When the Renewal Review capability analyzes the available policies, there are over 100 pieces of data that it can incorporate into its process. This data comes from two main sources: 

1. The PDF documents of the policies that are being reviewed
2. The account information within the Broker Management System
    

Data Extraction from PDF Policies

Quandri extracts data using its proprietary NLP (Natural Language Processing) engine.A NLP engine uses processes such as Optical Character Recognition (OCR) and Machine Learning (ML) to enable AI to understand and communicate with the human language. 

Some examples of data coming off of the policies are:

• Addresses of locations / number and make & model of vehicle
• Coverages applied
• Rating information
• Limit values
• Deductible values
• Discounts applied
• Latest updates to building infrastructure. i.e. heating system
• Credit scoring, if applicable
• Age of home or vehicles, if applicable
   

Data Extraction from the Broker Management System

After the Renewal Reviews capability extracts the required data from the PDF policies, it will turn to the management system to extract data that will help it fill in any blanks to determine if the information on the policy is relevant.

Some examples of data coming from the management system are:

• Contact information on file
• Driver information
• Claims

Conclusion

The Renewal Reviews capability can leverage its processing systems to automate the data extraction process from both your management systems and PDF policy documents to summarize any policy changes, saving you the manual work.