WTW and IMT team up on SaaS insurance solution


WTW, a global advisory, broking, and solutions company, has partnered with property & casualty insurer IMT Insurance to implement an SaaS solution.

IMT Insurance writes personal and commercia lines insurance in six US states, with nearly $300m in direct written premiums. The company has licensed Radar Live SaaS, WTW’s pricing delivery software.

WTW a global advisory, broking, and solutions company, provides data-driven, insight-led solutions in the areas of people, risk and capital.

According to WTW, Radar Live SaaS delivers ground-breaking capabilities from Radar Live, including its machine-learning predictive power, rate deployment speed, and calculation flexibility in addition to freeing the company from complex software and hardware management issues.

IMT selected WTW’s solution because it did not want to be constrained by “out-of-the-box” technology, according to Sean Kennedy, president and CEO of the company.

“Our goal is to implement a single rating engine for use on all property/casualty lines of business by connecting its proprietary policy administration system. We want to empower and enable our actuarial team to design and implement well-governed rating decisions, independent of IT,” Kennedy said.

Serhat Guven, managing director, WTW, added, “Our work with IMT demonstrates our commitment to delivering solutions for clients to achieve rating transformation and deliver significant efficiency gains that can be integrated with most policy systems,” said “IMT viewed Radar and Radar Live as unique and valuable, but recognized that integrating SaaS can bring growth. Radar Live is a sophisticated tool of choice. To grow and scale effectively, they recognize the importance of maintenance and governance and view this solution as the right platform.”

Earlier this year, Willis Tower Watson (WTW), in partnership with Solera Audatex, has launched a price inflation forecasting tool for auto insurers.

The tool uses Audatex’s repair data, which cover 98% of all UK vehicles, augmented by machine learning and comprehensive historical data analysis by WTW.

WTW said the technology has been developed to predict inflationary effects on vehicle repair costs for multiple vehicle categories.

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