A Day in the Life of an AI-Enabled Wealth Manager

A Day in the Life of an AI-Enabled Wealth Manager
By Gavin Spitzner (@gspitzner)

12 June 2022, 10:18am – We begin our story in the not-too-distant future and at 10:18am. Why 10:18am? Our “bionic” AI-enabled wealth manager has just arrived in her office, having had her AI wealth platform rebalance¬† the 376 accounts under her advisement, 47 automated natural language generated messages based on her clients’ transactional data, social media updates, client portal activity and browsing history, and market data having been sent out automatically according to machine learning-based client channel preference and has done more without lifting a finger than she did in a week in her pre-bionic days.

What has she been up to this morning before coming into the office? She met with two clients and working off her AI-driven financial planning tablet application, reviewed progress since their last meeting and provided personalised, prescriptive next-best-action advice and coaching.

And that’s the key: our heroine has learned to leverage data-driven AI to automate and augment tasks that machines outperform humans at and in doing so, freed up enormous sums of time to do what clients will continue to pay for in an era of commoditised investment advice where the race
in fees is to zero: advise and coach in very personalised ways at scale. Later today she is having lunch with a client who has shown up on our dashboard as at high risk based on withdrawals, interaction and performance vs. goals. After that she is meeting with a prospect that based on AI-driven profile-matching algorithms suggested the pairing and has been demonstrated to increase client acquisition success 38%.

While only 25% of firms with $10-50B in assets have even a single deployed AI solution* and fewer than 7% of those sub-$10B, early results show that the AI ROI is powerful. For example, early AI adopter Morgan Stanley has reported material increases in advisor productivity that have more than offset lower average fees.

*World Economic Forum 2018

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