Willis Towers Watson (WTW) has introduced the Radar Connector for Snowflake, aimed at improving the functionality of its Radar insurance analytics and pricing platform.  

Radar, designed for the insurance sector, features machine learning algorithms and supports real-time decision-making and regulatory reporting.  

The collaboration with Snowflake, an AI data cloud company, allows Radar users to securely access data directly from the Snowflake platform. 

Analysts working with Radar can gain access to raw data by choosing Snowflake as a data source and then retrieve this data from the platform in one step. Following completion of their analysis, users can then directly transfer the results back into Snowflake. 

The Radar Connector for Snowflake streamlines data handling by eliminating the delays associated with file export and import, drastically cutting down the time and effort involved compared to conventional methods.  

A data update that once took several hours can now be accomplished in minutes, offering a substantial boost in efficiency. Furthermore, since the data remains within the Snowflake and Radar ecosystem, security is enhanced, and the process can be governed more effectively from start to finish, stated WTW. 

Snowflake Financial Services global head Rinesh Patel said: “This integration replaces a manual, complex workflow with a streamlined, automated process. The Radar Connector for Snowflake enables increased speed, accuracy and security, allowing teams to dedicate more time to analysis instead of operational tasks.  

“We are excited to bring this connector to market by combining the strengths of both Radar and our easy, connected and trusted platform.” 

The Radar Connector for Snowflake is stated to offer a range of advantages including a streamlined one-click data transfer that eliminates the need for cumbersome export/import cycles, thus simplifying the process significantly.  

It provides near-instant access to data, accelerating analysis and model deployment, leading to faster insights.  

The automated pipeline reduces human error associated with manual file handling, enhancing accuracy and reliability.  

Furthermore, it introduces bi-directional integration, allowing users to directly write results back into Snowflake, effectively closing the loop without additional steps.  

It also supports scalability by seamlessly integrating with existing workflows and tools like business intelligence dashboards, accommodating data growth easily.  

Additionally, it is claimed to be cost-effective, as it enhances data accessibility and reduces the necessity for custom integration solutions, ultimately saving both time and resources.  

WTW Insurance Consulting and Technology senior director Chris Halliday said: “The integration of Radar with Snowflake enables insurers to seamlessly access data from Snowflake for better-informed analysis.” 

In September, Sompo Group forged an alliance with WTW to utilise Radar technology in its non-life insurance offerings.