TREND WATCHER: WHAT’S NEXT FOR WEALTH TECH?

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In a bid to dispel the notion that wealth management is lagging behind the digital revolution, the sector has begun to embrace and, dare we say – innovate – in this space.

On the one hand we see global firms actively embrace the rapidly evolving technological landscape – most recently evidenced by global private banks and investment managers acquiring robo-advice platforms, or indeed building and launching their own.

On the other, we see a steadily growing cohort of challengers, eager to disrupt and offer their own innovative solutions to the industry. Indeed, our research finds a steady rise in the number of robo-advisors entering the UK market since 2014, which is likely to continue (and perhaps intensify) while regulation and other factors play catch up (Figure 1).

Figure 1: The rise of robosUltra_Figure1

So it’s safe to say that the wealth sector is catching up with digital demand, but never content to be idle we are now looking ahead for the next big step. The next two stops on the technology road map for wealth will undoubtedly be ‘big data’ and ‘machine learning’.

Big data itself is not really a new concept, but its potential is yet to be fully realised and successes lie far and few between. According to research from My Private Banking, while many firms have implemented big data strategies, these are not executed with a needs-based approach in mind – and therefore can be slow to yield results.

To maximise chances of success, wealth managers and senior stakeholders need to do more to be internally aligned. Having clear business objectives can help identify how best to integrate the technology into a wealth business model, speeding up process and interpretation of results.

Following on from big data is machine learning, which crunches up that data to create an artificial intelligence (AI) solution. AI can quickly learn and call upon a near infinite amount of data to provide thoughtful and informed responses almost instantaneously. Systems can learn and change future behaviour, leading to the creation of more intelligent devices and programs.

Machine learning has already made a splash in the investment world, and is being incorporated by the likes of Blackrock to beat the market by extracting sentiment. According to Gartner, organizations seeking to drive digital innovation with this trend should evaluate a number of business scenarios in which AI and machine learning could drive clear and specific business value, and consider experimenting with one or two high-impact scenarios.

These technologies are just beginning to break out of an emerging state so it will take time for the full benefits of these solutions to be realised.

 Thought for the week:

The science of today is the technology of tomorrow – Edward Teller

 News from the world of wealth:

Morgan Stanley shuffles wealth management unit – Reuters

Deutsche Bank to add more than 50 people to wealth management in Asia – Financial Times

Behind Gender-Pay disparity in wealth management: too few female financiers – WSJ

Millennials: Re-designing wealth management – Business 2 Community

Barclays tohire 100 for private banking push – Citywire

Author: Alexaalexjnder Johnson, Senior Manager

Expertise: Alex sits analytics team at Scorpio Partnership. Is also heavily involved client engagement programmes. He also works alongside other AON and McLagan business lines to help wealth managers link client engagement with pay and productivity.

Background: Alex studied Business Management in Canada at the University of Western Ontario as well as Business Enterprise and IT Management at the University of Chichester in England. Enjoys whiskey, big-budget Hollywood action films & chess-boxing.

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