Problem Statement

QIC is the market leader in Qatar and a dominant insurer in the GCC and MENA region. Given the significant customer base, a high volume of documentation was required to be processed for issuing Insurance policies. These documents included residence permit cards, vehicle registration forms, driving licenses , etc.The process was completely manual where all the documents submitted were being scanned and stored while also the necessary key details available in these documents were being keyed in manually into the relevant applications. All this manual processing meant that there was significant time lag between submission of an application for insurance and completion of the necessary verification of the documents provided.

Solution Overview

NCompass, after detailed process study and mapping, came up with a custom solution which created significant inroads into a highly automated process. The scope of the automation included optical character recognition of the documents. On upload of the scanned documents, the system applied the necessary intelligence to cleanse the image, remove watermarks, lines, etc. and perform character recognition through algorithms. The digital information extracted was automatically imported into the master application to process the insurance claims. The solution included an integration of a vast stack of technology solutions. Document cleansing using Python, character recognition using google managed services or AWS, grey scale imaging, and API integration with master application for clean data transfer were input parameters for issuance of insurance.


Comprehensive integrated automation enabled the creation of a highly scalable solution which brought in a high level of efficiency and accuracy into the system. An application for insurance which previously took an average TAT of 2 days was now being processed in 30 seconds. Customer satisfaction was a clear extension of the automation.