Summary
This case study outlines the data cleansing and enrichment solution implemented by Xceedance for a global insurance provider facing significant data processing challenges. The client experienced delays in processing time, high lead times for quoting, and an increased need for data cleansing and analysis. To address these issues, Xceedance developed a multi-phase strategy that included the design and implementation of a new data cleansing solution. The process involved transitioning from an Excel-based model to a more robust system capable of ingesting, storing, and mapping data efficiently. The project was divided into phases, including the establishment of a slip interpretation and extraction workflow utilizing natural language processing and machine learning algorithms. The case study details the steps taken to enhance data quality and processing efficiency, ultimately leading to improved operational outcomes for the client. Proven results include a significant reduction in data processing time and an increase in renewal rates and written policies.
