Fundsters in the national accounts side of the business may soon have to woo, or at least work with, a new kind of gatekeeper: algorithms, and the people whose ideas power them.

Multinational financial services giant UBS (among other things, here in the U.S. it is a wirehouse, investment bank, and asset manager) is looking into using recommendation algorithms to suggest trades, the Financial Times reports. The idea is still in early stages and is currently targeted at corporate bond trading clients who are themselves asset managers or hedge fund shops. Yet it's not much of a stretch to imagine a similar engine being used (perhaps by UBS FAs) to recommend funds to individual investors.

UBS is likening the idea to the way Netflix, Pandora, and Spotify try to find music, movies, or TV shows that an individual might like based on what they already like.

"Imagine what the world looked like when you watched television and had to scan through channels, whereas now it is not only on demand, it is presented to you so you easily find what you are looking for," Giuseppe Nuti, head of data science at UBS' strategic development lab for FX, rates, and credit, tells the FT. "That's what we are trying to do for our clients, presenting them with a choice of likely, interesting trades."

In some ways, working with providers of these kinds of algorithms might be similar to working with TAMPs, ETF strategists, roboadvisors, and model portfolio analysts. Yet national accounts and marketers may find themselves pushing products in different ways, to offer data and tidbits that could be useful for a recommendation engine.

We'll see who brings this tech to retail wealth management first. 

Edited by: Neil Anderson, Managing Editor


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