Collaborating Authors

AI-powered robo adviser takes aim at the richest clients


It's another step in the march toward advice that erodes investors' needs for human help: A robo adviser focused on serving the high-net-worth client, powered by artificial intelligence and designed to automate their specific tax management concerns. Meeting the complicated needs of the wealthy requires a deep knowledge of tax rules and regulations says Hedgeable CEO Mike Kane. "Technology and AI systems can interpret and learn from these rules better than humans can, without our emotional biases." Doubling down on its embrace of Asian themes, Hedgeable's newest offering in its robo platform is a feature called'Tax Samurai,' run by an AI bot called'Katana.' For 30 basis points, it will work for client accounts with a minimum of 1 million to analyze their securities, aggregate all of their financial data, create tax efficient transfers, apply automated downside protection on any current holdings, and perform tax efficient trading and tax-loss harvesting.

How to Build a Robo Advisor: Advice for Starting a Robo Advisory


To provide you with this exclusive report, MyPrivateBanking has partnered with BI Intelligence, Business Insider's premium research service, to create The Complete Robo Advisor Research Collection. If you're involved in the financial services industry at any level, you simply must understand the paradigm shift caused by robo advisors. Investors frustrated by mediocre investment performance, high wealth manager fees and deceptive sales techniques are signing up for automated investment accounts at a record pace. And the robo advisor field is evolving right before our eyes. Firms are figuring out on the fly how to best attract, service and upsell their customers. What lessons are they learning?

9 Questions on Artificial Intelligence for Wealth Management - Wealth Management Today


"I believe that by the end of the century, the use of words will have been altered so much that one will be able to speak of machines thinking without expecting to be contradicted." The foundation of AI started back in 1950 when scientist Alan Turing published a seminal paper containing a description of what is now referred to as the "Turing Test" which is designed to determine if a machine can think. A group of scientists got together at Dartmouth College a few years later and coined the term "artificial intelligence". Fast forward to this year and a panel discussion at the Invest 2017 Conference held in New York City on the ability of AI to revolutionize wealth management. Implementing AI technology is an offensive move all the way, Clinc's Mars stated.

AI Eyes Wealth Management


The conventional wisdom is that that AIs, or robo-advisors, will provide the necessary financial advisement for the retail client, which frees up the advisor to provide more of a human touch to high net worth clients. However, William Trout, senior analyst, wealth management, at industry research firm Celent, has written a new white paper on how AI is moving up the food chain. "What AI is trying to tackle in the wealth management space is cognitive overload and automate discovery," he said. "Humans have a finite ability to keep more than a few things in their minds at any one time. Certainly, a book of 200 clients will provide a challenge for advisors to balance the concerns and interests of all their clients."

The tech edge that could put RIAs on par with wirehouses


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.