https://store-images.s-microsoft.com/image/apps.56740.66e870e6-6fbb-407b-9f3c-160b110a3e26.6f79499d-45a2-422c-9dbb-30111effeb2c.94b15573-3e28-4d8d-b65b-a62a3ab959fb

Coforge Quasar - Loss Run document analysis

Coforge Limited

Coforge Quasar - Loss Run document analysis

Coforge Limited

Accelerator solution for automating data extraction and analysis from loss runs documents.

Loss Run Document Extraction is a process that extracts important information from loss run documents. These documents are used to track the claims history of an insurance policyholder. The information extracted from these documents can be used to identify potential areas of risk and to assess the financial stability of an insurance policyholder.

By using Coforge Quasar AI solution, insurers can automate the process of extracting important information from loss run documents. System can quickly and accurately identify key information from the documents, such as policyholder account number, policy numbers, claim dates, Loss Status and claim amounts. The user interface is intuitive and provides a simple and effective way to edit and validate data. The solution provides a convenient way to extract and validate data with minimal effort. Overall solution is powered by good combination of Azure AI Cognitive services.

Key Benefits:

o Detect potential fraud or errors in the documents, allowing them to take corrective action quickly.

o Improve risk management processes and make more informed decisions about policies.

o A loss run document can consist of one or more claim. Solution provides all the relevant loss run information for each page of a document.

https://store-images.s-microsoft.com/image/apps.33387.66e870e6-6fbb-407b-9f3c-160b110a3e26.595e268d-1f41-43b9-8d2b-90523d6b8607.b7090b88-fe80-4474-bfab-071e8b9704bf
https://store-images.s-microsoft.com/image/apps.33387.66e870e6-6fbb-407b-9f3c-160b110a3e26.595e268d-1f41-43b9-8d2b-90523d6b8607.b7090b88-fe80-4474-bfab-071e8b9704bf
https://store-images.s-microsoft.com/image/apps.41778.66e870e6-6fbb-407b-9f3c-160b110a3e26.595e268d-1f41-43b9-8d2b-90523d6b8607.ff0909d8-a967-4843-a77a-b49e34792a83