Life - Articles - Willis Towers Watson launches vGrid 2.0

 The computational grid solution gives life insurers on-demand access to scalable computing power to help them meet ever-reducing reporting timetables. Tests of vGrid 2.0, concluded by Willis Towers Watson, confirm the latest upgrades have resulted in runtime improvements of between 20% to 30%.

 Stephen Hollands, Global Product Leader at Willis Towers Watson, said: “An independent assessment of an insurance industry client showed a 27% cost saving by switching to vGrid compared to running their own on-premise system. We would also expect the strong performance gains from the new version to deliver further cost savings.”

 According to Willis Towers Watson, the ability to achieve quicker results and execute more complex run scenarios will make it easier for insurers to respond to both changing regulatory requirements and internal pressure to improve business performance.

 Stephen Hollands, said: “Managing large compute capacity and complex IT infrastructure can be expensive, especially when demand is variable. vGrid 2.0 is another step change in delivering an efficient, scalable and secure environment, allowing users to further increase their processing power as and when they need it, without the high ongoing costs of when they don’t.”

 Additional security features have been added to the ‘pay-as-you-go’ virtual grid technology to ensure compatibility with in-house IT policies and requirements. For example, vGrid 2.0 now includes multi-factor authentication, reflecting a requirement for many companies to reduce the risk of access credentials for web applications and services being compromised or shared. Also, companies are now able to set their own timings for when their data will automatically be cleaned from vGrid’s cloud storage.

 Willis Towers Watson’s latest vGrid software is designed to complement its RiskAgility Financial Modeller (RiskAgility FM), which helps life insurers to develop and run financial models to better manage risk and safeguard solvency.