary by line of business and baseline workflow.
Start a Pilot
You can test this with your own submissions and carriers.
A pilot is set up in 7 to 10 business days with full SLA tracking.
Related Reading
- Submission Triage
- AI Assist (Underwriting Copilot)
- RQB
- Expert Insured (Forms System)
- Insurance BPO
- Value Flywheel Hub
FAQs
What documents does AI OCR handle?
It processes most common policy, submission, and carrier form layouts, including custom templates.
How does it connect to RQB and EI?
Extracted data is transferred automatically through APIs into quote and account fields.
How long does setup take?
7 to 10 business days for a scoped pilot using your own sample files.
What improvements can we expect?
Typical results are 20 to 35 percent faster turnaround and up to 50 percent fewer returns.
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