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Insurance Entity Extraction Model
by YouTube
0
ML Model
<100
Summary
Summary
Statistical ML model is used for entity extraction specific to the insurance industry for Insurance industries for extraction for entities i.e. policy number, policy tenure, client name.
Overview
Overview
The goal of this project is to ensure the smooth extraction of insurance-related entities from unstructured data. The unstructured data is to be provided as input which is obtained from any of the OCR engines by processing their documents in the image of PDF formats.
This AIFabric compatible ML model analyses incoming insurance documents and extracts entities i.e. policy number, policy tenure & client name and the extracted data can be utilized by the bot to perform data entry activities to their respective application.
The model has been trained on the client and carrier-specific insurance documents compatible with the Accord template.
Installation Guide:
1. Download the zip file from drive and upload the package to AIFabric
2. Input for the model is string obtained from OCR(Preferably tesseract) after passing the insurance document.
3. Output will be json object with keys "POLICY_NO","POLICY_PERIOD","INSURED_ORG".
Features
Features
Insurance industries receive a large volume of documents where end-users manually must look out majorly for entities i.e. policy number, policy tenure, client name for data entry or indexing to the respective application. UiPath enables its customers to automate a key step of the customer service experience via a combination of RPA and ML. A custom-built statistical ML model is used for entity extraction specific to the insurance industry.
Additional Information
Additional Information
Dependencies
UiPath Studio >19.8 UiPath.Web.Activities UiPath.MLServices.Activities
License & Privacy
MIT
Privacy Terms
Technical
Version
1.0Updated
April 7, 2020Works with
UiPath Studio >=19.8
Certification
Silver Certified
Support
UiPath Community Support
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