The project aimed to enhance the efficiency of insurance clearance processes. This initiative sought to introduce AI assistance for the extraction of ISO codes from insurance documents, particularly focusing on reducing manual input in the first stage. The project team addressed challenges associated with the manual input of information by developing an AI-assisted solution. Leveraging tools such as Google Cloud Platform's Gen Ai Studio, Document AI, and Google Cloud Vision API, the team extracted data from diverse sources like emails, Accord forms, and the company's Contractors Supplemental Application.

The approach adopted a mixed-method strategy, collecting both qualitative and quantitative data. Insights were gathered from industry professionals and by analyzing processes in-depth. The team explored a range of ISO/NAIC documents and evaluated current AI-assistance technologies. Rigorous model testing was conducted, with a strong focus on ethical practices to ensure data privacy and security, coupled with transparent documentation of the AI's decision-making process. The project underscored the company's dedication to technological progress, promising improved operational excellence and service quality, reinforcing the company's position as an industry leader and innovator.

Keywords: Process Improvement, Clearance and Underwriting, ISO Codes, Insurance, AI