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Envestnet Rolls Out Data-Driven 'Recommendations Engine' for Enterprises

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Envestnet, Inc. (NYSE: ENV) has launched a new version of its Recommendations Engine designed for enterprise organizations. This tool efficiently analyzes wealth and industry data, presenting actionable insights to advisors through the 'Opportunities to Engage' dashboard. It aims to streamline client engagement by alerting advisors of key moments, enabling timely advice tailored to individual client needs. The platform integrates with data sources like Salesforce, enhancing operational efficiency. Interested parties can learn more in a webinar on January 27.

Positive
  • Launch of the enhanced Recommendations Engine improves advisor efficiency.
  • Integrates with popular CRM systems like Salesforce, enabling streamlined workflows.
  • Offers actionable insights based on client profiles, improving client engagement.
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CHICAGO, Jan. 26, 2021 /PRNewswire/ -- Envestnet, Inc. (NYSE: ENV) has announced the launch of the new version of its Recommendations Engine for enterprise organizations.

The Recommendations Engine smartly sifts through the wealth and industry data across Envestnet's unified platform, which includes access to connectors such as Salesforce and MoneyGuide, and powers the "Opportunities to Engage" dashboard, a list of actionable steps that advisors can take based on a client's unique, machine-learning-created profile. These timely, data-driven recommendations for advisors are presented in a comprehensive, streamlined list format.

"Put simply, the Recommendations Engine can save advisors from spending hours—or more—preparing for client meetings," said Todd Buck, Managing Director and Head of Business Development at Envestnet Analytics. "The smart solution can also proactively alert advisors when it may be an opportune time to call a certain client. For example, the system can flag when a key retirement date is upcoming for one of the hundreds upon hundreds of clients an advisor serves. Or maybe it is a good time to talk college savings planning strategies with another client, based on the ages of children in a household. This is next-level innovation, available for Enterprise clients today."

Examples of "opportunities to engage" which can be surfaced by Envestnet's Recommendations Engine include:

  • Underperforming product
  • Unrealized loss in taxable accounts
  • High held-away non-401(k) assets under management (AUM)
  • Life insurance gap
  • Unusually high cash levels

"Giving advice is what advisors do. But giving advice to the right client at the right time is what makes advisors great," said Mr. Buck. "Now, our system can alert an advisor on which clients they may want to call—and why. And what's even more game-changing is that we now have the ability to customize how wide the Engine's reach can go. Making it easier for advisors to give timely advice is one way Envestnet empowers advisors to help make financial wellness a reality for more people." 

Envestnet Analytics can connect to additional data sources in nearly any format to give advisors the most complete set of analytics, and Recommendations from the analytics, possible. These data connectors not only accept additional data, but now have the ability to push data to CRM systems, such as Salesforce and Microsoft Dynamics, to allow advisors to view and act on recommendations directly in the systems where they already work. For example, an advisor can view a client contact, see a list of Envestnet Analytics' data-driven recommendations for that client, obtain details on the underlying data powering the recommendation, reach out to the client, and mark the opportunity as complete—all without leaving their CRM. 

Some examples:

  • Non-Envestnet AUM and transaction data
  • Firm hierarchies, including teams and split rep codes
  • Custom product names
  • Revenue/expense data
  • Sales and activity data

Envestnet rolled out the RIA version of the data-driven, platform-wide engine that serves as a time-saving office assistant for advisors last year.

For more information on this new offering, interested parties can attend a webinar on Wednesday, January 27 at 4:00 pm ET by signing up here:  https://us02web.zoom.us/webinar/register/WN_DYfkiw-TQs-Ei7It6SPSug.

About Envestnet

Envestnet, Inc. (NYSE: ENV) is transforming the way financial advice and wellness are delivered. Our mission is to empower advisors and financial service providers with innovative technology, solutions, and intelligence to make financial wellness a reality for everyone. Over 105,000 advisors across more than 5,100 companies—including 17 of the 20 largest U.S. banks, 47 of the 50 largest wealth management and brokerage firms, over 500 of the largest RIAs, and hundreds of FinTech companies—leverage the Envestnet platform to grow their businesses and client relationships.

For more information on Envestnet, please visit www.envestnet.com, subscribe to our blog, and follow us on Twitter (@ENVintel) and LinkedIn.

Media Contact:
Dana Taormina
JConnelly for Envestnet
973.647.4626
envestnetpr@jconnelly.com

Cision View original content to download multimedia:http://www.prnewswire.com/news-releases/envestnet-rolls-out-data-driven-recommendations-engine-for-enterprises-301215016.html

SOURCE Envestnet, Inc.

FAQ

What is the new Recommendations Engine from Envestnet?

The Recommendations Engine is a tool that analyzes wealth and industry data to provide actionable insights to financial advisors.

When was the Recommendations Engine launched?

The new version of the Recommendations Engine was announced on January 26, 2021.

How does the Recommendations Engine benefit financial advisors?

It saves time by providing timely, data-driven recommendations, allowing advisors to give personalized advice efficiently.

What data sources does the Recommendations Engine connect to?

The engine connects to various data sources, including Salesforce and MoneyGuide, for a comprehensive view of client needs.

How can I learn more about the Recommendations Engine?

You can attend a webinar on January 27 at 4:00 pm ET to learn more about the Recommendations Engine.

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