WTW (Willis Towers Watson, NASDAQ: WTW) has announced the launch of the newest version of its market-leading Radar software. Radar 4.14 now features a fully integrated Python capability, allowing insurers simultaneously to benefit from the advanced pricing capabilities of Radar and the power of innovative open source software, all within a well-governed environment.
At the same time that collaboration between users became harder during the pandemic, with working practices radically transformed, regulatory scrutiny of insurers’ analytical methods intensified. Demand to adjust quickly to market shocks escalated, as well as the ability to automate processes. This market disruption also increased pressure on insurers to introduce enhanced governance and security controls around their pricing capabilities.
Serhat Guven, Managing Director at WTW, said: “Integrating Python with Radar gives insurers fast and easy access to latest developments from the open source world in a reliable, low-risk and well-governed way, supported by more than 20 years of WTW software development experience and insurance expertise.”
In addition to addressing security and governance-related concerns that previously prevented insurers from applying open source software more widely, the new version of Radar offers enhanced functionality and user experience. Integrating Python with Radar gives users access to a wider range of options when selecting the optimal tool for a specific project and the flexibility to adapt to a rapidly-changing technology environment.
Guven added: “Radar technology has always led the market in its ability to develop and deploy complex rating algorithms with ease and at speed, supported by a transparent and sophisticated governance capability. Seamlessly incorporating open source models, such as Python, represents the next step in Radar’s continued evolution and our ongoing commitment to deliver leading-edge pricing techniques that respond to changing market conditions and help insurers improve operational efficiency, speed to market and pricing accuracy.”