Data Vera for Exposure Management
Data Vera for Exposure Management – Improving SOV cleansing efficiency and confidence.
The below case study outlines the improvements to SOV cleansing efficiency and confidence one of our clients gained after implementing Data Vera for Exposure Management.
CATEX engaged with a large multi-national insurer, who was struggling to cleanse, validate and prepare the increasing number of SOVs they were receiving for modelling. This process was a labour intensive, manual effort performed largely using spreadsheet templates, drawing data from multiple distinct sources. Due to the quality of the SOVs received a significant amount of augmentation to the SOVs was required to make them ready for modelling and facilitate accurate pricing of each account. As the volume and size of SOVs received by the insurer increased, the confidence in this manual process decreased due to the error prone nature of manual cleansing and the lack of audit available on any changes made.
CATEX embarked on a custom implementation project to elevate the insurer out of their legacy manual processes, leveraging machine learning, API integration and automated workflows to boost efficiency and confidence in the quality data produced from the SOV cleansing process. The project resulted in the following improvements:
The system is hosted at an SSAE16 facility that adheres to the highest industry standards for data protection and operational controls. Real-time data backup at a secondary facility — located thousands of miles away from the primary site — provides robust disaster recovery capabilities. This remote setup ensures the safety and integrity of the carrier’s critical data, providing peace of mind and protecting the carrier from the consequences of disruptions. Additional security is provided by CATEX’s designation as ISO/IEC 27001:2013 compliant indicating that CATEX’s internal processes, data handling, software development practices adhere to industry best practices and are regularly audited by a third-party firm.