Insurance Data Extraction
Evaluating old applications: AI processing of historical documents, including handwritten text.
Automated review of historical health-insurance applications. Recognition of handwritten data and matching documents to records in the insurer's systems.
Precise · handwriting recognition · The Problem
What needed to change
- Dôvera health insurance needed to determine which old health-insurance applications had to remain archived and which could be prepared for disposal.
- The task was extremely labor-intensive – reviewing a large volume of historical documents manually.
- Many applications had been filled in by hand, which made automated processing with standard tools significantly harder.
- To make the right decision, the data on each application had to be identified, extracted, and matched against the data in the insurer's systems.
The Solution
What we implemented
We implemented an AI solution that can process historical health-insurance applications, including handwritten documents.
- Recognizes text from scanned documents and identifies the relevant data needed to evaluate each application.
- Handles handwritten text, which was the key challenge for this type of document.
- Extracted data is matched with records in the insurer's systems to support decisions on archiving or disposal.
- The solution was first validated via a Proof of Concept that confirmed both its technical feasibility and its operational value.
After the successful PoC, the solution is now being rolled into the insurer's processes.
The Results
What changed after deployment
- After a successful Proof of Concept, the AI solution was confirmed to handle historical applications, including handwritten documents.
- Significantly reduces the need for manual transcription and verification of data from old applications.
- The solution makes it possible to match document data with records in the insurer's systems and support decisions on archiving or disposal.
- The insurer gains a technological foundation for systematically processing high volumes of historical documents. Following the successful PoC, the solution is being implemented in the insurer's processes to speed up and streamline work with archival records.
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