WTW Schedules Feb. 3 Earnings Release, Launches Radar Connector for Databricks
WTW will announce fourth-quarter and full-year 2025 results on February 3, 2026 before market open, with a 9:00 a.m. ET conference call and live webcast. The company launched the Radar Connector for Databricks to accelerate insurance data analytics and governance, enabling minutes-level data updates.
1. WTW to Report Q4 & Full-Year Results on February 3, 2026
WTW will release its fourth quarter and full-year 2025 financial results before U.S. markets open on Tuesday, February 3, 2026. Management will host a live conference call at 9:00 a.m. Eastern Time to discuss revenue trends across its advisory, broking and solutions segments, including performance in key regions such as North America and Asia-Pacific, where WTW operates in 140 countries and markets. Investors will gain insight into segment margins, policyholder services growth rates and capital allocation plans, as well as updated guidance for 2026. An audio webcast will be accessible on the company’s website, with replay available immediately after the call concludes for analysts and institutional participants who register in advance.
2. WTW Launches Radar Connector for Databricks to Enhance Data Sharing
On January 12, 2026, WTW unveiled its new Radar Connector for Databricks, integrating its end-to-end insurance analytics and pricing platform directly with the Databricks Data Intelligence Platform. The integration eliminates manual data transfers and cuts update turnaround time from hours to minutes, enabling users to select Databricks as a data source, run analyses with Radar’s proprietary machine-learning algorithms, and write results back into Databricks within a single, automated workflow. WTW serves over 1,000 insurance clients across six continents and employs more than 1,700 colleagues in 35 markets to support ongoing product innovation. The launch is expected to drive higher client retention in its Insurance Consulting and Technology business by offering faster pricing decisions, unified governance through Unity Catalog, and seamless deployment of Databricks machine-learning models.