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Salesforce says AI can pinpoint unhappy clients

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Salesforce is betting advisors are willing to pay for software that could give them a heads-up about clients who are potentially headed for the door.

The leading CRM provider by market share is rolling out Einstein Analytics, a platform designed specifically for wealth advisors, retail bankers, managers and other financial services professionals.

“There’s been an explosion of data that’s available at an advisor’s fingertips,” says Rohit Mahna, senior vice president at Salesforce. “It’s not just talking about alpha and giving stock tips anymore. With a more goals-based planning model, there is a lot of data and it is coming much faster.”

Einstein allows advisors to analyze an entire book of business with an eye toward measuring the health of client relationships. For example, the artificial intelligence-based algorithm delivers a churn statistic that demonstrates the probability that a client is unhappy and is likely to take their money and move to another wealth manager. The scores are based on actions from previous clients that left the firm.

Using advanced analytics, advisors can also identify the clients who aren't meeting their financial goals and create a task to reach out to them directly from the analytics dashboard, according to the firm.

“It’s a lot of effort for a financial advisor to get a client on board,” Manha says. “The last thing you want to see is a client leave you.”

The upgrade, an add-on to the firm’s Financial Services Cloud package, will cost advisors $150 per account-user per month. Financial Services Cloud, which also costs $150 per user per month, had its last major upgrade in October and was geared to streamlining the onboarding process and flagging tasks needing additional oversight.

Salesforce's Einstein makes more than four billion business analytics predictions per day, according to ARK Investment Management data which was presented at the Investments & Wealth Institute annual conference in Las Vegas this week. Salesforce reported two billion AI predictions per day in May 2018.

“We think AI, and it’s really deep learning, which is a subset of AI, is going to impact every line of the income statement," said Catherine Wood, CEO of ARK Investment Management at the conference. "Any business leader not using it or figuring out how to use it is going to be at a severe competitive disadvantage. We are in the arms race right now.”

However, Salesforce cannot guarantee its profitability yet, according to documents the firm filed with the SEC. "The markets for certain of our offerings, including our Einstein artificial intelligence and data integration offerings, remain relatively new and it is uncertain whether our efforts, and related investments, will ever result in significant revenue for us," according to the document.

There's additional competition also, as Salesforce isn't the only tech vendor offering such predictive analytics about client attitudes. IBM's AI engine, Watson, powers its wealth management offering.

CRM tools are still the most-used wealth management technology, according to Financial Planning’s 2019 Tech survey. Nine out of every 10 advisors surveyed use a CRM tool — more than any other technology offering. Salesforce is the dominant CRM provider, according to the survey. Almost 23% of all advisors use the firm’s software ahead of both Redtail (22.1%) and Microsoft Outlook (14.3%).

“Advisors are being asked to produce more on their own with less support from the home office,” Mahna says.

Competitors like Redtail have upgraded their own systems to incorporate new technology such as machine learning. The Sacramento, California-based fintech rolled out AI capabilities last year that help advisors respond to questions via text message and categorize client inquiries.

The first chapter of the Salesforce tool was about productivity, Mahna says. The upgrade provides deeper analysis, especially regarding information about internal and external client accounts, he says. For example, users can bring in data on outside loan payments and credit card balances, as well as customer satisfaction data.

“Now, we asked, how can we make advisors smarter,” Manha says.

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