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Willis Towers Watson launches new RiskAgility Financial Modeller

Its calculation engine, available through RiskAgility FM 3.0, enables models to run, on average, 10 times faster than previously possible

Willis Towers Watson has launched a new version of RiskAgility Financial Modeller, its financial modelling and reporting software technology for life insurers. 

RiskAgility FM 3.0 provides life and health insurers with a new calculation approach to actuarial modelling, with run-times typically ten times faster than current software.

Willis Towers Watson’s calculation engine, available through RiskAgility FM 3.0, enables models to run, on average, 10 times faster than previously possible, reducing financial and environmental costs of current hardware or PAYG cloud compute resources. 

The engine has been designed to complement Unify, Willis Towers Watson’s workflow automation and governance platform. 

Mark Brown, global product leader, Life Financial Modelling, Willis Towers Watson, said: “The need to be faster, better and cheaper when delivering actuarial calculations is a concern for many CFOs, CROs and Chief Actuaries. 

“The new calculation engine from Willis Towers Watson has enabled them to make significant improvements in all areas, giving them more confidence in their ability to deliver regulatory and internal reporting on time; and allowing them to better model the risks they cover, leading to significant competitive advantage.”

Marcus Bowser, head of Life Consulting, UK and Ireland, Willis Towers Watson, said: “Solvency II and IFRS 17 require insurers to perform ever more assessments of their balance sheet and profitability, which has inevitably led to a sharp rise in demand for greater computational power and increased infrastructure costs. 

“But now it is possible to cut these costs down to size. The phenomenal performance gains achieved by the RiskAgility FM development team are truly game changing for insurers, and will see significant cost reductions for insurers adopting RiskAgility FM 3.0.”

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