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Investment Recommendations to Be Automated Like Netflix and Amazon Picks

written by Bella Palmer

We’re all used to Netflix algorithms suggesting films and shows to us based on what our viewing history indicates as statistically likely to also be of interest. Amazon uses similar big data AI algorithms to upsell to users, recommending products based on a buyer’s recent and broader consumer behaviour patterns. Now the Swiss international banking and financial services group UBS is preparing to launch their own version of the breed of predictive behaviour algorithms until now associated with consumer technology companies. The UBS algorithm, however, will recommend trading and investment opportunities to clients investing online.

The project, which is still in the early stages of development, will initially only be available to hedge fund and asset management clients. However, if successful, it would seem likely that retail clients investing online could soon be logging into our investment platform to see ‘you have recently bought X,Y and Z funds. You might also be interested in these…’.

Of course, the challenges posed to an algorithm that recommends trades is very different to one that suggests a new band, TV show or sunglasses. If this form of automation were to cross over into the retail investment space, regulation would certainly have to tentatively navigated. However, if robo advisory platforms can recommend off-the-shelf investment portfolios to beginner investors based on a simple online questionnaire, why would algorithm trades or investment product suggestions offered to experienced DIY investors be problematic for regulators?

Increasing cost pressures on banks and investment platforms currently in the midst of a price war mean investment in technology that automates as many processes as possible is attractive. The sales staff of UBS and other investment platform providers will already call their clients and suggest interesting trades their analysis has highlighted. As explained by Giuseppe Nuti, head of data science for UBS’s FX, rates and credit Strategic Development Lab:

“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. That’s what we are trying to do for our clients, presenting them with a choice of likely, interesting trades.”

At the moment the technology is being trialled in UBS’s corporate bond trading division and recommendations are being sent to sales staff rather than directly to clients. However, if it shows promise the idea is that the middleman, the sales team, will be cut out and the recommendations sent directly to the client. There is, however, some scepticism around the news. Quoted in the Financial Times, Christian Hauff, a co-founder of trading algorithm company Quantitative Brokers, commented:

“Creating and managing a financial instrument portfolio is not the same as creating and managing a playlist”.

Those creating and managing playlists probably said that their job was not the same as creating and managing online shopping suggestions too… Predictive behaviour algorithms may take a little time to make it into the retail investment space but don’t be surprised if AI-powered fund recommendations do and in the not too distant future.


The opinions expressed by our writers are their own and do not represent the views of UK Investment Guides. The information provided on UK Investment Guides is intended for informational purposes only. UK Investment Guides is not liable for any financial losses incurred. Conduct your own research by contacting financial experts before making any investment decisions.

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