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Franklin Templeton Teams with vWise on Personalized Investment Solutions

Service Providers

Franklin Templeton has collaborated with California-based vWise, Inc. to integrate technology, predictive analytics and behavioral finance to deliver a personalized investment solution to improve retirement outcomes in DC plans.

According to the July 7 announcement, Franklin Templeton’s patent-pending Goals Optimization Engine (GOE), combined with vWise’s Experience Platform, will use real-time participant data to deliver personalized experiences that encourage participants to take actions that better prepare them for retirement. Additionally, Mary Beth Glotzbach, Senior Institutional DC Strategist for Franklin Templeton, has been named to the vWise board.

“The workplace is the financial hub for many American workers and our collaboration with vWise will enable us to deliver on our commitment to personalization,” said Glotzbach. “We can now bring to DC plan participants the same level of personalized recommendations we’ve all come to expect in other aspects of our lives.” 

vWise’s technology enables financial service providers to aggregate data and build participant profiles, apply a customized rules engine that selects the best “call to action” and delivers a personal experience. The vWise Experience platform is designed to be effective in institutional, advisor sold and retail financial verticals, the announcement notes. 

“Our open-platform approach is the key to unlocking more targeted communications and, in turn, more engaged participants,” notes David Ferrigno, CEO of vWise. “Aggregating data from multiple sources—our clients, their clients and their partners—allows vWise to deliver personalized communications based on relevant demographic and financial characteristics.”

GOE is an open-architecture offering that combines a proprietary algorithm, detailed capital market expectations and a set of parameters for each goal provided by the investor. GOE is designed to take these parameters and optimize the asset allocation to maximize the probability of successfully achieving the goal by applying machine learning. DC participants will have the option to provide additional information and then choose what portion of their account balance they would like to invest in Franklin Templeton’s model portfolios. 

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