Home > XtractEdge > Blogs > Document AI capabilities and benefits for the insurance sector

Document AI capabilities and benefits for the insurance sector

June 15, 2022 - Team EdgeVerve


Document-intensive workflows are usually time and labor-intensive and, if handled manually, can delay the processing of claims and policies indefinitely, leaving the workforce with minimal bandwidth to take up new issues. And manual document processing and extracting information often leave behind a trail of human error. So, returning to those documents to address those errors or re-connecting with customers for more information that was initially overlooked only adds to the delay.

According to reports, unstructured documents are growing by 55% to 65% every year. This translates to millions of documents. Hence, managing and storing these documents is a huge challenge for an insurance provider. How can commercial insurers address this problem?

Document AI in insurance

According to reports, more than 80% of documents that are processed by insurance firms contain mostly unstructured data.

Hence, Document AI in insurance can be the best bet considering the massive volume of documents waiting to be handled on a daily basis. AI in insurance cuts down the long waiting times for customers by bringing down the long hours of reviewing documents, which are initially handled manually.

A purpose-built Document AI platform with advanced capabilities like Machine Learning and Deep Learning helps organizations quickly scan, analyze and understand documents, emulating human understanding of files and data as closely as possible. For instance, XtractEdge is a cloud-based solution that easily tackles complex multi-document data, making it consumption ready to unlock the latent business value.

Insurance processing challenges and remedies

In the insurance industry, processing new policy requests typically take time. The reason is that insurers have to collate large amounts of data from multiple documents and sources. Additionally, they have to use proper guidelines, codes, and modifiers. Each application is reviewed for accuracy and accepted or declined. Then, requesting additional or missing information in certain instances is necessary, which prolongs the process. Hence, lengthy processing time and faulty human judgments occasionally impact the customer experience.

The employees must work with unstructured data, which adds to their problems. Statistics suggest that  85-90% of these documents require manual effort to extract, validate and structure the data.

Semi-structured and unstructured documents have the following characteristics: –

Document AI in insurance solves the pain points of managing semi-structured and unstructured documents.


As companies prepare for the surge in growth in these markets, there will be an increase in the dependence on emerging technologies and data sources to drive efficiency, enhance productivity and expand capabilities across the organization. Document AI in insurance is just the tip of the iceberg, but its benefits for the insurance sector, especially for the employees and customers, are manifold. It expertly handles and solves the document-centric complexities previously faced by insurers.

Related Blogs All Blogs


Cognitive Machine Reading helps meet data extraction challenges – Learn how
July 07, 2022


Modernize Industrial Operations with XtractEdge Asset Efficiency Solution
March 13, 2018

Leave a Reply

Your email address will not be published.