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The tech edge that could put RIAs on par with wirehouses

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Artificial intelligence can help businesses identify new clients and streamline back office operations, but so far, only the largest companies have found the data-heavy tech practical.

Early adopters of artificial intelligence are expecting substantial increases in profitability in 2018, according to the Nationwide’s Advisor Authority survey of 1,700 advisors. But, those that used big data were also more likely to have sizeable assets under management, over $250 million in AUM and incomes of more than $500,000.

That’s because, for more modest firms, fewer clients mean less reliable data. “Wealth managers are still struggling to get a consistent line of sight on customer data and that includes things like demographics and transaction data,” says William Trout, senior analyst at the consulting firm Celent. “To what extent will that lack of visibility — and ultimately understanding of the client — inhibit the delivery of services.”

Data sets are growing increasingly important to wealth management firms, information like purchasing power, life events and even website browsing history, according to a new study by Celent. Of value to wealth managers, in particular, are signals regarding financial information for credit, insurance and investment decisions; and, habits and hobbies to analyze retirement and lifestyle planning, according to the study.

“Data-based analytics and decision tools can support productivity by pinpointing client psychosocial and financial requirements,” Trout says. “These insights must be integrated into the CRM system and provided on-the-go in something close to real time.”

Larger firms have traditionally feasted on these data sets. Tech firms like Facebook, Google and Alibaba use them to visualize connections between customers and create powerful information advantages, he says. “Every piece of data is connected or related in a logical fashion and frankly that’s why Amazon can get a direct line on customers,” Trout says. “Does a customer buy a lot of expensive camping gear? Then, they have time to vacation, and ultimately expendable cash.”

External market signals are utilized as well, he says. “Portfolio management is being commoditized and advisors that can connect the fall of the Turkish lira to foreign exposure in clients’ portfolios — those advisors are going to be around for a while,” Trout says.

“Amazon and others that build their platforms on knowledge-graph technology may market this intelligence to wealth managers — or potentially become ones themselves,” Trout says.

However, advanced analytics are slowly becoming more accessible to RIAs. Some are even available on the cloud from Software-as-a-service companies for under $100 a month, Trout says. Firms like FinMason and WisdomTree are examples, he says.

Boston-based, LifeYield, which provides its platform to LPL, Morgan Stanley and others, offers two tools to help RIAs gather insights about clients, says former LPL chief Mark Casady. First is a tool to estimate when clients should cash in their social security checks, and another more important tool determines the most tax advantaged vehicles for wealthy clients to place their assets.

“An algorithm that can pull a lot of data together and create better outcomes that take away the drudgery from RIAs is the smart way to go,” Casady says.

Partnerships are also blossoming. Orion Advisor Services recently announced a partnership with FinMason to offer native Monte Carlo capabilities, says the firm.

While larger firms have a head start, they have their own sets of problems to unravel, Trout says. “The fact remains that data still resides in silos and that effects the client experience whether it’s a lack of a single sign up or not being able to get real time information on a portfolios,” he says. “There’s still a long way to go.”

In many cases technology was fashioned one layer lumped on top of the next and large institutions have multiple lines of business, various services units that are walled off from each other. “They don’t communicate well, and it requires a lot of people to flag issues and resolve them manually,” Trout says. “That’s before anyone can even start to analyze the data for any insights.”

For Trout, data has become the “life blood” of the financial services industry and firms should be doing their best to catch up. “Until firms figure out how to get clean data, they’re not going to be able improve delivery.”

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