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Enhancements To Envestnet’s Recommendations Engine Further Optimize Presentation & Delivery Of Unique Data-Driven Ideas To Help Advisors

Planning Analytics Component & Annuity Data Strengthen Actionable Recommendations & Engagement Opportunities for Advisors

Envestnet has rolled out updates to the new version of its Recommendations Engine, allowing financial advisors at enterprise organizations and Registered Investment Advisers (RIAs) to further optimize client advice and engagement using data from across Envestnet’s financial wellness ecosystem.

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The Recommendations Engine smartly sifts through consumer and industry data throughout the Envestnet platform, as well as data connectors such as Envestnet | MoneyGuide and Salesforce. The engine’s findings power the “Opportunities to Engage” dashboard, which suggests actionable steps that advisors can take based on a client’s unique profile created by machine learning. These timely and relevant data-driven recommendations for engaging clients are presented in a comprehensive, streamlined format.

For example, the Recommendations Engine can flag when a retirement date or other lifecycle event is coming up for a specific client. Similarly, the Engine’s “Opportunities to Engage” dashboard can show advisors which clients have unusually high levels of cash, surfacing data points that highlight opportunities for advisors to meaningfully engage with their clients.

Envestnet Analytics can connect to additional data sources in a variety of formats, and push that data to customer relationship management (CRM) systems like Salesforce and, soon, Microsoft Dynamics—enabling advisors to directly view and choose whether or not to act on recommendations from that data in their current systems.

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“By culling more and more intelligence in our data to help advisors proactively address the needs of individual clients in real time, the Recommendations Engine serves as an essential component of The Intelligent Financial Life,” said Todd Buck, Managing Director and Head of Business Development at Envestnet Analytics. “We continue to implement updates to the Recommendations Engine to give advisors greater insight for discovering opportunities to serve clients more effectively and efficiently.”

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Envestnet’s most recent updates to the Recommendations Engine include:

  • Planning Analytics—Through single-sign-on access to the Recommendations Engine in MoneyGuide, RIAs that utilize the MoneyGuide financial planning solution can receive advisor-level, data-driven recommendations for helping clients adhere to their plans. These recommendations, available to MoneyGuide users that might not utilize Envestnet | Tamarac, are presented in the “Opportunities to Engage” dashboard. In addition, advisors can uncover analytics from MyBlocksSM and MoneyGuide’s Client Portal.
  • Annuity Insights & Strategies—Through a data connection with Fiduciary Exchange, LLC (FIDx), the Recommendations Engine brings advisors actionable insights to benefit their clients using annuities. Intuitive dashboards help advisors target specific opportunities within their books while giving home offices a view of firm-wide opportunities. The Recommendations Engine can show advisors:
  • When an annuity has reached maturity.
  • When the client may benefit by converting a commission-based annuity to a fee-based annuity.
  • When the client can receive more value from new features offered by carriers.

The Recommendations Engine can also help advisors bring a more holistic strategy to their clients by addressing needs—such as income, wealth protection and taxes—that annuities are uniquely designed to tackle.

“An advisor’s book of business can include hundreds of clients, so a powerful, differentiated engine like ours is crucial for identifying opportunities to engage individual clients, and communicating the possible courses of action to take,” said Mr. Buck. “Envestnet’s data and analytics provide the blueprints for how advisors can bring all the pieces together for households, and use these connections to engage with clients at a higher level.”

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