Enterprise

[DB Insurance] Building an AI-OCR Platform for DB Insurance

DB Insurance built an AI-OCR platform to establish a company-wide AI OCR development and operations environment. This improved the accuracy and operational efficiency of insurance document processing and created a foundation for managing AI OCR models reliably.

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An AI OCR Operating Environment for High-volume Insurance Documents

To efficiently process the wide variety of documents generated in insurance and sales operations, DB Insurance needed a platform that supports both AI OCR model development and operations in an integrated way.

Securing a Platform Foundation for Company-wide OCR Operations

An integrated management framework was needed to reliably handle high-volume document processing and AI OCR model operations.

  • High-volume document processing: An integrated environment to process diverse insurance documents quickly and reliably

  • AI OCR model operations: A framework to consistently manage OCR model development, deployment, and performance

  • Financial-sector security compliance: A secure environment for processing documents containing personal information

Building an MLOps-based Integrated AI OCR Platform

We built an MLOps-based platform that manages OCR models from development to operations in a single environment.

  • AI OCR model development and operations: Integrated management of OCR model training, deployment, and operations on the platform

  • Integrated document processing workflow: Standardized the recognition, review, and post-processing flow to improve processing efficiency

  • Built-in security controls: Met financial-sector security requirements through access control, permission management, and audit history

Higher AI OCR Accuracy and Operational Efficiency

An AI OCR-based document processing framework improved the quality of insurance document processing and the efficiency of operations management.

  • Higher document processing accuracy: Improved recognition quality and processing accuracy for insurance documents with AI OCR models

  • More efficient model operations: Standardized model development, deployment, and operations to reduce repetitive work

  • Stronger company-wide OCR management: Secured operational stability by centrally managing document processing status and model operations

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